Many applications of robots in collaboration with humans require the robot to follow the person autonomously. Depending on the tasks and their context, this type of tracking can be a complex problem. The paper proposes and evaluates a principle of control of autonomous robots for applications of services to people, with the capacity of prediction and adaptation for the problem of following people without the use of cameras (high level of privacy) and with a low computational cost. A robot can easily have a wide set of sensors for different variables, one of the classic sensors in a mobile robot is the distance sensor. Some of these sensors are capable of collecting a large amount of information sufficient to precisely define the positions of objects (and therefore people) around the robot, providing objective and quantitative data that can be very useful for a wide range of tasks, in particular, to perform autonomous tasks of following people. This paper uses the estimated distance from a person to a service robot to predict the behavior of a person, and thus improve performance in autonomous person following tasks. For this, we use an adaptive fuzzy neural network (AFNN) which includes a fuzzy neural network based on Takagi-Sugeno fuzzy inference, and an adaptive learning algorithm to update the membership functions and the rule base. The validity of the proposal is verified both by simulation and on a real prototype. The average RMSE of prediction over the 50 laboratory tests with different people acting as target object was 7.33.
Identifier of human emotions based on convolutional neural network for assist...TELKOMNIKA JOURNAL
This paper proposes a solution for the problem of continuous prediction in real-time of the emotional state of a human user from the identification of characteristics in facial expressions. In robots whose main task is the care of people (children, sick or elderly people) is important to maintain a close relationship man-machine, anld a rapid response of the robot to the actions of the person under care. We propose to increase the level of intimacy of the robot, and its response to specific situations of the user, identifying in real time the emotion reflected by the person's face. This solution is integrated with algorithms of the research group related to the tracking of people for use on an assistant robot. The strategy used involves two stages of processing, the first involves the detection of faces using HOG and linear SVM, while the second identifies the emotion in the face using a CNN. The strategy was completely tested in the laboratory on our robotic platform, demonstrating high performance with low resource consumption. Through various controlled laboratory tests with different people, which forced a certain emotion on their faces, the scheme was able to identify the emotions with a success rate of 92%.
This paper reports results of artificial neural network for robot navigation tasks. Machine
learning methods have proven usability in many complex problems concerning mobile robots
control. In particular we deal with the well-known strategy of navigating by “wall-following”.
In this study, probabilistic neural network (PNN) structure was used for robot navigation tasks.
The PNN result was compared with the results of the Logistic Perceptron, Multilayer
Perceptron, Mixture of Experts and Elman neural networks and the results of the previous
studies reported focusing on robot navigation tasks and using same dataset. It was observed the
PNN is the best classification accuracy with 99,635% accuracy using same dataset.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
AN APPROACH OF IR-BASED SHORT-RANGE CORRESPONDENCE SYSTEMS FOR SWARM ROBOT BA...ijaia
This paper exhibits a short-run correspondence method appropriate for swarm versatile robots application.
Infrared is utilized for transmitting and accepting information and obstruction location. The infrared
correspondence code based swarm signaling is utilized for an independent versatile robot communication
system in this research. A code based signaling system is developed for transmitting information between
different entities of robot. The reflected infrared sign is additionally utilized for separation estimation for
obstruction evasion. Investigation of robot demonstrates the possibility of utilizing infrared signs to get a
solid nearby correspondence between swarm portable robots. This paper exhibits a basic decentralized
control for swarm of self-collecting robots. Every robot in the code based swarm signaling is completely
self-governing and controlled utilizing a conduct based methodology with just infrared-based nearby
detecting and correspondences. The viability of the methodology has been checked with simulation, for a
set of swarm robots.
Machine Learning approach for Assisting Visually ImpairedIJTET Journal
Abstract- India has the largest blind population in the world. The complex Indian environment makes it difficult for the people to navigate using the present technology. In-order to navigate effectively a wearable computing system should learn the environment by itself, thus providing enough information for making visually impaired adapt to the environment. The traditional learning algorithm requires the entire percept sequence to learn. This paper will propose algorithms for learning from various sensory inputs with selected percept sequence; analyze what feature and data should be considered for real time learning and how they can be applied for autonomous navigation for blind, what are the problem parameters to be considered for the blind navigation/protection, tools and how it can be used on other application.
Identifier of human emotions based on convolutional neural network for assist...TELKOMNIKA JOURNAL
This paper proposes a solution for the problem of continuous prediction in real-time of the emotional state of a human user from the identification of characteristics in facial expressions. In robots whose main task is the care of people (children, sick or elderly people) is important to maintain a close relationship man-machine, anld a rapid response of the robot to the actions of the person under care. We propose to increase the level of intimacy of the robot, and its response to specific situations of the user, identifying in real time the emotion reflected by the person's face. This solution is integrated with algorithms of the research group related to the tracking of people for use on an assistant robot. The strategy used involves two stages of processing, the first involves the detection of faces using HOG and linear SVM, while the second identifies the emotion in the face using a CNN. The strategy was completely tested in the laboratory on our robotic platform, demonstrating high performance with low resource consumption. Through various controlled laboratory tests with different people, which forced a certain emotion on their faces, the scheme was able to identify the emotions with a success rate of 92%.
This paper reports results of artificial neural network for robot navigation tasks. Machine
learning methods have proven usability in many complex problems concerning mobile robots
control. In particular we deal with the well-known strategy of navigating by “wall-following”.
In this study, probabilistic neural network (PNN) structure was used for robot navigation tasks.
The PNN result was compared with the results of the Logistic Perceptron, Multilayer
Perceptron, Mixture of Experts and Elman neural networks and the results of the previous
studies reported focusing on robot navigation tasks and using same dataset. It was observed the
PNN is the best classification accuracy with 99,635% accuracy using same dataset.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
AN APPROACH OF IR-BASED SHORT-RANGE CORRESPONDENCE SYSTEMS FOR SWARM ROBOT BA...ijaia
This paper exhibits a short-run correspondence method appropriate for swarm versatile robots application.
Infrared is utilized for transmitting and accepting information and obstruction location. The infrared
correspondence code based swarm signaling is utilized for an independent versatile robot communication
system in this research. A code based signaling system is developed for transmitting information between
different entities of robot. The reflected infrared sign is additionally utilized for separation estimation for
obstruction evasion. Investigation of robot demonstrates the possibility of utilizing infrared signs to get a
solid nearby correspondence between swarm portable robots. This paper exhibits a basic decentralized
control for swarm of self-collecting robots. Every robot in the code based swarm signaling is completely
self-governing and controlled utilizing a conduct based methodology with just infrared-based nearby
detecting and correspondences. The viability of the methodology has been checked with simulation, for a
set of swarm robots.
Machine Learning approach for Assisting Visually ImpairedIJTET Journal
Abstract- India has the largest blind population in the world. The complex Indian environment makes it difficult for the people to navigate using the present technology. In-order to navigate effectively a wearable computing system should learn the environment by itself, thus providing enough information for making visually impaired adapt to the environment. The traditional learning algorithm requires the entire percept sequence to learn. This paper will propose algorithms for learning from various sensory inputs with selected percept sequence; analyze what feature and data should be considered for real time learning and how they can be applied for autonomous navigation for blind, what are the problem parameters to be considered for the blind navigation/protection, tools and how it can be used on other application.
Mobile robot controller using novel hybrid system IJECEIAES
Hybrid neuro-fuzzy controller is one of the techniques that is used as a tool to control a mobile robot in unstructured environment. In this paper a novel neuro-fuzzy technique is proposed in order to tackle the problem of mobile robot autonomous navigation in unstructured environment. Obstacle avoidance is an important task in the field of robotics, since the goal of autonomous robot is to reach the destination without collision. The objective is to make the robot move along a collision free trajectory until it reaches its target. The proposed approach uses the artificial neural network instead of the fuzzified engine then the output from it is processed using adaptive inference engine and defuzzification engine. In this approach, the real processing time is reduced that is increase the mobile robot response. The proposed neuro-fuzzy controller is evaluated subjectively and objectively with other approaches and also the processing time is taken in consideration.
Autonomous system to control a mobile robotjournalBEEI
This paper presents an ongoing effort to control a mobile robot in unstructured environment. Obstacle avoidance is an important task in the field of robotics, since the goal of autonomous robot is to reach the destination without collision. Several algorithms have been proposed for obstacle avoidance, having drawbacks and benefits. In this paper, the fuzzy controller is used to tackle the problem of mobile robot autonomous navigation in unstructured environment. The objective is to make the robot move along a collision free trajectory until it reaches its target. The proposed approach uses the fuzzified, adaptive inference engine and defuzzification engine. Also number of linguistic labels is optimized for the input of the mobile robot in order to reduce computational time for real-time applications. The proposed fuzzy controller is evaluated subjectively and objectively with other approaches and also the processing time is taken in consideration.
Intelligent Robotics Navigation System: Problems, Methods, and Algorithm IJECEIAES
This paper set out to supplement new studies with a brief and comprehensible review of the advanced development in the area of the navigation system, starting from a single robot, multi-robot, and swarm robots from a particular perspective by taking insights from these biological systems. The inspiration is taken from nature by observing the human and the social animal that is believed to be very beneficial for this purpose. The intelligent navigation system is developed based on an individual characteristic or a social animal biological structure. The discussion of this paper will focus on how simple agent’s structure utilizes flexible and potential outcomes in order to navigate in a productive and unorganized surrounding. The combination of the navigation system and biologically inspired approach has attracted considerable attention, which makes it an important research area in the intelligent robotic system. Overall, this paper explores the implementation, which is resulted from the simulation performed by the embodiment of robots operating in real environments.
USING THE MANDELBROT SET TO GENERATE PRIMARY POPULATIONS IN THE GENETIC ALGOR...csandit
Nowadays, finding a way to secure media is common with the growth of digital media. An
effective method for the secure transmission of images can be found in the field of visual
cryptography. There is a growing interest in the use of visual cryptography in security
application. Since this method is used for secure transmission of images, many of the methods
are developed based on the original algorithm proposed by Naor and Shamir in 1994. In this
paper, a new hybrid model is used in cryptography of images which is composed of Mandelbrot
algorithm and genetic algorithm. In the early stages of proposal, a number of encrypted images
are made by using the Mandelbrot algorithm and the original picture and in the next stage,
these encrypted images are used as the initial population for the genetic algorithm. At each
stage of the genetic algorithm, the answer of previous iterations is optimized to get the best
encoding image. Also, in the proposed method, we can achieve the decoded image by a reverse
operation from the genetic algorithm. The best encrypted image is an image with high entropy
and low correlation coefficient. According to the entropy and correlation coefficient of the
proposed method compared with existing methods, it is observed that our method gets better
results in both of them.
MUE2012-Space-aware Design Factors for Located Learning Activities Supported ...Mar Pérez-Sanagustín
presented at the 6th International Conference on Multimedia and Ubiquitous Engineering (MUE, 2012) the paper “Space-aware Design FActors for Located Learning Activities Supported with Smart Phones” a work by Patricia Santos, Mar Pérez-Sanagustín, Davinia Hernández-Leo & Josep Blat.
A Robot Collision Avoidance Method Using Kinect and Global VisionTELKOMNIKA JOURNAL
This paper introduces a robot collision avoidance method using Kinect and global vision to
improve the industrial robot’s security. Global vision is installed above the robot, and a combination of the
background-difference method and the Otsu algorithm are used. Human skeleton detection is then
introduced to detect the location information of the human body. The collided objects are classified into
nonhuman and human obstacle which is further categorized into the human head and non-head areas
such as the arm. The Kalman filter is used to predict the human gesture. The human joints danger index is
used to evaluate the risk level of the human on the basis of human body joints and robot’s motion
information. Finally, a motion control strategy is adopted in view of obstacle categories and the human joint
danger index. Results show that the proposed method can effectively improve robot’s security in real time.
Robust and Efficient Coupling of Perception to Actuation with Metric and Non-...Darius Burschka
The talk motivates a re-thinking of the way, how perception passes the information to the control modules. Metric information is not a native space of the camera and apparently also not used in biology for navigation. Early abstraction of information from images loses a lot of important information that can be directly used for following (Visual-Servoing), motion estimation(Motion Blurr), and collision relations(Optical Flow Clustering). I present in this talk ways, how we use the image information in "classical way" that does not require any learning and runs on low-power CPUs.
Deep Learning - a Path from Big Data Indexing to Robotic ApplicationsDarius Burschka
These are the slides to my ShanghAI lecture from Dec 10, 2020. It proposes necessary extensions to make DeepNets appropriate tools for robotic systems.
The talk can be found on https://fb.watch/2hXDC6K4Pq/
A novel visual tracking scheme for unstructured indoor environmentsIJECEIAES
In the ever-expanding sphere of assistive robotics, the pressing need for advanced methods capable of accurately tracking individuals within unstructured indoor settings has been magnified. This research endeavours to devise a realtime visual tracking mechanism that encapsulates high performance attributes while maintaining minimal computational requirements. Inspired by the neural processes of the human brain’s visual information handling, our innovative algorithm employs a pattern image, serving as an ephemeral memory, which facilitates the identification of motion within images. This tracking paradigm was subjected to rigorous testing on a Nao humanoid robot, demonstrating noteworthy outcomes in controlled laboratory conditions. The algorithm exhibited a remarkably low false detection rate, less than 4%, and target losses were recorded in merely 12% of instances, thus attesting to its successful operation. Moreover, the algorithm’s capacity to accurately estimate the direct distance to the target further substantiated its high efficacy. These compelling findings serve as a substantial contribution to assistive robotics. The proficient visual tracking methodology proposed herein holds the potential to markedly amplify the competencies of robots operating in dynamic, unstructured indoor settings, and set the foundation for a higher degree of complex interactive tasks.
Robot operating system based autonomous navigation platform with human robot ...TELKOMNIKA JOURNAL
In emerging technologies, indoor service robots are playing a vital role for people who are physically challenged and visually impaired. The service robots are efficient and beneficial for people to overcome the challenges faced during their regular chores. This paper proposes the implementation of autonomous navigation platforms with human-robot interaction which can be used in service robots to avoid the difficulties faced in daily activities. We used the robot operating system (ROS) framework for the implementation of algorithms used in auto navigation, speech processing and recognition, and object detection and recognition. A suitable robot model was designed and tested in the Gazebo environment to evaluate the algorithms. The confusion matrix that was created from 125 different cases points to the decent correctness of the model.
A one decade survey of autonomous mobile robot systems IJECEIAES
Recently, autonomous mobile robots have gained popularity in the modern world due to their relevance technology and application in real world situations. The global market for mobile robots will grow significantly over the next 20 years. Autonomous mobile robots are found in many fields including institutions, industry, business, hospitals, agriculture as well as private households for the purpose of improving day-to-day activities and services. The development of technology has increased in the requirements for mobile robots because of the services and tasks provided by them, like rescue and research operations, surveillance, carry heavy objects and so on. Researchers have conducted many works on the importance of robots, their uses, and problems. This article aims to analyze the control system of mobile robots and the way robots have the ability of moving in real-world to achieve their goals. It should be noted that there are several technological directions in a mobile robot industry. It must be observed and integrated so that the robot functions properly: Navigation systems, localization systems, detection systems (sensors) along with motion and kinematics and dynamics systems. All such systems should be united through a control unit; thus, the mission or work of mobile robots are conducted with reliability.
Acoustic event characterization for service robot using convolutional networksIJECEIAES
This paper presents and discusses the creation of a sound event classification model using deep learning. In the design of service robots, it is necessary to include routines that improve the response of both the robot and the human being throughout the interaction. These types of tasks are critical when the robot is taking care of children, the elderly, or people in vulnerable situations. Certain dangerous situations are difficult to identify and assess by an autonomous system, and yet, the life of the users may depend on these robots. Acoustic signals correspond to events that can be detected at a great distance, are usually present in risky situations, and can be continuously sensed without incurring privacy risks. For the creation of the model, a customized database is structured with seven categories that allow to categorize a problem, and eventually allow the robot to provide the necessary help. These audio signals are processed to produce graphical representations consistent with human acoustic identification. These images are then used to train three convolutional models identified as high-performing in this type of problem. The three models are evaluated with specific metrics to identify the best-performing model. Finally, the results of this evaluation are discussed and analyzed.
Mobile robot controller using novel hybrid system IJECEIAES
Hybrid neuro-fuzzy controller is one of the techniques that is used as a tool to control a mobile robot in unstructured environment. In this paper a novel neuro-fuzzy technique is proposed in order to tackle the problem of mobile robot autonomous navigation in unstructured environment. Obstacle avoidance is an important task in the field of robotics, since the goal of autonomous robot is to reach the destination without collision. The objective is to make the robot move along a collision free trajectory until it reaches its target. The proposed approach uses the artificial neural network instead of the fuzzified engine then the output from it is processed using adaptive inference engine and defuzzification engine. In this approach, the real processing time is reduced that is increase the mobile robot response. The proposed neuro-fuzzy controller is evaluated subjectively and objectively with other approaches and also the processing time is taken in consideration.
Autonomous system to control a mobile robotjournalBEEI
This paper presents an ongoing effort to control a mobile robot in unstructured environment. Obstacle avoidance is an important task in the field of robotics, since the goal of autonomous robot is to reach the destination without collision. Several algorithms have been proposed for obstacle avoidance, having drawbacks and benefits. In this paper, the fuzzy controller is used to tackle the problem of mobile robot autonomous navigation in unstructured environment. The objective is to make the robot move along a collision free trajectory until it reaches its target. The proposed approach uses the fuzzified, adaptive inference engine and defuzzification engine. Also number of linguistic labels is optimized for the input of the mobile robot in order to reduce computational time for real-time applications. The proposed fuzzy controller is evaluated subjectively and objectively with other approaches and also the processing time is taken in consideration.
Intelligent Robotics Navigation System: Problems, Methods, and Algorithm IJECEIAES
This paper set out to supplement new studies with a brief and comprehensible review of the advanced development in the area of the navigation system, starting from a single robot, multi-robot, and swarm robots from a particular perspective by taking insights from these biological systems. The inspiration is taken from nature by observing the human and the social animal that is believed to be very beneficial for this purpose. The intelligent navigation system is developed based on an individual characteristic or a social animal biological structure. The discussion of this paper will focus on how simple agent’s structure utilizes flexible and potential outcomes in order to navigate in a productive and unorganized surrounding. The combination of the navigation system and biologically inspired approach has attracted considerable attention, which makes it an important research area in the intelligent robotic system. Overall, this paper explores the implementation, which is resulted from the simulation performed by the embodiment of robots operating in real environments.
USING THE MANDELBROT SET TO GENERATE PRIMARY POPULATIONS IN THE GENETIC ALGOR...csandit
Nowadays, finding a way to secure media is common with the growth of digital media. An
effective method for the secure transmission of images can be found in the field of visual
cryptography. There is a growing interest in the use of visual cryptography in security
application. Since this method is used for secure transmission of images, many of the methods
are developed based on the original algorithm proposed by Naor and Shamir in 1994. In this
paper, a new hybrid model is used in cryptography of images which is composed of Mandelbrot
algorithm and genetic algorithm. In the early stages of proposal, a number of encrypted images
are made by using the Mandelbrot algorithm and the original picture and in the next stage,
these encrypted images are used as the initial population for the genetic algorithm. At each
stage of the genetic algorithm, the answer of previous iterations is optimized to get the best
encoding image. Also, in the proposed method, we can achieve the decoded image by a reverse
operation from the genetic algorithm. The best encrypted image is an image with high entropy
and low correlation coefficient. According to the entropy and correlation coefficient of the
proposed method compared with existing methods, it is observed that our method gets better
results in both of them.
MUE2012-Space-aware Design Factors for Located Learning Activities Supported ...Mar Pérez-Sanagustín
presented at the 6th International Conference on Multimedia and Ubiquitous Engineering (MUE, 2012) the paper “Space-aware Design FActors for Located Learning Activities Supported with Smart Phones” a work by Patricia Santos, Mar Pérez-Sanagustín, Davinia Hernández-Leo & Josep Blat.
A Robot Collision Avoidance Method Using Kinect and Global VisionTELKOMNIKA JOURNAL
This paper introduces a robot collision avoidance method using Kinect and global vision to
improve the industrial robot’s security. Global vision is installed above the robot, and a combination of the
background-difference method and the Otsu algorithm are used. Human skeleton detection is then
introduced to detect the location information of the human body. The collided objects are classified into
nonhuman and human obstacle which is further categorized into the human head and non-head areas
such as the arm. The Kalman filter is used to predict the human gesture. The human joints danger index is
used to evaluate the risk level of the human on the basis of human body joints and robot’s motion
information. Finally, a motion control strategy is adopted in view of obstacle categories and the human joint
danger index. Results show that the proposed method can effectively improve robot’s security in real time.
Robust and Efficient Coupling of Perception to Actuation with Metric and Non-...Darius Burschka
The talk motivates a re-thinking of the way, how perception passes the information to the control modules. Metric information is not a native space of the camera and apparently also not used in biology for navigation. Early abstraction of information from images loses a lot of important information that can be directly used for following (Visual-Servoing), motion estimation(Motion Blurr), and collision relations(Optical Flow Clustering). I present in this talk ways, how we use the image information in "classical way" that does not require any learning and runs on low-power CPUs.
Deep Learning - a Path from Big Data Indexing to Robotic ApplicationsDarius Burschka
These are the slides to my ShanghAI lecture from Dec 10, 2020. It proposes necessary extensions to make DeepNets appropriate tools for robotic systems.
The talk can be found on https://fb.watch/2hXDC6K4Pq/
A novel visual tracking scheme for unstructured indoor environmentsIJECEIAES
In the ever-expanding sphere of assistive robotics, the pressing need for advanced methods capable of accurately tracking individuals within unstructured indoor settings has been magnified. This research endeavours to devise a realtime visual tracking mechanism that encapsulates high performance attributes while maintaining minimal computational requirements. Inspired by the neural processes of the human brain’s visual information handling, our innovative algorithm employs a pattern image, serving as an ephemeral memory, which facilitates the identification of motion within images. This tracking paradigm was subjected to rigorous testing on a Nao humanoid robot, demonstrating noteworthy outcomes in controlled laboratory conditions. The algorithm exhibited a remarkably low false detection rate, less than 4%, and target losses were recorded in merely 12% of instances, thus attesting to its successful operation. Moreover, the algorithm’s capacity to accurately estimate the direct distance to the target further substantiated its high efficacy. These compelling findings serve as a substantial contribution to assistive robotics. The proficient visual tracking methodology proposed herein holds the potential to markedly amplify the competencies of robots operating in dynamic, unstructured indoor settings, and set the foundation for a higher degree of complex interactive tasks.
Robot operating system based autonomous navigation platform with human robot ...TELKOMNIKA JOURNAL
In emerging technologies, indoor service robots are playing a vital role for people who are physically challenged and visually impaired. The service robots are efficient and beneficial for people to overcome the challenges faced during their regular chores. This paper proposes the implementation of autonomous navigation platforms with human-robot interaction which can be used in service robots to avoid the difficulties faced in daily activities. We used the robot operating system (ROS) framework for the implementation of algorithms used in auto navigation, speech processing and recognition, and object detection and recognition. A suitable robot model was designed and tested in the Gazebo environment to evaluate the algorithms. The confusion matrix that was created from 125 different cases points to the decent correctness of the model.
A one decade survey of autonomous mobile robot systems IJECEIAES
Recently, autonomous mobile robots have gained popularity in the modern world due to their relevance technology and application in real world situations. The global market for mobile robots will grow significantly over the next 20 years. Autonomous mobile robots are found in many fields including institutions, industry, business, hospitals, agriculture as well as private households for the purpose of improving day-to-day activities and services. The development of technology has increased in the requirements for mobile robots because of the services and tasks provided by them, like rescue and research operations, surveillance, carry heavy objects and so on. Researchers have conducted many works on the importance of robots, their uses, and problems. This article aims to analyze the control system of mobile robots and the way robots have the ability of moving in real-world to achieve their goals. It should be noted that there are several technological directions in a mobile robot industry. It must be observed and integrated so that the robot functions properly: Navigation systems, localization systems, detection systems (sensors) along with motion and kinematics and dynamics systems. All such systems should be united through a control unit; thus, the mission or work of mobile robots are conducted with reliability.
Acoustic event characterization for service robot using convolutional networksIJECEIAES
This paper presents and discusses the creation of a sound event classification model using deep learning. In the design of service robots, it is necessary to include routines that improve the response of both the robot and the human being throughout the interaction. These types of tasks are critical when the robot is taking care of children, the elderly, or people in vulnerable situations. Certain dangerous situations are difficult to identify and assess by an autonomous system, and yet, the life of the users may depend on these robots. Acoustic signals correspond to events that can be detected at a great distance, are usually present in risky situations, and can be continuously sensed without incurring privacy risks. For the creation of the model, a customized database is structured with seven categories that allow to categorize a problem, and eventually allow the robot to provide the necessary help. These audio signals are processed to produce graphical representations consistent with human acoustic identification. These images are then used to train three convolutional models identified as high-performing in this type of problem. The three models are evaluated with specific metrics to identify the best-performing model. Finally, the results of this evaluation are discussed and analyzed.
Tutorial CLEI 2010 - Assuncion - Paraguay
Outubro 2010
LRM - ICMC - USP São Carlos
INCT-SEC
Titulo: "Robôs Móveis e Veículos Autônomos: Pesquisa, Desenvolvimento e Desafios na área da Inteligência Artificial"
LEARNING OF ROBOT NAVIGATION TASKS BY PROBABILISTIC NEURAL NETWORKcscpconf
This paper reports results of artificial neural network for robot navigation tasks. Machine learning methods have proven usability in many complex problems concerning mobile robots
control. In particular we deal with the well-known strategy of navigating by “wall-following”. In this study, probabilistic neural network (PNN) structure was used for robot navigation tasks.
The PNN result was compared with the results of the Logistic Perceptron, Multilayer Perceptron, Mixture of Experts and Elman neural networks and the results of the previous
studies reported focusing on robot navigation tasks and using same dataset. It was observed the PNN is the best classification accuracy with 99,635% accuracy using same dataset.
LEARNING OF ROBOT NAVIGATION TASKS BY PROBABILISTIC NEURAL NETWORKcsandit
This paper reports results of artificial neural network for robot navigation tasks. Machine
learning methods have proven usability in many complex problems concerning mobile robots
control. In particular we deal with the well-known strategy of navigating by “wall-following”.
In this study, probabilistic neural network (PNN) structure was used for robot navigation tasks.
The PNN result was compared with the results of the Logistic Perceptron, Multilayer
Perceptron, Mixture of Experts and Elman neural networks and the results of the previous
studies reported focusing on robot navigation tasks and using same dataset. It was observed the
PNN is the best classification accuracy with 99,635% accuracy using same dataset.
Swarm robotics : Design and implementationIJECEIAES
This project presents a swarming and herding behaviour using simple robots. The main goal is to demonstrate the applicability of artificial intelligence (AI) in simple robotics that can then be scaled to industrial and consumer markets to further the ability of automation. AI can be achieved in many different ways; this paper explores the possible platforms on which to build a simple AI robots from consumer grade microcontrollers. Emphasis on simplicity is the main focus of this paper. Cheap and 8 bit microcontrollers were used as the brain of each robot in a decentralized swarm environment were each robot is autonomous but still a part of the whole. These simple robots don’t communicate directly with each other. They will utilize simple IR sensors to sense each other and simple limit switches to sense other obstacles in their environment. Their main objective is to assemble at certain location after initial start from random locations, and after converging they would move as a single unit without collisions. Using readily available microcontrollers and simple circuit design, semi-consistent swarming behaviour was achieved. These robots don’t follow a set path but will react dynamically to different scenarios, guided by their simple AI algorithm.
Visual victim detection and quadrotor-swarm coordination control in search an...IJECEIAES
We propose a distributed victim-detection algorithm through visual information on quadrotors using convolutional neuronal networks (CNN) in a search and rescue environment. Describing the navigation algorithm, which allows quadrotors to avoid collisions. Secondly, when one quadrotor detects a possible victim, it causes its closest neighbors to disconnect from the main swarm and form a new sub-swarm around the victim, which validates the victim’s status. Thus, a formation control that permits to acquire information is performed based on the well-known rendezvous consensus algorithm. Finally, images are processed using CNN identifying potential victims in the area. Given the uncertainty of the victim detection measurement among quadrotors’ cameras in the image processing, estimation consensus (EC) and max-estimation consensus (M-EC) algorithms are proposed focusing on agreeing over the victim detection estimation. We illustrate that M-EC delivers better results than EC in scenarios with poor visibility and uncertainty produced by fire and smoke. The algorithm proves that distributed fashion can obtain a more accurate result in decision-making on whether or not there is a victim, showing robustness under uncertainties and wrong measurements in comparison when a single quadrotor performs the mission. The well-functioning of the algorithm is evaluated by carrying out a simulation using V-Rep.
Sensor Based Motion Control of Mobile Car Robotijtsrd
A robot is a computer , mobile , or digital programmed virtual synthetic agent or electromechanical system that can perform tasks on its own. These frameworks stand out because of their ability to be controlled. As a result of this, a group of independent PCs appears to clients as a single controlling framework. Artificial Intelligence AI is required to construct technologies that can interact with the physical world in Robotics and Vision. AI systems such as robots can only communicate with the real world if they do their tasks accurately. The Robots efficiency is highly dependent on the applications vision techniques. As a result, the development of self driving and self contained robots relies heavily on visual techniques and procedures. A combination of temperature, gas, and fire sensors, as well as a buzzer, is used to detect areas that are more prone to explosions. In addition, a live video feed is available to keep tabs on the cars every move. Sensor based remote control of mobile robots in an unknown environment with obstacles is the focus of this paper. Prakash. P. | Mohamed Abdul Naseer R | Shajil Ameer V. V. "Sensor Based Motion Control of Mobile Car Robot" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-3 , April 2022, URL: https://www.ijtsrd.com/papers/ijtsrd49688.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/49688/sensor-based-motion-control-of-mobile-car-robot/prakash-p
In recent times, the definition of internet of things has evolved to great extent and it means different things
to different people. However the basic idea of Internet of Things remains the same which is use of information and
communication Technologies(ICT’s) as well as Internet to provide efficient services to the mankind for their
optimum benefits. While implementing the Internet of Things itself is complex due to large of devices various link
layer technologies and services that are involved in such systems. In this paper, we specifically implement an urban
Internet of Things system which primarily gives an emphasis on smart educational institute which aims at
exploiting advanced communication technologies to support for administration of the institute and for the new
visitor who find it difficult to find their way around the institute. This paper thereby provides a comprehensive
survey of various technologies such as Android , Java, protocols and architecture for using Internet of Things in
Smart Institute. Furthermore ,this system will provide an overlook of the institute via the administration office
,playground and canteens. The user of the system will also get an static image map to roam around the institute.
Lastly the system will provide technical solutions and best practice guidelines for finding the way around the
institute and also help a new visitor in reaching his desired location.
A Multi-robot System Coordination Design and Analysis on Wall Follower Robot ...IJECEIAES
In this research, multi-robot formation can be established according to the environment or workspace. Group of robots will move sequently if there is no space for robots to stand side by side. Leader robot will be on the front of all robots and follow the right wall. On the other hand, robots will move side by side if there is a large space between them. Leader robot will be tracked the wall on its right side and follow on it while every follower moves side by side. The leader robot have to broadcast the information to all robots in the group in radius 9 meters. Nevertheless, every robot should be received information from leader robot to define their movements in the area. The error provided by fuzzy output process which is caused by read data from ultrasound sensor will drive to more time process. More sampling can reduce the error but it will drive more execution time. Furthermore, coordination time will need longer time and delay. Formation will not be establisehed if packet error happened in the communication process because robot will execute wrong command.
Obstacle detection for autonomous systems using stereoscopic images and bacte...IJECEIAES
This paper presents a low cost strategy for real-time estimation of the position of ob- stacles in an unknown environment for autonomous robots. The strategy was intended for use in autonomous service robots, which navigate in unknown and dynamic indoor environments. In addition to human interaction, these environments are characterized by a design created for the human being, which is why our developments seek morphological and functional similarity equivalent to the human model. We use a pair of cameras on our robot to achieve a stereoscopic vision of the environment, and we analyze this information to determine the distance to obstacles using an algorithm that mimics bacterial behavior. The algorithm was evaluated on our robotic platform demonstrating high performance in the location of obstacles and real-time operation.
Efficient and secure real-time mobile robots cooperation using visual servoing IJECEIAES
This paper deals with the challenging problem of navigation in formation of mobiles robots fleet. For that purpose, a secure approach is used based on visual servoing to control velocities (linear and angular) of the multiple robots. To construct our system, we develop the interaction matrix which combines the moments in the image with robots velocities and we estimate the depth between each robot and the targeted object. This is done without any communication between the robots which eliminate the problem of the influence of each robot errors on the whole. For a successful visual servoing, we propose a powerful mechanism to execute safely the robots navigation, exploiting a robot accident reporting system using raspberry Pi3. This reporting system testbed is used to send an accident notification, in the form of a specifical message. Experimental results are presented using nonholonomic mobiles robots with on-board real time cameras, to show the effectiveness of the proposed method.
Social Service Robot using Gesture recognition techniqueChristo Ananth
A robot is a machine that can automatically do a task or a series of tasks based on its programming and environment. They are artificially built machines or devices that can perform activities with utmost accuracy and precision minimizing time constraints. Service robots are technologically advanced machines deployed to service and maintain certain activities. Research findings convey the essential fact that serving robots are now being deployed worldwide. Social robotics is one such field that heavily involves an interaction between humans and an artificially built machine. These man-built machines interact with humans and can also understand social terms and words. Modernization has bought changes in design and mechanisms due to this ever-lasting growth in technology and innovation. Therefore, food industries are also dynamically adapting to the new changes in the field of automation to reduce human workload and increase the quality of service. Deployment of a robot in the food industries which help to aid deaf and mute people who face social constraints is an evergrowing challenge faced by engineers for the last few decades. Moreover, a contactless form of speedy service system which accomplishes its task with at most precision and reduced complexity is a feat yet to be perfected. Preservation of personal hygiene, a better quality of service, and reduced labour costs is achieved.
Similar to Scheme for motion estimation based on adaptive fuzzy neural network (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
In this paper, snake optimization algorithm (SOA) is used to find the optimal gains of an enhanced controller for controlling congestion problem in computer networks. M-file and Simulink platform is adopted to evaluate the response of the active queue management (AQM) system, a comparison with two classical controllers is done, all tuned gains of controllers are obtained using SOA method and the fitness function chose to monitor the system performance is the integral time absolute error (ITAE). Transient analysis and robust analysis is used to show the proposed controller performance, two robustness tests are applied to the AQM system, one is done by varying the size of queue value in different period and the other test is done by changing the number of transmission control protocol (TCP) sessions with a value of ± 20% from its original value. The simulation results reflect a stable and robust behavior and best performance is appeared clearly to achieve the desired queue size without any noise or any transmission problems.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
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Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
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Scheme for motion estimation based on adaptive fuzzy neural network
1. TELKOMNIKA Telecommunication, Computing, Electronics and Control
Vol. 18, No. 2, April 2020, pp. 1030~1037
ISSN: 1693-6930, accredited First Grade by Kemenristekdikti, Decree No: 21/E/KPT/2018
DOI: 10.12928/TELKOMNIKA.v18i2.14752 1030
Journal homepage: http://journal.uad.ac.id/index.php/TELKOMNIKA
Scheme for motion estimation
based on adaptive fuzzy neural network
Fredy Martínez, Cristian Penagos, Luis Pacheco
Facultad Tecnológica, Universidad Distrital Francisco José de Caldas, Colombia
Article Info ABSTRACT
Article history:
Received Jul 13, 2019
Revised Jan 4, 2020
Accepted Feb 19, 2020
Many applications of robots in collaboration with humans require the robot to
follow the person autonomously. Depending on the tasks and their context, this
type of tracking can be a complex problem. The paper proposes and evaluates
a principle of control of autonomous robots for applications of services to
people, with the capacity of prediction and adaptation for the problem
of following people without the use of cameras (high level of privacy) and with
a low computational cost. A robot can easily have a wide set of sensors for
different variables, one of the classic sensors in a mobile robot is the distance
sensor. Some of these sensors are capable of collecting a large amount
of information sufficient to precisely define the positions of objects
(and therefore people) around the robot, providing objective and quantitative
data that can be very useful for a wide range of tasks, in particular, to perform
autonomous tasks of following people. This paper uses the estimated distance
from a person to a service robot to predict the behavior of a person, and thus
improve performance in autonomous person following tasks. For this, we use
an adaptive fuzzy neural network (AFNN) which includes a fuzzy neural
network based on Takagi-Sugeno fuzzy inference, and an adaptive learning
algorithm to update the membership functions and the rule base. The validity
of the proposal is verified both by simulation and on a real prototype.
The average RMSE of prediction over the 50 laboratory tests with different
people acting as target object was 7.33.
Keywords:
Adaptive learning algorithm
Fuzzy neural network
Motion planning
Service robot
This is an open access article under the CC BY-SA license.
Corresponding Author:
Fredy Martínez,
Facultad Tecnológica,
Universidad Distrital Francisco José de Caldas Bogotá, Colombia.
Email: fhmartinezs@udistrital.edu.co
1. INTRODUCTION
Service robotics is one of the applications of robotic systems that arouses the most interest among
the general population due to its high expectations and possibilities, but at the same time is one of the areas
with the most unsolved engineering problems [1]. Robots that interact with humans in human environments
must solve problems of path planning, image processing, interaction with the environment, fine manipulation,
communication, and in particular, direct interaction with the human being [2]. This interaction involves many
engineering problems, not only considering the safety problems for both parties during the interaction, which
is a net engineering problem [3, 4], but the interaction is conditioned by human behavior, which is quite
unpredictable. In domestic applications, for example, applications in which the robot must be attentive to
children or elderly, we expect the machine to always be close to the person under care, moving with him to
provide their services, but without interfering with his normal activity. Given the unknown nature
of the movement of people in the environment and the high complexity and dynamics of the environments,
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adaptable tracking systems are required, with the ability to learn and work in real time. A typical characteristic
of service robots is that their tasks are carried out in dynamic, unstructured and unknown environments,
generally without identifiable characteristics. The robot must be able to navigate and interact in any
environment in which people find themselves, which characterizes the physical structure of the robot
(size, type of displacement, actuators, etc.) and its needs for sensing and acting (often equivalent to human).
In addition, the processing of information and the response of the robot must be in real time. This is why these
sensors are so important for autonomous robots in general [5, 6].
Currently a crucial element in the design of this type of systems are the active robotic sensors, which
have become high performance tools capable of considerably reducing the processing requirements of the robot
control unit. These systems have gained great commercial recognition, even at the military level, thanks to
their embedded structure that, together with sensors that observe physical variables directly, process this
information in real time to extract relevant information for the robot. This kind of sensors has promoted
research in information-driven strategies for the development of tasks with robots, as well as
the implementation of algorithms for digital signal processing and control schemes oriented to these sensor [4].
As minimum requirements, the robot must be able to define its distance and size. In other cases, it is also
necessary to know its height to define interaction strategies (pick up an object from a table, for example).
Depending on the application it is possible to use different kinds of sensors, in interaction with human
environments are very important optical sensors [4, 6, 7], however, when the person has been identified, and
the goal is to make a basic tracking of him, the most important sensors are the distance sensors [8, 9, 10].
The camera-supported optical sensors in robotics have been widely used to solve the problem of
identifying and tracking people. The schemes, though far from autonomous implementation, provide high
levels of performance for both problems [11, 12]. This strategy is known as Visual Servoing or Vision-Based
Robot Control (VS) and is characterized by having as feedback information the image of a camera [13].
The goal is to support robot decision making with eyes that take optical information from its own
perspective [14]. However, the use of cameras capable of continuously recording people’s personal lives
involves serious privacy issues, and despite the guarantees of encryption and non-sharing of information, fear
prevails [15]. In addition, the visual information captured by the cameras is, in fact, excessive for the realization
of certain tasks. Distance sensors are also widely used in these applications [11], and unlike video cameras,
they have greater acceptance to work between people because they record less private information. The most
important characteristic of the following task is that it is strongly focused on the person under care. This is a
common case in service robots that provide some service to a person [16-18]. Practically speaking, this means
that the robot must be aware of the person’s behavior. Similarly, the robot will ignore other elements of
the environment unless they force the robot’s response [19, 20]. In this sense, we only study in our research
the autonomous response of the robot to the behavior of the person.
In our research, we define the task of following people, in the context of service robots, as a
high-level task that the robot performs at all times in parallel with its interaction tasks [21]. In the context of
the task, the robot does not know the person’s movement dynamics, whether the person is going to remain still,
or where it is going when walking. In this way, the robot needs to infer the person’s movement beforehand and
act accordingly. In addition, the design of the movement scheme must take into account the aforementioned
aspects of navigation, interaction, and sensing, as these are key elements in the robot’s final action. These
parameters are combined with an adaptive learning scheme and an inference machine based on fuzzy inference.
These two elements form the Fuzzy Neural Network (FNN) designed for decision making, which is supplied
by our active distance sensor [22, 23].
2. PROBLEM FORMULATION
The goal of this research is to develop a robust and high-performance software tool that allows
the development of autonomous tasks of people follow-up by a small autonomous robot. The work is strongly
motivated by the need for this feature as part of the routine interaction of an assistive robot that operates in
unknown indoor environments.
Let W ⊂ ℝ2
be the closure of a contractible open set in the plane that has a connected open interior
with obstacles that represent inaccessible regions. Let 𝓞 be a set of obstacles, in which each O ⊂ 𝓞 is closed
with a connected piecewise-analytic boundary that is finite in length. The position of obstacles in
the environment changes over time in an unknown way, but they are detectable by distance sensors. In addition,
the obstacles in 𝓞 are pairwise-disjoint and countably finite in number.
Let E ⊂ W be the free space in the environment, which is the open subset of W with the obstacles
removed. This space can be freely navigated by the robot, but it can also be occupied at any time by an obstacle.
The robot knows the environment W (and E) from observations, using sensors. These observations allow him
to build an information space I. An information mapping is of the form:
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𝑞: 𝐸 → 𝑆 (1)
where S denote an observation space, constructed from sensor readings over time, i.e., through an observation
history of the form (2).
𝑜̃: [0, 𝑡] → 𝑆 (2)
The interpretation of this information space, i.e., I ✕ S ⟶ I, is that which allows the robot to make decisions.
The problem can be expressed as the search for a function u for a specific set of conditions between a certain
obstacle and the robot, from a set of robot sensed data y ⊂ S and a target function g.
𝑓: 𝒚 × 𝒈 → 𝒖 (3)
3. METHODOLOGY
As part of the research, the research group has previously developed an active sensor that processes
distance information to define the motion of an autonomous robot in indoor environments using real-time
analysis of raw data from a group of nine infrared sensors [22]. The infra-red sensor captures distance data in
real time producing a large database that the robot analyzes according to previous experiences to directly define
distance on the horizontal plane to the object (person). Observing the dependence of data with the topology of
the environment, the active sensor uses a model based on a long short-term memory (LSTM) network to
estimate distances [24]. Thanks to this model it is possible to define coordinates on the plane of the environment
to an obstacle of interest, regardless of the characteristics of the obstacle or its position with respect to
the robot. The historical behavior of the variables is also used to differentiate the person of interest from other
elements and obstacles of the environment, however, to differentiate between different people we have used
specific marks on the person of interest.
The active sensor delivers the coordinates x and y to the obstacle under study (person to follow) with
respect to an axis defined on the geometrical center of the robot. This sensor has a real-time processing unit
that assigns values to the raw data captured by the nine infra-red sensors using models based on an LSTM
network. These data also define the heading θ and allow to determine speed and acceleration Figure 1.
Figure 1. Variables and dimensions axes on the plane with respect to the robot
The proposed system is composed of a fuzzy neural network (FNN) and an adaptive learning
algorithm Figure 2. The neural network is made up of five layers: a layer of input variables (two-dimensional
distances from the robot to the obstacle, the relative velocity between robot and obstacle, the heading angle
and acceleration), the second layer corresponds to the membership functions, the third layer is of reasoning
rules with Takagi-Sugeno type inference, the fourth layer corresponding to the fuzzy quantification of
the output variable, and the fifth layer containing the output nodes (output variable, robot heading angle).
The input vector has the following format (4):
𝑋 = [𝛥𝑥, 𝛥𝑦, 𝛥𝑣, 𝜃, 𝑎𝑐] (4)
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We define three trapezoidal fuzzy sets for each of the input variables uniformly distributed throughout
the discourse universe of each variable. This design generated a total of 243 fuzzy rules each with the following
structure (5):
𝑅𝑖: 𝐼𝐹 (∆𝑥 𝑖𝑠 𝐴𝑖) 𝑎𝑛𝑑 (∆𝑦 𝑖𝑠 𝐵𝑖) 𝑎𝑛𝑑 (∆𝑣 𝑖𝑠 𝐶𝑖)
𝑎𝑛𝑑 (𝜃 𝑖𝑠 𝐷𝑖) 𝑎𝑛𝑑 (𝑎𝑐 𝑖𝑠 𝐸𝑖)
𝑇𝐻𝐸𝑁 ℎ𝑖 𝑖𝑠 𝑓𝑖(∆𝑥, ∆𝑦, ∆𝑣, 𝜃, 𝑎𝑐)
(5)
Figure 2. Proposed prediction system architecture
A, B, C, D, and E correspond to a fuzzy set defined by its membership function, and fi corresponds to
the inference consequence for the output variable and according to the evaluated ith fuzzy rule. We use a
Takagi-Sugeno-Kang fuzzy inference in order to obtain an output membership function defined from
the input variables (a linear function defined by the input vector).
Due to the mechanical delays in the motion responses of the robot platform, we decided not to use
fuzzy sets with triangular or Gaussian shapes [25], instead, we chose trapezoidal functions that allowed
constant output behaviors for certain ranges of input variables Figure 3. The output inferred h0 is determined
as the weighted average of the outputs of each rule for the input vector X0 = [Δx0, Δy0, Δv0, θ0, ac0] (6), where
ωi is the membership degree for the ith rule.
ℎ̂0 =
∑ 𝜔𝑖 ∙ 𝑓𝑖
𝑘
𝑖=1 (∆𝑥0, ∆𝑦0, ∆𝑣0, 𝜃0, 𝑎𝑐0)
∑ 𝜔𝑖
𝑘
𝑖=1
(6)
We use a Least Squares Estimator (LSE) to perform parameter estimation by training the linear
functions. Each of these functions has the general form (7).
𝑓(𝑋) = 𝑏0 + 𝑏1 𝑋(1) + 𝑏2 𝑋(2) + 𝑏3 𝑋(3) + 𝑏4 𝑋(4) + 𝑏5 𝑋(5) (7)
To increase the performance of the prediction scheme, we use an adaptive learning algorithm to improve the
inference machine, particularly by adjusting the membership functions defined initially Figure 3 from the
behavior of the prediction error.
𝑒 = ℎ − ℎ̂ (8)
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During training each fuzzy set is replaced by a set that improves the performance of the estimator, i.e., produces
less error according to the behavior of the RMSE.
Figure 3. Initial membership functions of the five input variables
4. FINDINGS
Our robot platform consists of two robots integrated in a single system: Nao robot from SoftBank
Group, and our ARMOS TurtleBot 1 robot Figure 4. Our future objective is to develop our platform for service
applications, we have created a first mobile functional prototype, and we are experimenting with different
manipulator prototypes, but in the meantime, this integration of robots makes up our robotic solution. The Nao
robot is used for direct interaction with human beings taking advantage of their morphology, sensors, actuators
and responsiveness. The ARMOS TurtleBot 1 robot is used as a robust navigation platform in dynamic indoor
environments. The two robots share information via a router installed in the ARMOS TurtleBot 1. The ARMOS
TurtleBot 1 robot also has sufficient processing capacity for real-time execution of simple visual recognition
algorithms (DragonBoard 410c of Arrow Electronics with ARM Cortex-A53 Quad-core up to 1.2 GHz per
core and Qualcomm Adreno 306 @ 400MHz). The DragonBoard also collects the data read by the sensors
during robot-human interaction tests, processes them and produces the training database with the input and
output variables. The dataset was divided into 70% for training and 30% for testing. This division allows using
most of the dataset to create the model, ensuring that statistically, the population of datasets are marginally
different and that all possible patterns that will characterize the model are included. The 30% of unknown data
allows validation and testing of the model.
Figure 5 shows the final membership functions for the five input variables after the learning process.
With this structure the performance of the model was validated for different people identified by the robot.
Figure 6 shows the prediction results for the tracking of two different people under laboratory conditions.
In the tests people gently approach and move away from the robot after it has identified them as a target object.
The first person was a man of 1.71 m height and medium body (76 kg weight). The second person was a man
1.74 m high with a little more volume (89 kg weight). The entire training process was conducted with five
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different people. The movements in front of the robot were slow, but corresponding to the natural behavior of
a person in human interaction. The model is not trained with high-speed behaviors because they do not
correspond to the expected operation, and because the active sensor has a response speed limit.
In the figure the black line represents the real behavior data detected by the robot sensors, while the red curve
represents the behavior predicted by the model for the same instant. In blue is the tracking error in each case.
As in the two cases shown, the results show that the proposed model can closely follow the movements of
the target person. The average RMSE of prediction over the 50 laboratory tests with different people acting as
target object was 7.33.
Figure 4. Service robot (Nao robot at the top and ARMOS TurtleBot 1 at the bottom)
used in interaction and tracking tests
Figure 5. Final membership functions of the five input variables
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5. CONCLUSIONS
In this paper we propose an adaptive fuzzy neural network to predict the movements of a person, in
real time, by a service robot. This scheme is integrated with other subroutines in our robotic platform in order
to develop complex tasks in the care of children, sick and elderly people. The proposed model uses as input
variables the two-dimensional coordinates of the robot in the environment over time, as well as
the estimation of its speed, orientation and acceleration. The proposed strategy presents a high performance in
predicting the behavior of the target person thanks to the optimization of the parameters in the Takagi-Sugeno
model. In addition, the adaptive learning scheme used optimizes the design of the belonging functions and the
related fuzzy rules which improves accuracy. The size and location of the fuzzy sets was adjusted in line with
the learning process. In most cases the central set was reduced, and the central value moved from the center
of the discourse universe. Laboratory experiments performed with our robotic platform demonstrate the high
performance of the strategy, and its high reliability to predict the behavior of the person from the readings of
the active distance sensor. The average RMSE of prediction over the 50 laboratory tests with different people
acting as target object was 7.33. On the model achieved it is proposed to improve the performance reducing
the errors of prediction through the presentation of new patterns with a wider set of people that includes a
greater class of characteristics to detect by the robot.
Figure 6. Predictive results for two following cases. The red curve represents the behavior predicted by
the model, while the blue curve represents the tracking error
ACKNOWLEDGMENTS
This work was supported by the Universidad Distrital Francisco José de Caldas, in part through CIDC,
and partly by the Facultad Tecnológica. The views expressed in this paper are not necessarily endorsed by
District University. The authors thank the research group ARMOS for the evaluation carried out on prototypes
of ideas and strategies.
REFERENCES
[1] J. Wirtz, W. Kunz, T. Gruber, V. Nhat, S. Paluch, and A. Martins, “Brave new world: service robots in the frontline,”
Journal of Service Management, vol. 29, no. 5, pp. 907-931, 2018. doi: https://doi.org/10.1108/JOSM-04-2018-0119
[2] I. Stanislav, W. Craig, and K. Berezina, “Adoption of robots and service automation by tourism and hospitality
companies”. Revista Turismo & Desenvolvimento, vol. 27, no. 28, pp. 1501-1517, 2017.
[3] P. Lasota, T. Fong, and J. Shah, “A survey of methods for safe human-robot interaction,” Foundations and Trends in
Robotics, vol 5, no. 4, pp. 261-349, 2017. doi: http://dx.doi.org/10.1561/2300000052
[4] C. Freundlich, Y. Zhang, A. Zhu, P. Mordohai, and M. Zavlanos, “Controlling a robotic stereo camera under image
quantization noise,” The International Journal of Robotics Research, vol. 36, no. 12, pp. 1268-1285, June 2017.
doi: 10.1177/0278364917735163
[5] S. Solak and E. D. Bolat, "Distance estimation using stereo vision for indoor mobile robot applications," 2015 9th
International Conference on Electrical and Electronics Engineering (ELECO), Bursa, pp. 685-688, 2015.
doi: 10.1109/ELECO.2015.7394442
[6] Y. Hongshan, Z. Jiang, W. Yaonan, J. Wenyan, S. Mingui, and T. Yandong, “Obstacle classificationand 3D
measurementin unstructured environmentsbased on ToF cameras”, Sensors, vol. 14, no. 1, pp. 10753-10782, 2014.
doi: 10.3390/s140610753
8. TELKOMNIKA Telecommun Comput El Control
Scheme for motion estimation based on adaptive fuzzy neural network (Fredy Martinez)
1037
[7] Z. Yuanshen, G. Liang, H. Yixiang, and L. Chengliang, “A review of key techniques of vision-based control for
harvesting robot,” Computers and Electronics in Agriculture, ISSN 0168-1699, vol. 127, pp. 311-323, Sept 2016.
doi: 10.1016/j.compag.2016.06.022
[8] D. Fischinger, P. Einramhof, K. Papoutsakis, W. Wohlkinger, P. Mayer, P. Panek, S. Hofmann, T. Koertner, A.
Weiss, A. Argyros, and M. Vincze. “Hobbit, a care robot supporting independent living at home: First prototype and
lessons learned. Robotics and Autonomous Systems,” Robotics and Autonomuous System, vol. 75, pp. 60-78,
Jan 2016. doi: https://doi.org/10.1016/j.robot.2014.09.029
[9] Y. Wang, L. Zhijun, and S. Chun-Yi, “Rgb-d sensor-based visual slam for localization and navigation of indoor
mobile robot,” International Conference on Advanced Robotics and Mechatronics (ICARM 2016), pp. 82-87, Macau,
2016. doi: 10.1109/ICARM.2016.7606899
[10] F. Yang and X. Chenkun, “Human-tracking strategies for a six-legged rescue robot based on distance and view,”
Chinese Journal of Mechanical Engineering, ISSN 1000-9345, vol. 29, pp. 219-230, March 2016.
doi: https://doi.org/10.3901/CJME.2015.1212.146
[11] T. Linder and K. Arras. People Detection, “Tracking and Visualization Using ROS on a Mobile Service Robot,”
Robot Operating System (ROS). Springer, pp. 187-213, Feb 2016.
[12] M. Mahammed, A. Melhum, and F. Kochery, “Object distance measurement by stereo vision,” International Journal
of Science and Applied Information Technology, vol. 2, no 2, pp. 5-8, March 2013.
[13] C. Mao-Hsiung, L. Hao-Ting, and H. Chien-Lun, “Development of a stereo vision measurement system for a 3d
three-axial pneumatic parallel mechanism robot arm,” Sensors, vol. 11, no 2, pp. 2257-2281, Feb 2011.
doi: 10.3390/s110202257
[14] A. Mohamed, Y. Chenguang, and A. Cangelosi, “Stereo vision based object trackingcontrol for a movable robot
head,” 4th
IFAC International Conference onIntelligent Control and Automation Sciences, vol. 49, no. 5,
pp. 155-162, 2016.
[15] S. Glende, I. Conrad, L. Krezdorn, S. Klemcke, and C. Krätzel, “Increasing the acceptance of assistive robots for
older people through marketing strategies based on stakeholder needs,” International Journal of Social Robotics,
ISSN 1875-4791, vol. 8, no. 3, pp. 355-369, June 2016, doi: https://doi.org/10.1007/s12369-015-0328-5
[16] H. Gross, A. Scheidig, K. Debes, E. Einhorn, M. Eisenbach, S. Mueller, T. Schmiedel, T. Trinh, T. Weingefeld, A.
Bley, and C. Martin, “ROREAS: robot coach for walking and orientation training in clinical post-stroke
rehabilitation-prototype implementation and evaluation in field trials,” Autonomous Robots, vol. 41, no. 3,
pp. 679-698, March 2017. doi: https://doi.org/10.1007/s10514-016-9552-6
[17] M. Mast, M. Burmester, B. Graf, F. Weisshardt, G. Arbeiter, M. Spanel, Z. Materna, P. Smrz, and G. Kronreif,
“Design of the human-robot interaction for a semi-autonomous service robot to assist elderly people” Advanced
Technologies and Societal Change, vol. 1, no. 1, pp. 15-29, 2015. doi: https://doi.org/10.1007/978-3-319-11866-6_2
[18] K. Koide and J. Miura, “Identification of a specific person using color, height, and gait features for a
person following robot,” Robotics and Autonomous Systems, vol. 84, no. 1, pp. 76-87, Oct 2016.
doi: https://doi.org/10.1016/j.robot.2016.07.004
[19] R. Triebel, K. Arras, R. Alami, L. Beyer, S. Breuers, R. Chatila, M. Chetouani, D. Cremers, V. Evers, M. Fiore, H.
Hung, O. Islas, M. Joosse, H. Khambhaita, and T. Kucner, “Spencer: A socially aware service robot for passenger
guidance and help in busy airports,” Springer Tracts in Advanced Robotics, vol, 113, no. 1, pp. 607-622, 2016.
doi: https://doi.org/10.1007/978-3-319-27702-8_40
[20] M. Hersh, “Overcoming barriers and increasing independence - service robots for elderly and disabled people,”
International Journal of Advanced Robotic Systems, vol. 12, no. 8, pp. 1-33, 2015. doi: https://doi.org/10.5772/59230
[21] G. Ferrer, A. Garrell, F. Herrero, and A. Sanfeliu, “Robot social-aware navigation framework to accompany people
walking side-by-side,” Autonomous Robots, vol. 41, no. 4, pp. 775-793, 2017. doi: https://doi.org/10.1007/s10514-
016-9584-y
[22] F. Martínez, A. Rendón, and M. Arbulú, “A data-driven path planner for small autonomous robots using deep
regression models,” Lecture Notes in Computer Science, pp. 596-603, 2018. doi: https://doi.org/10.1007/978-3-319-
93803-5_56
[23] F. Martínez, D. Acero, and M. Castiblanco, “Robótica autónoma: Acercamiento a algunos problemas centrales,”
Universidad Distrital Francisco José de Caldas, 2015.
[24] F. Kratzert, D. Klotz, C. Brenner, K. Schulz, and M. Herrnegger, “Rainfall–runoff modelling using Long Short-
TermMemory (LSTM) networks,” Hydrology and Earth System Sciences, vol. 22, no. 11, pp. 6005-6022, Nov 2018.
doi: https://doi.org/10.5194/hess-22-6005-2018
[25] S. Azimi, and H. Miar, “Designing an analog CMOS fuzzy logic controller forthe inverted pendulum with
a novel triangular membership function,” Scientia Iranica, vol 26, no. 3, pp. 1736-1748, 2019.
doi: 10.24200/sci.2018.5224.1153