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.
Reactive Navigation of Autonomous Mobile Robot Using Neuro-Fuzzy SystemWaqas Tariq
Neuro-fuzzy systems have been used for robot navigation applications because of their ability to exert human like expertise and to utilize acquired knowledge to develop autonomous navigation strategies. In this paper, neuro-fuzzy based system is proposed for reactive navigation of a mobile robot using behavior based control. The proposed algorithm uses discrete sampling based optimal training of neural network. With a view to ascertain the efficacy of proposed system; the proposed neuro-fuzzy system’s performance is compared to that of neural and fuzzy based approaches. Simulation results along with detailed behavior analysis show effectiveness of our algorithm in all kind of obstacle environments.
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.
Autonomous Path Planning and Navigation of a Mobile Robot with Multi-Sensors ...CSCJournals
The mobile robot is applied widely and investigated deeply in industrial fields, meanwhile, mobile robot autonomous path planning and navigation algorithm is a hot research topic. In this paper, firstly mobile robot is introduced, the general path planning and navigation algorithms of the mobile robot are reviewed, then a fuzzy logic with filter smoothing is proposed based on the data from the laser scan sensor and GPS module, which is useful for mobile robot to find the best path to the destination automatically according to the position and size of the gaps between the obstacles in the dynamic environment, finally our designed mobile robot and corresponding Android APP are introduced, the path planning and navigation algorithms are tested on this mobile robot, the testing result shows that this algorithm is globally optimized, quickly responded, battery power and hardware cost saved compared with other algorithms, it is suitable for the mobile robot that is running on the embedded system and it can satisfy our design requirement.
Develop a mobility model for MANETs networks based on fuzzy Logiciosrjce
The study and research in the field of networks MANETs depends alleged understand the protocols
well of the simulation process before they are applied in the real world, so that we create an environment
similar to these networks. The problem of a set of nodes connected with each other wirelessly, this requires the
development of a comprehensive model and full and real emulator for the movement of the contract on behalf of
stochastic models. Many models came to address the problems of random models that restricted the movement
of decade barriers as well as the signals exchanged between them, but these models were not receiving a lot of
light on the movement of the contract, such as direction, speed and path that is going by the node. The main
goal is to get a comprehensive model and simulator for all parts of the environment of the barriers and
obstacles to the movement of the nodes and the mobile signal between them as well as to focus on the movement
transactions for the node of the direction, speed, and best way. . This research aims to provide a realistic
mobility model for MANET networks. It also addresses the problem of imprecision in social relationships and
the location where we apply Fuzzy logic.
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON TH...Wireilla
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is
the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of
the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted
based on the robot's distance from obstacles, and the target position relative to the instantaneous
orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also,
Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy
systems are determined based on the estimation of the localization process, the information of the obstacles
center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile
robot are determined by the desired fuzzy structures which are applied to its kinematic model.
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON TH...ijfls
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted based on the robot's distance from obstacles, and the target position relative to the instantaneous orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also, Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy systems are determined based on the estimation of the localization process, the information of the obstacles center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile robot are determined by the desired fuzzy structures which are applied to its kinematic model.
Wall follower autonomous robot development applying fuzzy incremental controllerrajabco
This paper presents the design of an autonomous robot as a basic development of an intelligent wheeled mobile robot for air duct or corridor cleaning. The robot navigation is based on wall following algorithm. The robot is controlled us- ing fuzzy incremental controller (FIC) and embedded in PIC18F4550 microcontroller. FIC guides the robot to move along a wall in a desired direction by maintaining a constant distance to the wall. Two ultrasonic sensors are installed in the left side of the robot to sense the wall distance. The signals from these sensors are fed to FIC that then used to de- termine the speed control of two DC motors. The robot movement is obtained through differentiating the speed of these two motors. The experimental results show that FIC is successfully controlling the robot to follow the wall as a guid- ance line and has good performance compare with PID controller.
Reactive Navigation of Autonomous Mobile Robot Using Neuro-Fuzzy SystemWaqas Tariq
Neuro-fuzzy systems have been used for robot navigation applications because of their ability to exert human like expertise and to utilize acquired knowledge to develop autonomous navigation strategies. In this paper, neuro-fuzzy based system is proposed for reactive navigation of a mobile robot using behavior based control. The proposed algorithm uses discrete sampling based optimal training of neural network. With a view to ascertain the efficacy of proposed system; the proposed neuro-fuzzy system’s performance is compared to that of neural and fuzzy based approaches. Simulation results along with detailed behavior analysis show effectiveness of our algorithm in all kind of obstacle environments.
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.
Autonomous Path Planning and Navigation of a Mobile Robot with Multi-Sensors ...CSCJournals
The mobile robot is applied widely and investigated deeply in industrial fields, meanwhile, mobile robot autonomous path planning and navigation algorithm is a hot research topic. In this paper, firstly mobile robot is introduced, the general path planning and navigation algorithms of the mobile robot are reviewed, then a fuzzy logic with filter smoothing is proposed based on the data from the laser scan sensor and GPS module, which is useful for mobile robot to find the best path to the destination automatically according to the position and size of the gaps between the obstacles in the dynamic environment, finally our designed mobile robot and corresponding Android APP are introduced, the path planning and navigation algorithms are tested on this mobile robot, the testing result shows that this algorithm is globally optimized, quickly responded, battery power and hardware cost saved compared with other algorithms, it is suitable for the mobile robot that is running on the embedded system and it can satisfy our design requirement.
Develop a mobility model for MANETs networks based on fuzzy Logiciosrjce
The study and research in the field of networks MANETs depends alleged understand the protocols
well of the simulation process before they are applied in the real world, so that we create an environment
similar to these networks. The problem of a set of nodes connected with each other wirelessly, this requires the
development of a comprehensive model and full and real emulator for the movement of the contract on behalf of
stochastic models. Many models came to address the problems of random models that restricted the movement
of decade barriers as well as the signals exchanged between them, but these models were not receiving a lot of
light on the movement of the contract, such as direction, speed and path that is going by the node. The main
goal is to get a comprehensive model and simulator for all parts of the environment of the barriers and
obstacles to the movement of the nodes and the mobile signal between them as well as to focus on the movement
transactions for the node of the direction, speed, and best way. . This research aims to provide a realistic
mobility model for MANET networks. It also addresses the problem of imprecision in social relationships and
the location where we apply Fuzzy logic.
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON TH...Wireilla
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is
the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of
the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted
based on the robot's distance from obstacles, and the target position relative to the instantaneous
orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also,
Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy
systems are determined based on the estimation of the localization process, the information of the obstacles
center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile
robot are determined by the desired fuzzy structures which are applied to its kinematic model.
EFFECTIVE REDIRECTING OF THE MOBILE ROBOT IN A MESSED ENVIRONMENT BASED ON TH...ijfls
The use of fuzzy logic in redirecting mobile robot is based on two sets of received information. First set is the instantaneous distance of the robot from the obstacle and second set is the instantaneous information of the robot's position. For this purpose, the fuzzy rules base consists of forty-two bases, which is extracted based on the robot's distance from obstacles, and the target position relative to the instantaneous orientation of the robot. In the structure of fuzzy systems, minimal inference engine are considered. Also, Extended Kalman filter is used for localization in a noisy environment. Accordingly, the inputs of the fuzzy systems are determined based on the estimation of the localization process, the information of the obstacles center and the target position. Also, the linear acceleration and instantaneous orientation of the mobile robot are determined by the desired fuzzy structures which are applied to its kinematic model.
Wall follower autonomous robot development applying fuzzy incremental controllerrajabco
This paper presents the design of an autonomous robot as a basic development of an intelligent wheeled mobile robot for air duct or corridor cleaning. The robot navigation is based on wall following algorithm. The robot is controlled us- ing fuzzy incremental controller (FIC) and embedded in PIC18F4550 microcontroller. FIC guides the robot to move along a wall in a desired direction by maintaining a constant distance to the wall. Two ultrasonic sensors are installed in the left side of the robot to sense the wall distance. The signals from these sensors are fed to FIC that then used to de- termine the speed control of two DC motors. The robot movement is obtained through differentiating the speed of these two motors. The experimental results show that FIC is successfully controlling the robot to follow the wall as a guid- ance line and has good performance compare with PID controller.
Optimally Learnt, Neural Network Based Autonomous Mobile Robot Navigation SystemIDES Editor
Neural network based systems have been used in
past years for robot navigation applications because of their
ability to learn human expertise and to utilize this knowledge
to develop autonomous navigation strategies. In this paper,
neural based systems are developed for mobile robot reactive
navigation. The proposed systems transform sensors’ input to
yield wheel velocities. Novel algorithm is proposed for optimal
training of neural network. With a view to ascertain the efficacy
of proposed system; developed neural system’s performance
is compared to other neural and fuzzy based approaches.
Simulation results show effectiveness of proposed system in
all kind of obstacle environments.
Mobility models for delay tolerant network a surveyijwmn
Delay Tolerant Network (DTN) is an emerging networking technology that is widely used in the
environment where end-to-end paths do not exist. DTN follows store-carry-forward mechanism to route
data. This mechanism exploits the mobility of nodes and hence the performances of DTN routing and
application protocols are highly dependent on the underlying mobility of nodes and its characteristics.
Therefore, suitable mobility models are required to be incorporated in the simulation tools to evaluate DTN
protocols across many scenarios. In DTN mobility modelling literature, a number of mobility models have
been developed based on synthetic theory and real world mobility traces. Furthermore, many researchers
have developed specific application oriented mobility models. All these models do not provide accurate
evaluation in the all scenarios. Therefore, model selection is an important issue in DTN protocol
simulation. In this study, we have summarized various widely used mobility models and made a comparison
of their performances. Finally, we have concluded with future research directions in mobility modelling for
DTN simulation.
In our World of today, the quest to get rich at all cost without working for our money has led some of our youth into crimes such as robbery and kidnapping. As a result of this and by the sheer fact that vehicles are now very expensive to buy these days, there is a need for people to safeguard their vehicles against these hoodlums to avoid loss of their precious Assets to these rampaging criminals. Tracking is technology that is used by many companies and individuals to track a vehicle, an individual or an asset by using many ways like GPS that operates using satellites and ground-based stations or by using our approach which depends on the cellular mobile towers. Vehicle tracking system is a system that can be used in monitoring and locating a vehicle, avoid theft or recover a stolen vehicle, for monitoring of vehicle routes to ensure strict compliance to an already defined vehicle routes, monitor driver’s behavior, predict bus arrival as well as for fleet management. Internet of things has made it very possible to devices to inter communicate amongst themselves and exchange information, helping in acquiring and analyzing information faster that we used to know in the past and this has helped more especially in vehicle monitoring to ensure that vehicle owners feel safe about their investments without fearing about their loss. In this paper, we propose a vehicle monitoring system based on IOT technology, using 4G/LTE to get the get the coordinate, speed, and overall condition of the vehicle, process and send to a remote server to be analyzed and used in locating the vehicle and monitor its other configured parameters. This is realized using Raspberry pi, 4G/LTE, GPS, Accelerometer and other sensors with communicate amongst themselves to get the environmental parameters which is processed and sent to a remote server where it is analyzed and represented on a map to locate the vehicle and monitor the other set parameters. 4G/LTE provides fast internet connectivity with overcomes the usual delay usually experienced in sending the acquired signals to be processed. The True Vehicle position is represented using google geolocation service and the actual position triangulated in real-time.
Introduction to the Special issue on ‘‘Future trends in robotics and autonomo...Anand Bhojan
Robotics is an extremely dynamic field with thriving advancement in its technology. As research progresses in robotic systems, more and more aspects of vision based processing, GPS enabled services, Autonomous techniques, very far distance communication in robots, dynamic environment handling, mobility techniques, multi-agent control and coordination techniques, multi-robot communication and coordination are explored to make robotics intelligent and to do specific tasks. Vision has helped in many areas for better services and fastens the process for localized results. Advancements in communication, positioning and localization techniques brought the robotics beyond the controlled industrial environments to more dynamic outdoor environments. Research in autonomous and other intelligent techniques has made robots capable of taking decisions in complex environments. The book covers future trends in robotics research topics including motion path planning, routing in dynamic environments, multi-agent control techniques, nature inspired algorithms and synchronization techniques with interesting applications.
A robot may need to use a tool to solve a complex problem. Currently, tool use must be pre-programmed by a human. However, this is a difficult task and can be helped if the robot is able to learn how to use a tool by itself. Most of the work in tool use learning by a robot is done using a feature-based representation. Despite many successful results, this representation is limited in the types of tools and tasks that can be handled. Furthermore, the complex relationship between a tool and other world objects cannot be captured easily. Relational learning methods have been proposed to overcome these weaknesses [1, 2]. However, they have only been evaluated in a sensor-less simulation to avoid the complexities and uncertainties of the real world. We present a real world implementation of a relational tool use learning system for a robot. In our experiment, a robot requires around ten examples to learn to use a hook-like tool to pull a cube from a narrow tube.
Neural Network based Vehicle Classification for Intelligent Traffic Controlijseajournal
Nowadays, number of vehicles has been increased and traditional systems of traffic controlling couldn’t be
able to meet the needs that cause to emergence of Intelligent Traffic Controlling Systems. They improve
controlling and urban management and increase confidence index in roads and highways. The goal of this
article is vehicles classification base on neural networks. In this research, it has been used a immovable
camera which is located in nearly close height of the road surface to detect and classify the vehicles. The
algorithm that used is included two general phases; at first, we are obtaining mobile vehicles in the traffic
situations by using some techniques included image processing and remove background of the images and
performing edge detection and morphology operations. In the second phase, vehicles near the camera are
selected and the specific features are processed and extracted. These features apply to the neural networks
as a vector so the outputs determine type of vehicle. This presented model is able to classify the vehicles in
three classes; heavy vehicles, light vehicles and motorcycles. Results demonstrate accuracy of the
algorithm and its highly functional level.
Advancement in VANET Routing by Optimize the Centrality with ANT Colony Approachijceronline
In a wireless ad hoc network, an opportunistic routing strategy is a strategy where there is no predefined rule for choosing the next node to destination (as it is the case in conventional schemes such as OLSR, DSR or even Geo-Routing). A popular example of opportunistic routing is the “delay tolerant” forwarding to VANET network when a direct path to destination does not exist. Conventional routing in this case would just “drop” the packet. With opportunistic routing, a node acts upon the available information, In this thesis optimize the routing by centrality information then refine by ant colony metaheuristics. In this method validate our approach on different parameter like overhead, throughput.
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.
Synchronous mobile robots formation control is one of the most challenging and interesting fields
in robotics. The mobile robots communicate with each other through wireless communication to perform
similar movement. This study analyzed two mobile robots that can perform synchronous movement along
a shaped path. A square shape is set as a path for the mobile robot movements. The front robot being the
leading robot transmits the instruction of its movement to the robot b ehind it, acting as the following robot
through a wireless communication. The instruction sent by the leading robot is received by the following
robot through a program embedded in the leading robot microcontroller which then drives the following
robot to move and imitates the movement of the leading. The algorithm for the movement is tested on the
hardware and the results of the experiment are included to verify the effectiveness of the proposed
method.
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.
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.
With the development of robotics and artificial intelligence field unceasingly thorough, path planning for avoid
obstacles as an important field of robot calculation has been widespread concern. This paper analyzes the
current development of robot and path planning algorithm for path planning to avoid obstacles in practice. We
tried to find a good way in mobile robot path planning by using ant colony algorithm, and it also provides some
solving methods.
Optimally Learnt, Neural Network Based Autonomous Mobile Robot Navigation SystemIDES Editor
Neural network based systems have been used in
past years for robot navigation applications because of their
ability to learn human expertise and to utilize this knowledge
to develop autonomous navigation strategies. In this paper,
neural based systems are developed for mobile robot reactive
navigation. The proposed systems transform sensors’ input to
yield wheel velocities. Novel algorithm is proposed for optimal
training of neural network. With a view to ascertain the efficacy
of proposed system; developed neural system’s performance
is compared to other neural and fuzzy based approaches.
Simulation results show effectiveness of proposed system in
all kind of obstacle environments.
Mobility models for delay tolerant network a surveyijwmn
Delay Tolerant Network (DTN) is an emerging networking technology that is widely used in the
environment where end-to-end paths do not exist. DTN follows store-carry-forward mechanism to route
data. This mechanism exploits the mobility of nodes and hence the performances of DTN routing and
application protocols are highly dependent on the underlying mobility of nodes and its characteristics.
Therefore, suitable mobility models are required to be incorporated in the simulation tools to evaluate DTN
protocols across many scenarios. In DTN mobility modelling literature, a number of mobility models have
been developed based on synthetic theory and real world mobility traces. Furthermore, many researchers
have developed specific application oriented mobility models. All these models do not provide accurate
evaluation in the all scenarios. Therefore, model selection is an important issue in DTN protocol
simulation. In this study, we have summarized various widely used mobility models and made a comparison
of their performances. Finally, we have concluded with future research directions in mobility modelling for
DTN simulation.
In our World of today, the quest to get rich at all cost without working for our money has led some of our youth into crimes such as robbery and kidnapping. As a result of this and by the sheer fact that vehicles are now very expensive to buy these days, there is a need for people to safeguard their vehicles against these hoodlums to avoid loss of their precious Assets to these rampaging criminals. Tracking is technology that is used by many companies and individuals to track a vehicle, an individual or an asset by using many ways like GPS that operates using satellites and ground-based stations or by using our approach which depends on the cellular mobile towers. Vehicle tracking system is a system that can be used in monitoring and locating a vehicle, avoid theft or recover a stolen vehicle, for monitoring of vehicle routes to ensure strict compliance to an already defined vehicle routes, monitor driver’s behavior, predict bus arrival as well as for fleet management. Internet of things has made it very possible to devices to inter communicate amongst themselves and exchange information, helping in acquiring and analyzing information faster that we used to know in the past and this has helped more especially in vehicle monitoring to ensure that vehicle owners feel safe about their investments without fearing about their loss. In this paper, we propose a vehicle monitoring system based on IOT technology, using 4G/LTE to get the get the coordinate, speed, and overall condition of the vehicle, process and send to a remote server to be analyzed and used in locating the vehicle and monitor its other configured parameters. This is realized using Raspberry pi, 4G/LTE, GPS, Accelerometer and other sensors with communicate amongst themselves to get the environmental parameters which is processed and sent to a remote server where it is analyzed and represented on a map to locate the vehicle and monitor the other set parameters. 4G/LTE provides fast internet connectivity with overcomes the usual delay usually experienced in sending the acquired signals to be processed. The True Vehicle position is represented using google geolocation service and the actual position triangulated in real-time.
Introduction to the Special issue on ‘‘Future trends in robotics and autonomo...Anand Bhojan
Robotics is an extremely dynamic field with thriving advancement in its technology. As research progresses in robotic systems, more and more aspects of vision based processing, GPS enabled services, Autonomous techniques, very far distance communication in robots, dynamic environment handling, mobility techniques, multi-agent control and coordination techniques, multi-robot communication and coordination are explored to make robotics intelligent and to do specific tasks. Vision has helped in many areas for better services and fastens the process for localized results. Advancements in communication, positioning and localization techniques brought the robotics beyond the controlled industrial environments to more dynamic outdoor environments. Research in autonomous and other intelligent techniques has made robots capable of taking decisions in complex environments. The book covers future trends in robotics research topics including motion path planning, routing in dynamic environments, multi-agent control techniques, nature inspired algorithms and synchronization techniques with interesting applications.
A robot may need to use a tool to solve a complex problem. Currently, tool use must be pre-programmed by a human. However, this is a difficult task and can be helped if the robot is able to learn how to use a tool by itself. Most of the work in tool use learning by a robot is done using a feature-based representation. Despite many successful results, this representation is limited in the types of tools and tasks that can be handled. Furthermore, the complex relationship between a tool and other world objects cannot be captured easily. Relational learning methods have been proposed to overcome these weaknesses [1, 2]. However, they have only been evaluated in a sensor-less simulation to avoid the complexities and uncertainties of the real world. We present a real world implementation of a relational tool use learning system for a robot. In our experiment, a robot requires around ten examples to learn to use a hook-like tool to pull a cube from a narrow tube.
Neural Network based Vehicle Classification for Intelligent Traffic Controlijseajournal
Nowadays, number of vehicles has been increased and traditional systems of traffic controlling couldn’t be
able to meet the needs that cause to emergence of Intelligent Traffic Controlling Systems. They improve
controlling and urban management and increase confidence index in roads and highways. The goal of this
article is vehicles classification base on neural networks. In this research, it has been used a immovable
camera which is located in nearly close height of the road surface to detect and classify the vehicles. The
algorithm that used is included two general phases; at first, we are obtaining mobile vehicles in the traffic
situations by using some techniques included image processing and remove background of the images and
performing edge detection and morphology operations. In the second phase, vehicles near the camera are
selected and the specific features are processed and extracted. These features apply to the neural networks
as a vector so the outputs determine type of vehicle. This presented model is able to classify the vehicles in
three classes; heavy vehicles, light vehicles and motorcycles. Results demonstrate accuracy of the
algorithm and its highly functional level.
Advancement in VANET Routing by Optimize the Centrality with ANT Colony Approachijceronline
In a wireless ad hoc network, an opportunistic routing strategy is a strategy where there is no predefined rule for choosing the next node to destination (as it is the case in conventional schemes such as OLSR, DSR or even Geo-Routing). A popular example of opportunistic routing is the “delay tolerant” forwarding to VANET network when a direct path to destination does not exist. Conventional routing in this case would just “drop” the packet. With opportunistic routing, a node acts upon the available information, In this thesis optimize the routing by centrality information then refine by ant colony metaheuristics. In this method validate our approach on different parameter like overhead, throughput.
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.
Synchronous mobile robots formation control is one of the most challenging and interesting fields
in robotics. The mobile robots communicate with each other through wireless communication to perform
similar movement. This study analyzed two mobile robots that can perform synchronous movement along
a shaped path. A square shape is set as a path for the mobile robot movements. The front robot being the
leading robot transmits the instruction of its movement to the robot b ehind it, acting as the following robot
through a wireless communication. The instruction sent by the leading robot is received by the following
robot through a program embedded in the leading robot microcontroller which then drives the following
robot to move and imitates the movement of the leading. The algorithm for the movement is tested on the
hardware and the results of the experiment are included to verify the effectiveness of the proposed
method.
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.
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.
With the development of robotics and artificial intelligence field unceasingly thorough, path planning for avoid
obstacles as an important field of robot calculation has been widespread concern. This paper analyzes the
current development of robot and path planning algorithm for path planning to avoid obstacles in practice. We
tried to find a good way in mobile robot path planning by using ant colony algorithm, and it also provides some
solving methods.
Scheme for motion estimation based on adaptive fuzzy neural networkTELKOMNIKA JOURNAL
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.
This paper presents the design of an autonomous robot as a basic development of an intelligent wheeled mobile robot for air duct or corridor cleaning. The robot navigation is based on wall following algorithm. The robot is controlled us- ing fuzzy incremental controller (FIC) and embedded in PIC18F4550 microcontroller. FIC guides the robot to move along a wall in a desired direction by maintaining a constant distance to the wall. Two ultrasonic sensors are installed in the left side of the robot to sense the wall distance. The signals from these sensors are fed to FIC that then used to determine the speed control of two DC motors. The robot movement is obtained through differentiating the speed of these two motors. The experimental results show that FIC is successfully controlling the robot to follow the wall as a guidance line and has good performance compare with PID controller.
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.
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.
RESEARCH ON THE MOBILE ROBOTS INTELLIGENT PATH PLANNING BASED ON ANT COLONY A...cscpconf
With the development of robotics and artificial intelligence field unceasingly thorough, path
planning as an important field of robot calculation has been widespread concern. This paper
analyzes the current development of robot and path planning algorithm and focuses on the
advantages and disadvantages of the traditional intelligent path planning as well as the path
planning. The problem of mobile robot path planning is studied by using ant colony algorithm, and
it also provides some solving methods.
Research on the mobile robots intelligent path planning based on ant colony a...csandit
With the development of robotics and artificial intelligence field unceasingly thorough, path
planning as an important field of robot calculation has been widespread concern. This paper
analyzes the current development of robot and path planning algorithm and focuses on the
advantages and disadvantages of the traditional intelligent path planning as well as the path
planning. The problem of mobile robot path planning is studied by using ant colony algorithm, and
it also provides some solving methods.
High-Speed Neural Network Controller for Autonomous Robot Navigation using FPGAiosrjce
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
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.
Overview of different techniques utilized in designing of a legged robotNikhil Koli
This paper focuses on the various techniques which are implemented to design a small scale legged robot. It specifies various parameters which play a vital role for designing of robot. It also provides the basic level analysis method which can be used to deal with calculation of force, generation of foot profile, calculating dimension of linkages and different method to help the robot to
navigate across rough terrains using sensors and various other algorithm or programs, which instantly optimises the foot profile of the robot to overcome any obstacle
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
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.
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.
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.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
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information. Furthermore, a group of autonomous robots has to avoid collision from each other by defining
each path based on shared data [1]. It is different to some others research which only applied a single robot,
especially in defining a path. For example, in Tatiya Padang Tunggal et al. they only applied fuzzy cell-
decomposition to define a path in a single robot [2].
Multi-robot system must be designed to have ability in collecting and integrating data from robots
wether it’s uniform or not [3]. We can explore from ants which live in colony. They have a kind of system
when they travel, an ant will leave ammonia to ease other ants follow the path [4]. Based on that movement,
ant colony mostly similar to leader-follower mechanism in multi-robot. It’s important of a group robot to
have a leader to ease tha data acquisition system and solve the jobs [5].
Research in Multi-Robot, mostly develops control system based on computer process [6]. Besides,
there are some kind of multi-robot autonomous control system, which robot will ove autonomos after
activated without any other commands [7]. Moreover,distributed control system is one of popular research
area related to multi-robot controlling. One of them was focused on collision avoidance between robots when
trying to accomplish the given mission [8]. In advance, robot can avoid collision without stopping their
movement [9].
On the other hand, there were multi-robot agorithm evaluated to assemble robots in a similar
location [10], [11]. It can evaluate leader-follower algorithm context and also one kind of test to define the
reability of the mechanism. Another mechanism of that, follower robot will move by following the leader
track [12]. Then, it were developed by applying distribution control and information sharing so that follower
robot can move more precisely to adjust the speed, path, and orientation [13].
Network connectivity is also one of important part in multi-robot. It should be reliable in multi-robot
to avoid information missundertanding between robots because robots will always communicate during
operation.There were two kind of communication, decentralized and centralized method. In decentralize or
distributed method, connectivity can handlelarge amount of robots [14]. While in centralized method, it has
to be define a robot as a leader which will handle data from all of robots. In network, it also similar as a
router. Every single robot will move based on data come from leader [15], [16]. It is effective and efficient
for small amount of robots.
In this research, we will apply a small group of robots consist of four which one robot will be
defined as a leader. It will be an evaluation to determine the reability of multi-robot mechanism which mainly
purposed to maintain the formation of robots with simplest possible algorithm. It means that the computation
expected is as mild as possible. In our previous research, it is proved that designed algorithm can run
properly in arduino based controller where follower robot can move through leader track [17]. We applied
less complexity than either swarm system or localization methods presented in [18] and [19] in order to make
a quick respond system in only a simple robots.
In this paper, it will be presented the designed mechanism of communication and how the robots
make a proper coordination between them. This paper will be arranged as follows: in section 1, it is already
presented an introduction of the research and related works of that; while the system and method will be put
on the section 2; in section 3, testing scenarios, results, and evaluation of the system are given; as a last
section, in section 4 will be presented a conclusion and the description of our future works related to current
publication.
2. SYSTEM DESIGN
Generally, system consists of four uniform robots which can communicate each other for
coordination. Each robot has embedded processor as main controller, two dc-motors for actuator, and sensor
system for localization input in defining position such as ultrasound and compass sensor. Besides, for
communication each of them has an RF based tranceiver-receiver which works on frequency channel 433
MHz. From them, a robot has a role as leader while others will be follower. Each Robot Hardware Block
System as shown in Figure 1.
Figure 1. Each robot hardware block system
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Ultrasound sensors are needed to defined the position on a maze base on range between robot and
front-side walls. While compass sensor will determine the robot orientation. Besides, ultrasond can help
robot to move arround and avoid collision wether with or without data from other robot. After each robot
defines its position and orientation, they will send that information to leader robot in order to be processed.
Leader robot will compare every received information with its own to determine the next step for each robot
movement. The communication scheme used in this research was a broadcast or mesh network so that every
robot can communicate directly to others even the decision will be made by leader only. It helped widening
the range because it was defined that every follower robot will always resend data come from other follower
till it received by leader. Used Communication Network Scheme of Multi-Robot as shown in Figure 2.
Figure 2. Used Communication Network Scheme of Multi-Robot
For communication and navigation sharing necessity, there were created come precedure and data
format to be sent by robots to group. Since there are two kind of formations desired, procedure created also
have differences between them.
2.1. Paralel Robot Formation
In paralel formation, follower robots will move forward by following leader’s track behind. Paralel
formation is equal to sequential formation where robots move in a straight line. This formation is very useful
when robots find a narrow lane. There were some procedures to define the paralel formation as follows:
1. At first, robot move by using wall following algorithm which following a right wall based on efined
range (3cm from the wall).
2. If leader robot find an obstacle in front of it, it will send EIM data to others. Then, it will turn left and
move forward until data B is received.
3. Follower robot at the second position will stop when it receive an EIM data for a moment (delay set),
and move again by wall following on the right wall.
4. The second robot will send IM data to robots behind it when find an obstacle in the front (obstacle can
be a leader also) and make a turn to left the follow the right wall.
5. If the third robot find an obstacle, others will be stopped. It will send data AEM to fourth robot. Other
behaviour is equal to leader n second robot.
6. For the last robot, it will send AEI data if it find an obstacle and the make a left turn and send BFJ data
to all robots. The next procedures are back to the first.
To determine movement steps of multi-robot above, data format which known by each robot have to
be designed. To ease the procedures, data format created as simple as possible so that it only uses a string or
character to define commands. However, commands are defined by sensor input condition based on
environment. As described before, sensor used consist of ultrasound to define an obstacle and range to the
wall, and compass use to find robot orientation. On the Table 1, shown messages creted to be sent from one
to other robots.
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Table 1. Communication and Navigation Procedure of Multi-Robot Paralel Formation
ROBOT 1 ROBOT 2 ROBOT 3 ROBOT 4
MOVEMENT DATA MOVEMENT DATA MOVEMENT DATA MOVEMENT DATA
RWF RWF RWF RWF
AP4 FUZZY
STOP
SEND EIM RECEIVE EIM RECEIVE EIM RECEIVE EIM
TURN LEFT STOP STOP STOP
DELAY DELAY DELAY
FORWARD RWF RWF RWF
STOP AP4 FUZZY
ROBOT 1 STOP UNTIL
RECEIVE DATA ‘B’
STOP
SEND IM RECEIVE IM RECEIVE IM
TURN LEFT STOP STOP
DELAY DELAY
FORWARD RWF RWF
RECEIVE B SEND B AP4 FUZZY
RWF RWF STOP
RECEIVE AEM RECEIVE AEM SEND AEM RECEIVE AEM
STOP STOP TURN LEFT STOP
ROBOT 1 DAN 2 STOP UNTIL RECEIVE DATA ‘BF’ DELAY
FORWARD RWF
RECEIVE BF RECEIVE BF SEND BF AP4 FUZZY
RWF RWF RWF STOP
RECEIVE AEI RECEIVE AEI RECEIVE AEI SEND AEI
STOP STOP STOP TURN LEFT
ROBOT 1, 2, DAN 3 STOP HINGGA MENERIMA DATA ‘BFJ’ FORWARD
RECEIVE BFJ RECEIVE BFJ RECEIVE BFJ SEND BFJ
RWF RWF RWF RWF
2.2. Serial Robot Formation
When robots detect and define larger area which is fit to put robots together in a row, then Multi-
Robot system will be entered the serial formation mode. In this mode, robots will move forward together in a
same row and in equal speed. The difficult problem is when robots find obstacle or wall in front of them, so
that they have to make a turn. But, it will be defined by the leader where the postion is nearest to the right
wall. Procedures is determined as follows:
1. When leader robot detects an obstacle or wall on the front, it will stop move at a moment and check the
left side. If the distance is more than 10cm to the second robot, it will send the GIM data to command
the second robot to stop. Besides, it will also send EKM data to stop the other follower robot.
2. Soon after the second robot stops, it will also check the left side and repeat the procedure used by leader
robot. Stop command is defined as IO data.
3. Meanwhile, robot 3 will also check its left side and send M data to robot 4.
Data flow from procedure above also can be shown by table 2 below. Meanwhile, Figure 3 shows
the flow process and communication between leader and follower robots.
Table 2. Communication and Navigation Procedure of Multi-Robot Serial Formation
ROBOT 1 ROBOT 2 ROBOT 3 ROBOT 4
MOVEMENT DATA GERKAN DATA MOVEMENT DATA MOVEMENT DATA
RWF RWF RWF RWF
AP4 FUZZY
STOP
SEND GIM RECEIVE GIM RECEIVE GIM RECEIVE GIM
STOP RWF STOP STOP
LEFT SENSOR
CHECK < 10 ?
SEND EKM RECEIVE EKM RECEIVE EKM RECEIVE EKM
STOP STOP RWF STOP
CEK SENSOR
KIRI < 10 ?
SEND IO RECEIVE IO RECEIVE IO
STOP STOP RWF
CEK SENSOR
KIRI < 10 ?
SEND M RECEIVE M
STOP STOP
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Start
Range Sensor
Detection
(Front + Right)
Front Object?
Fuzzy Control
Process
Move Forward
(Right Wall
Following)
Information
Sent to
Other
Robots
Start
Any Info
Received?
Turn Left (90deg)
Move Forward
(Right Wall
Following)
Front Object?
Information
Sent to
Leader
Any Replies?
Fuzzy Control
Process
Range Sensor
Detection
(Front + Right)
End
End
(a) (b)
Figure 3. Flow Chart of Formation Scheme (a) Leader Robot, (b) Follower Robot
2.3. Movement Robot Control
Generally, robot moves by grabbing on the right wall or commonly known as right wall following
method. It is a kind of simplest method to move and commonly used by blind mobile robot which only
depend on range sensor. To define the decision to move, fuzzy logic scheme is designed using two input by
using range sensor. It can be shown on the Figure 4 below.
Figure 4. Fuzzy Logic Design (16)
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Ffar(x) = {
1 , x ≥ 18
𝑥−8
18−8
, 8 < 𝑥 < 18
0 , x ≤ 8
(1)
Fnear(x) = {
1 , x ≤ 8
18−𝑥
18−8
, 8 < 𝑥 < 18
0 , x ≥ 18
(2)
Formulations above is defined for front sensor. It is used to make a decision to move or stop. On the
other hand, the right sensor is used for defining the speed of motors and make a robot moving by grabbing
the right wall. Furthermore, in the follower robot, it can be used for detecting the other robot on their right
side. All values are defined as a range in centimeters.
Rfar(x) = {
1 , x ≥ 40
𝑥−15
25−15
, 20 < 𝑥 < 40
0 , x ≤ 20
(3)
Rmid(x) =
{
1 , 𝑥 = 15
𝑥−5
15−5
,5 < 𝑥 < 15
25−𝑥
25−15
,15 < 𝑥 < 25
0 ,5 ≥ 𝑥 ≥ 25
(4)
Rnear(x) = {
1 , x ≤ 5
15−𝑥
15−5
, 5 < 𝑥 < 15
0 , x > 15
(5)
Figure 5 above shows the defuzzyfication result of the process. It gives the motor speed between
right and left in order to make a robot move forward by following the right wall. In the result, it still produces
the oscillation which is cused by different dc motors problem. Defuzzyfication process is based on the
following formula.
Figure 5. Fuzzy Logic Output Surface based on Two Sensor Inputs
𝑦∗
= Σ
𝜇(𝑦) × 𝑦
𝜇(𝑦)
(6)
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3. RESULTS AND ANALYSIS
It is important to test the designed system in order to know how reliable it is. Moreover, it can be
used to verify the system performance. Ther are some parameters used to measure the performance of the
system.
First of all, we have test how the communication can cover coordination between robots. Delay
parameter was used to know how good the used communication system is. Results of the measurement can
be seen below. For information, data was sent all from leader robot. Based on the result shown in Table 3,
delay can be minimized by using transfer rate 4000bps on the communication system. However, distance
between robot also affects the delay. Maximum distance of data transfer is 9 meters for this kind of
transceiver. On the other hand, if we applied 2000bps of transfer rate, data transfer process is produce more
stability and the variance of delays is less. At some point, it can be used more than 9 meters. Received signal
strength is still in the range to be accepted by receiver. Regarding to the evaluation of communication
system, we make a boundary of the robots workspace in a 9 meters radius. It is used because the leader robot
have to broadcast the information to all robots in the group. Nevertheless, every robot should be received
information from leader robot to define their movements in the area.
Then, it has been tested how robots execute their command from leader robot. It is shown on the
Table 4, that every robot in the group mostly executes command accurately based on received data. It can be
concluded that all of command from leader can be received by follower robots without error, so that follower
robots can execute them accurately. 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.
Table 3. Delay Testing Result
No.
Sampling
Rate
Transmitter Robot 1 Robot 2 Robot 3
Sent data Received data Delay (s) Received data Delay (s) Received data Delay (s)
1 4000 bps ABC ABC 0.15 ABC 0.15 ABC 0.15
2 4000 bps ABC ABC 0.13 ABC 0.13 ABC 0.13
6 4000 bps AB AB 0.13 AB 0.13 AB 0.13
7 4000 bps AB AB 0.14 AB 0.14 AB 0.14
11 4000 bps A A 0.12 A 0.12 A 0.12
12 4000 bps A A 0.13 A 0.13 A 0.13
16 2000 bps ABC ABC 0.19 ABC 0.19 ABC 0.19
17 2000 bps ABC ABC 0.16 ABC 0.16 ABC 0.16
21 2000 bps AB AB 0.2 AB 0.23 AB 0.23
22 2000 bps AB AB 0.22 AB 0.22 AB 0.22
26 2000 bps A A 0.22 A 0.22 A 0.22
27 2000 bps A A 0.17 A 0.17 A 0.17
31 1000 bps ABC ABC 0.7 ABC 0.49 ABC 0.49
32 1000 bps ABC Failed
Packet
Loss
Failed
Packet
Loss
Failed
Packet
Loss
38 1000 bps AB Failed
Packet
Loss
Failed
Packet
Loss
Failed
Packet
Loss
39 1000 bps AB Failed
Packet
Loss
Failed
Packet
Loss
Failed
Packet
Loss
41 1000 bps A A 0.2 A 0.2 A 0.2
42 1000 bps A A 0.2 A 0.2 A 0.2
Table 4. Robot Execution Test
Testing
Number -
Robot Leader Robot Follower
Annotation
Send Data Sent Data Receive Data Received Data Move as sent command
1 Yes Yes Yes Yes Yes Accurately
2 Yes Yes Yes Yes Yes Accurately
3 Yes Yes Yes Yes Yes Accurately
4 Yes Yes Yes Yes Yes Accurately
5 Yes Yes Yes Yes Yes Accurately
6 Yes Yes Yes Yes Yes Accurately
7 Yes Yes Yes Yes Yes Accurately
8 Yes Yes Yes Yes Yes Accurately
9 Yes Yes Yes Yes Yes Accurately
10 Yes Yes Yes Yes Yes Accurately
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4. CONCLUSION
On the multi-robot cases, every robot in the group can communicate in order to share information
between them simultanoeously. It is purposed to make a good coordination for environtment exploration or in
a simplified case, navigation. In the bigger purpose, a group of robots can explore and mapped the unknown
environtment quicker than single mobile robot.
In our case, 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.
Based on performance testing, formation can be established accurately without error on
communication. The error is provided by fuzzy output process which is caused by read data from ultrasound
sensor. More sampling can reduce the error but it will drive more execution time. Furthermore, coordination
time will need longer time and delay.
Communication process between leader and follower robot used RF 433MHz tranceiver module
with rate 4000bps in order to minimize transmission delay. Based on test, there was no packet loss until the
maximum distance 9 meters. Packet loss or error transmission would make robot execute wrong command so
that the formation could not be established.
In the near future, we plan to develop more process in the multi-robot schemes such as collision
avoidance and task allocation. It will be purposed to gain less time process in target or destination
accomplishment. For the example, that four robots will determine their task independently based on
information shared and their position in the maze, and define each path to reach the target differently.
REFERENCES
[1] J. Liu, K. Yuan, W. Zou and Q. Yang, "Monte Carlo Multi-Robot Localization Based on Grid Cells and
Characteristic Particles", International Conference on Advanced Intelligent Mechatronics, 2005.
[2] Tatiya Padang Tunggal, et al, “Pursuit Algorithm for Robot Trash Can Based on Fuzzy-Cell Decomposition”,
International Journal of Electrical and Computer Engineering (IJECE), Vol. 6, No. 6, December 2016, pp.
2863~2869.
[3] K.H. Lee, First Course on Fuzzy Theory and Applications, Berlin: Spinger, 2005.
[4] Adams, L. Vig and J.A., "Multi-Robot Coalition Formation", IEEE Transactions on Robotics, vol. 22, no. 4, pp.
637-649, 2006.
[5] FRQ Aini, AN Jati, U Sunarya, “A study of Monte Carlo Localization on Robot Operating System”, International
Conference on Information Technology System and Innovation (ICITSI), Bandung, 2015.
[6] M. Čáp, P. Novák, A. Kleiner and M. Selecký, "Prioritized Planning Algorithms for Trajectory Coordination of
Multiple Mobile Robots", IEEE Transactions on Automation Science and Engineering, vol. 12, no. 3, pp. 835-849,
2015.
[7] A.M. Fathan, A.N. Jati and R.E. Saputra, "Mapping Algorithm Using Ultrasonic and Compass Sensor on
Autonomous Mobile Robot," in 2016 International Conference on Control, Electronics, Renewable Energy and
Communications (ICCEREC), Bandung, 2016.
[8] C.H. Hsu and C.F. Juang, "Multi-objective Continuous- Ant-Colony-optimized FC for Robot Wall-Following
Control", IEEE Computational Intelligence Magazine , pp. 28-40, 2013.
[9] S. Li, R. Kong and Y. Guo, "Cooperative Distributed Source Seeking by Multiple Robots: Algorithms and
Experiments", IEEE/ASME Transactions on Mechatronics, vol. 19, no. 6, pp. 1810-1820, 2014
[10] L. Luo, N. Chakraborty and K. Sycara, "Provably-Good Distributed Algorithm for Constrained Multi-Robot Task
Assignment for Grouped Tasks", IEEE Transactions on Robotics, vol. 31, no. 1, pp. 19-30, 2015.
[11] A. Marino, G. Antonelli, A.P. Aguiar, A. Pascoal and S. Chiaverini, "A Decentralized Strategy for Multirobot
Sampling/Patrolling:Theory and Experiments", IEEE Transactions on Control Systems Technology, vol. 23, no. 1,
2015.
[12] D. Panagou, D.M. Stipanovic and P.G. Voulgaris, "Distributed Coordination Control for Multi-Robot Networks
Using Lyapunov-Like Barrier Functions", IEEE Transactions on Automatic Control, vol. 61, no. 3, pp. 617-632,
2016.
[13] L. Sabattini, C. Secchi, M. Cocetti, A. Levratti and C. Fantuzzi, "Implementation of Coordinated Complex
Dynamic Behaviors in Multirobot Systems", IEEE Transactions on Robotics, vol. 31, no. 4, pp. 1018-1032, 2015.
[14] A.P. Suparno, H. Widyantara and Harianto, "Simulasi Trajectory Planning dan Pembentukan Formasi pada Robot
Obstacle Avoidance", Journal of Control and Network Systems, vol. 4, no. 1, pp. 31-38, 2015.
[15] L. Vig and J.A. Adams, "Multi-Robot Coalition Formation", IEEE Transactions on Robotics, vol. 22, no. 4, pp.
637-649, 2006.
[16] W.B. Xu, X.P. Liu, X. Chen and J. Zhao, "Improved Artificial Moment Method for Decentralized Local Path
Planning of Multirobots", IEEE Transactions on Control Systems Technology, vol. 23, no. 6, pp. 2383-2390, 2015.
9. ISSN:2088-8708
Int J Elec & Comp Eng, Vol. 8, No. 6, December 2018 : 5098 - 5106
5106
[17] NT Al-Ghifary, AN Jati, RE Saputra, “Coordination Control of Simple Autonomous Mobile Robot”, IEEE
International Conference on Instrumentation Control and Automation, Yogyakarta – Indonesia, 2017.
10.1109/ICA.2017.8068420.
[18] Siti Nurmaini, Bambang Tutuko, “Intelligent Robotics Navigation System: Problems,Methods, and Algorithm”,
International Journal of Electrical and Computer Engineering (IJECE), Vol. 7, No. 6, December 2017, pp.
3711~3726.
[19] SM Mirzaei, MH Moattar, “Optimized PID Controller with Bacterial Foraging Algorithm”, International Journal
of Electrical and Computer Engineering (IJECE), Vol. 5, No. 6, December 2015, pp. 1372~1380.