Partial observability in EKF based mobile robot navigation is investigated in this paper to find a
solution that can prevent erroneous estimation. By only considering certain landmarks in an environment,
the computational cost in mobile robot can be reduced but with an increase of uncertainties to the system.
This is known as suboptimal condition of the system. Fuzzy Logic technique is proposed to ensure that the
estimation achieved desired performance even though some of the landmarks were excluded for
references. The Fuzzy Logic is applied to the measurement innovation of Kalman Filter to correct the
positions of both mobile robot and any observed landmarks during observations. The simulation results
shown that the proposed method is capable to secure reliable estimation results even a number of
landmarks being excluded from Kalman Filter update process in both Gaussian and non-Gaussian noise
conditions.
Online video-based abnormal detection using highly motion techniques and stat...TELKOMNIKA JOURNAL
At the essence of video surveillance, there are abnormal detection approaches, which have been proven to be substantially effective in detecting abnormal incidents without prior knowledge about these incidents. Based on the state-of-the-art research, it is evident that there is a trade-off between frame processing time and detection accuracy in abnormal detection approaches. Therefore, the primary challenge is to balance this trade-off suitably by utilizing few, but very descriptive features to fulfill online performance while maintaining a high accuracy rate. In this study, we propose a new framework, which achieves the balancing between detection accuracy and video processing time by employing two efficient motion techniques, specifically, foreground and optical flow energy. Moreover, we use different statistical analysis measures of motion features to get robust inference method to distinguish abnormal behavior incident from normal ones. The performance of this framework has been extensively evaluated in terms of the detection accuracy, the area under the curve (AUC) and frame processing time. Simulation results and comparisons with ten relevant online and non-online frameworks demonstrate that our framework efficiently achieves superior performance to those frameworks, in which it presents high values for the accuracy while attaining simultaneously low values for the processing time.
Vehicle Detection using Camera
Vehicle Detection Using Cameras for Self-Driving Cars |
Using machine learning and computer vision I create a pipeline that detects nearby vehicles from a dash-cam.
Online video-based abnormal detection using highly motion techniques and stat...TELKOMNIKA JOURNAL
At the essence of video surveillance, there are abnormal detection approaches, which have been proven to be substantially effective in detecting abnormal incidents without prior knowledge about these incidents. Based on the state-of-the-art research, it is evident that there is a trade-off between frame processing time and detection accuracy in abnormal detection approaches. Therefore, the primary challenge is to balance this trade-off suitably by utilizing few, but very descriptive features to fulfill online performance while maintaining a high accuracy rate. In this study, we propose a new framework, which achieves the balancing between detection accuracy and video processing time by employing two efficient motion techniques, specifically, foreground and optical flow energy. Moreover, we use different statistical analysis measures of motion features to get robust inference method to distinguish abnormal behavior incident from normal ones. The performance of this framework has been extensively evaluated in terms of the detection accuracy, the area under the curve (AUC) and frame processing time. Simulation results and comparisons with ten relevant online and non-online frameworks demonstrate that our framework efficiently achieves superior performance to those frameworks, in which it presents high values for the accuracy while attaining simultaneously low values for the processing time.
Vehicle Detection using Camera
Vehicle Detection Using Cameras for Self-Driving Cars |
Using machine learning and computer vision I create a pipeline that detects nearby vehicles from a dash-cam.
Scenario-Based Development & Testing for Autonomous DrivingYu Huang
Formal Scenario-Based Testing of Autonomous Vehicles: From Simulation to the Real World, 2020
A Scenario-Based Development Framework for Autonomous Driving, 2020
A Customizable Dynamic Scenario Modeling and Data Generation Platform for Autonomous Driving, 2020
Large Scale Autonomous Driving Scenarios Clustering with Self-supervised Feature Extraction, 2021
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles, 2021
Systems Approach to Creating Test Scenarios for Automated Driving Systems, Reliability Engineering and System Safety (215), 2021
A Much Advanced and Efficient Lane Detection Algorithm for Intelligent Highwa...cscpconf
This paper presents a much advanced and efficient lane detection algorithm. The algorithm is based on (ROI) Region of Interest segmentation. In this algorithm images are pre-processed by top-hat transform for de-noising and enhancing contrast. ROI of a test image is then extracted. For detecting lines in the ROI, Hough transform is used. Estimation of the distance between Hough origin and lane-line midpoint is made. Lane departure decision is made based on the difference between these distances. As for the simulation part we have used Matlab software.Experiments show that the proposed algorithm can detect the lane markings accurately and quickly.
Navigation is one of the main challenges in an underwater vehicle. To measure and sustain the depth in the micro class remotely operated vehicle (ROV) robot is one of the main demands in the underwater robot competition. There are many sensors that can be used to measure the depth; one of the sensors is using a single camera sensor. In this works, camera-based depth control is developed and evaluated for micro class ROV, namely as fitoplankton SAS ROV. Fitoplankton SAS ROV is a micro ROV prototype with six thrusters. To maintain the depth position, a PID control system with a camera-based depth sensor as the input of the setpoint is used. Moreover, the method for the camera to measure the distance is using the triangle similarity method. In this paper, the experimental scenario is using the rectangular marker to measure the distance, and the value of the depth is processing in the ground control station (GCS). The GCS will send the thruster value to control the depth, which depends on the PID control system. The experiment results show an average of depth accuracy of 95.74% to the depth setpoint.
The system presents a new framework for traffic density estimation based on topic model, which is an unsupervised model. It uses a set of visual features without any individual vehicle detection and tracking need, and discovers the motion patterns automatically in traffic scenes by using topic model
An IoT based Dynamic Traffic Signal ControlGauthamSK4
Used Kerner three-phase traffic theory to establishing an Intelligent Traffic System that will provide automatic management of traffic lights based on the concept of the Internet of Things which will resolve the traffic jam issues which will in turn reduce CO2 emissions and also the mobility metrics like the travel time.
Transit Signalisation Priority (TSP) - A New Approach to Calculate GainsWSP
Presentation by François Bélisle, Eng. , B.Sc., M.A. and Stephan Kellner, Eng., P.Eng., MS delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30.
Simulation design of trajectory planning robot manipulatorjournalBEEI
Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robot manipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.
Improving Posture Accuracy of Non-Holonomic Mobile Robot System with Variable...TELKOMNIKA JOURNAL
This paper presents a method to decrease imprecision and inaccuracy that have the tendency to
influence the posture of non-holonomic mobile robot by using the adaptive tuning of universe of discourse.
As such, the primary objective of the study is to force the posture error of , , and towards
zero. Hence, for each step of tuning the fuzzy domain, about 20% of imprecision and inaccuracy had been
added automatically into the variable universe fuzzy, while the control input was bound via scaling gain.
Furthermore, the simulation results showed that the tuning of universe fuzzy parameters could increase
the performance of the system from the aspects of response time and error for steady state through better
control of inaccuracy. Besides, the domains of universe fuzzy input [-4,4] and output [0,6] exhibited good
performance in inching towards zero values as the steady state error was about 1% for x(t) position, 0.02%
for y(t) position, and 0.16% for θ(t) orientation, whereas the posture error in the given reference was about
0.0002% .
A ROS IMPLEMENTATION OF THE MONO-SLAM ALGORITHMcsandit
Computer vision approaches are increasingly used in mobile robotic systems, since they allow
to obtain a very good representation of the environment by using low-power and cheap sensors.
In particular it has been shown that they can compete with standard solutions based on laser
range scanners when dealing with the problem of simultaneous localization and mapping
(SLAM), where the robot has to explore an unknown environment while building a map of it and
localizing in the same map. We present a package for simultaneous localization and mapping in
ROS (Robot Operating System) using a monocular camera sensor only. Experimental results in
real scenarios as well as on standard datasets show that the algorithm is able to track the
trajectory of the robot and build a consistent map of small environments, while running in near
real-time on a standard PC.
Scenario-Based Development & Testing for Autonomous DrivingYu Huang
Formal Scenario-Based Testing of Autonomous Vehicles: From Simulation to the Real World, 2020
A Scenario-Based Development Framework for Autonomous Driving, 2020
A Customizable Dynamic Scenario Modeling and Data Generation Platform for Autonomous Driving, 2020
Large Scale Autonomous Driving Scenarios Clustering with Self-supervised Feature Extraction, 2021
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles, 2021
Systems Approach to Creating Test Scenarios for Automated Driving Systems, Reliability Engineering and System Safety (215), 2021
A Much Advanced and Efficient Lane Detection Algorithm for Intelligent Highwa...cscpconf
This paper presents a much advanced and efficient lane detection algorithm. The algorithm is based on (ROI) Region of Interest segmentation. In this algorithm images are pre-processed by top-hat transform for de-noising and enhancing contrast. ROI of a test image is then extracted. For detecting lines in the ROI, Hough transform is used. Estimation of the distance between Hough origin and lane-line midpoint is made. Lane departure decision is made based on the difference between these distances. As for the simulation part we have used Matlab software.Experiments show that the proposed algorithm can detect the lane markings accurately and quickly.
Navigation is one of the main challenges in an underwater vehicle. To measure and sustain the depth in the micro class remotely operated vehicle (ROV) robot is one of the main demands in the underwater robot competition. There are many sensors that can be used to measure the depth; one of the sensors is using a single camera sensor. In this works, camera-based depth control is developed and evaluated for micro class ROV, namely as fitoplankton SAS ROV. Fitoplankton SAS ROV is a micro ROV prototype with six thrusters. To maintain the depth position, a PID control system with a camera-based depth sensor as the input of the setpoint is used. Moreover, the method for the camera to measure the distance is using the triangle similarity method. In this paper, the experimental scenario is using the rectangular marker to measure the distance, and the value of the depth is processing in the ground control station (GCS). The GCS will send the thruster value to control the depth, which depends on the PID control system. The experiment results show an average of depth accuracy of 95.74% to the depth setpoint.
The system presents a new framework for traffic density estimation based on topic model, which is an unsupervised model. It uses a set of visual features without any individual vehicle detection and tracking need, and discovers the motion patterns automatically in traffic scenes by using topic model
An IoT based Dynamic Traffic Signal ControlGauthamSK4
Used Kerner three-phase traffic theory to establishing an Intelligent Traffic System that will provide automatic management of traffic lights based on the concept of the Internet of Things which will resolve the traffic jam issues which will in turn reduce CO2 emissions and also the mobility metrics like the travel time.
Transit Signalisation Priority (TSP) - A New Approach to Calculate GainsWSP
Presentation by François Bélisle, Eng. , B.Sc., M.A. and Stephan Kellner, Eng., P.Eng., MS delivered at the 2015 Transportation Association of Canada (TAC) Conference & Exhibition, from September 27 to 30.
Simulation design of trajectory planning robot manipulatorjournalBEEI
Robots can be mathematically modeled with computer programs where the results can be displayed visually, so it can be used to determine the input, gain, attenuate and error parameters of the control system. In addition to the robot motion control system, to achieve the target points should need a research to get the best trajectory, so the movement of robots can be more efficient. One method that can be used to get the best path is the SOM (Self Organizing Maps) neural network. This research proposes the usage of SOM in combination with PID and Fuzzy-PD control for finding an optimal path between source and destination. SOM Neural network process is able to guide the robot manipulator through the target points. The results presented emphasize that a satisfactory trajectory tracking precision and stability could be achieved using SOM Neural networking combination with PID and Fuzzy-PD controller.The obtained average error to reach the target point when using Fuzzy-PD=2.225% and when using PID=1.965%.
Improving Posture Accuracy of Non-Holonomic Mobile Robot System with Variable...TELKOMNIKA JOURNAL
This paper presents a method to decrease imprecision and inaccuracy that have the tendency to
influence the posture of non-holonomic mobile robot by using the adaptive tuning of universe of discourse.
As such, the primary objective of the study is to force the posture error of , , and towards
zero. Hence, for each step of tuning the fuzzy domain, about 20% of imprecision and inaccuracy had been
added automatically into the variable universe fuzzy, while the control input was bound via scaling gain.
Furthermore, the simulation results showed that the tuning of universe fuzzy parameters could increase
the performance of the system from the aspects of response time and error for steady state through better
control of inaccuracy. Besides, the domains of universe fuzzy input [-4,4] and output [0,6] exhibited good
performance in inching towards zero values as the steady state error was about 1% for x(t) position, 0.02%
for y(t) position, and 0.16% for θ(t) orientation, whereas the posture error in the given reference was about
0.0002% .
A ROS IMPLEMENTATION OF THE MONO-SLAM ALGORITHMcsandit
Computer vision approaches are increasingly used in mobile robotic systems, since they allow
to obtain a very good representation of the environment by using low-power and cheap sensors.
In particular it has been shown that they can compete with standard solutions based on laser
range scanners when dealing with the problem of simultaneous localization and mapping
(SLAM), where the robot has to explore an unknown environment while building a map of it and
localizing in the same map. We present a package for simultaneous localization and mapping in
ROS (Robot Operating System) using a monocular camera sensor only. Experimental results in
real scenarios as well as on standard datasets show that the algorithm is able to track the
trajectory of the robot and build a consistent map of small environments, while running in near
real-time on a standard PC.
16 channels Velodyne versus planar LiDARs based perception system for Large S...Brett Johnson
The ability of self-localization is a basic requirement
for an autonomous vehicle, and a prior reconstruction
of the environment is usually needed. This paper analyses the
performances of two typical hardware architectures that we
evaluate in our 2D Simultaneous Localization and Mapping
(2D-SLAM) system for large scale scenarios. In particular, the
selected configurations are supposed to guarantee the possibility
of integrating at a later stage mobile objects tracking capabilities
without modifying the hardware architecture. The choice of
the perception system plays a vital role for building a reliable
and simple architecture for SLAM. Therefore we analyse two
common configurations: one based on three planar LiDARs Sick
LMS151 and the other based on a Velodyne 3D LiDAR VLP-
16. For each of the architectures we identify advantages and
drawbacks related to system installation, calibration complexity
and robustness, quantifying their respective accuracy for localization
purposes. The conclusions obtained tip the balance to
the side of using a Velodyne-like sensor facilitating the process
of hardware implementation, keeping a lower cost and without
compromising the accuracy of the localization. From the point
of view of perception, additional advantages arise from the
fact of having 3D information available on the system for other
purposes.
A study on data fusion techniques used in multiple radar trackingTBSS Group
This project aimed to compare the use of and resultant errors when Measurement Fusion (Plot Fusion) and Track Fusion were used to combine data from various sensors in a simulated environment analogous to the Singaporean environment. The environment and analysis was done wholly using a program executed by MATLAB 6.1, and results showed that Measurement Fusion was more accurate when tracking objects following a path with many turns. However, the major source of error was not the fusion algorithm, but the inclusion algorithm.
MODELING, IMPLEMENTATION AND PERFORMANCE ANALYSIS OF MOBILITY LOAD BALANCING ...IJCNCJournal
We propose in this paper a simulation implementation of Self-Organizing Networks (SON) optimization
related to mobility load balancing (MLB) for LTE systems using ns-3 [1]. The implementation is achieved
toward two MLB algorithms dynamically adjusting handover (HO) parameters based on the Reference
Signal Received Power (RSRP) measurements. Such adjustments are done with respect to loads of both an
overloaded cell and its cells’ neighbours having enough available resources enabling to achieve load
balancing. Numerical investigations through selected key performance indicators (KPIs) of the proposed
MLB algorithms when compared with another HO algorithm (already implemented in ns-3) based on A3
event [2] highlight the significant MLB gains provided in terms global network throughput, packet loss rate
and the number of successful HO without incurring significant overhead.
Maximum likelihood estimation-assisted ASVSF through state covariance-based 2...TELKOMNIKA JOURNAL
The smooth variable structure filter (ASVSF) has been relatively considered as a new robust predictor-corrector method for estimating the state. In order to effectively utilize it, an SVSF requires the accurate system model, and exact prior knowledge includes both the process and measurement noise statistic. Unfortunately, the system model is always inaccurate because of some considerations avoided at the beginning. Moreover, the small addictive noises are partially known or even unknown. Of course, this limitation can degrade the performance of SVSF or also lead to divergence condition. For this reason, it is proposed through this paper an adaptive smooth variable structure filter (ASVSF) by conditioning the probability density function of a measurement
to the unknown parameters at one iteration. This proposed method is assumed to accomplish the localization and direct point-based observation task of a wheeled mobile robot, TurtleBot2. Finally, by realistically simulating it and comparing to a conventional method, the proposed method has been showing a better accuracy and stability in term of root mean square error (RMSE) of the estimated map coordinate (EMC) and estimated path coordinate (EPC).
International Journal of Computational Engineering Research (IJCER) ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
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.
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.
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.
COIFLET-BASED FUZZY-CLASSIFIER FOR DEFECT DETECTION IN INDUSTRIAL LNG/LPG TANKScsandit
This paper describes a classification method for raw sensor data using a Fuzzy Inference
System to detect the defects in large LNG tanks. The data is obtained from a Magnetic Flux
Leakage (MFL) sensing system which is usually used in the industry to located defects in
metallic surfaces, such as tank floors. A robotic inspection system has been developed in
conjunction with the presented work which performs the same inspection tasks at much lower
temperatures than human operators would thus reducing the shutdown time significantly which
is typically of the order of 15-20 million Dollars per day. The main challenge was to come up
with an algorithm that can map the human heuristics used by the MFL inspectors in field to
locate the defects into an automated system and yet keep the algorithm simple enough to be
deployed in near real-time applications. Unlike the human operation of the MFL equipment, the
proposed technique is not very sensitive to the sensor distance from the test surface and the
calibration requirements are also very minimal which are usually a big impediment in speedy
inspections of the floor by human operator. The use of wavelet decomposition with Coiflet
waves has been utilized here for deconvolving the essential features of the signal before
calculating the classification features. This wavelet was selected to its canny resemblance with
the actual MFL signals that makes these wavelets very natural basis function for
decomposition..
EffectiveOcclusion Handling for Fast Correlation Filter-based TrackersEECJOURNAL
Correlation filter-based trackers heavily suffer from the problem of multiple peaks in their response maps incurred by occlusions. Moreover, the whole tracking pipeline may break down due to the uncertainties brought by shifting among peaks, which will further lead to the degraded correlation filter model. To alleviate the drift problem caused by occlusions, we propose a novel scheme to choose the specific filter model according to different scenarios. Specifically, an effective measurement function is designed to evaluate the quality of filter response. A sophisticated strategy is employed to judge whether occlusions occur, and then decide how to update the filter models. In addition, we take advantage of both log-polar method and pyramid-like approach to estimate the best scale of the target. We evaluate our proposed approach on VOT2018 challenge and OTB100 dataset, whose experimental result shows that the proposed tracker achieves the promising performance compared against the state-of-the-art trackers.
Refining Underwater Target Localization and Tracking EstimatesCSCJournals
Improving the accuracy and reliability of the localization estimates and tracking of underwater targets is a constant quest in ocean surveillance operations. The localization estimates may vary owing to various noises and interferences such as sensor errors and environmental noises. Even though adaptive filters like the Kalman filter subdue these problems and yield dependable results, targets that undergo maneuvering can cause incomprehensible errors, unless suitable corrective measures are implemented. Simulation studies on improving the localization and tracking estimates for a stationary target as well as a moving target including the maneuvering situations are presented in this paper
Similar to A Solution to Partial Observability in Extended Kalman Filter Mobile Robot Navigation (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
In this paper, snake optimization algorithm (SOA) is used to find the optimal gains of an enhanced controller for controlling congestion problem in computer networks. M-file and Simulink platform is adopted to evaluate the response of the active queue management (AQM) system, a comparison with two classical controllers is done, all tuned gains of controllers are obtained using SOA method and the fitness function chose to monitor the system performance is the integral time absolute error (ITAE). Transient analysis and robust analysis is used to show the proposed controller performance, two robustness tests are applied to the AQM system, one is done by varying the size of queue value in different period and the other test is done by changing the number of transmission control protocol (TCP) sessions with a value of ± 20% from its original value. The simulation results reflect a stable and robust behavior and best performance is appeared clearly to achieve the desired queue size without any noise or any transmission problems.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
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.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
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.
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.
2. TELKOMNIKA ISSN: 1693-6930
A Solution to Partial Observability in Extended Kalman Filter Mobile Robot… (Hamzah Ahmad)
135
demonstrate this condition is by considering a mobile robot which is able to recognize several
landmarks at a time compared to other different observation time. Even though this problem is
critical, still under investigation and further improvement, the situation has motivates a case to
determine the system performance when only several identified landmarks are referred during
mobile robot observations. By doing this, it is expected that the system can reduce its
computational cost and at the same time guarantees good estimation results [5], [6].
In SLAM, the partial observability problem is categorized and analyzed into three main
aspects; unstable partially observable, partially observable and observable SLAM problem[7]. It
is claimed that the partially observability has makes the mobile robot depends heavily on its
initial conditions [8], [9]. Due to partial observability, the performance of observation can
become worse as the updated state covariance of the system cannot guaranteed to be
converge even if the mobile robot has done multiple observations on its surroundings. EKF-
SLAM has been one of the influential technique and been analyzed thoroughly in different
perspectives [10]-[13]. The technique is also been widely applied in real-life applications for
navigation purposes.
This paper is organized as follow. Section 2 describes the proposed technique of EKF
based SLAM and Fuzzy Logic technique. Section 3 demonstrates the simulation results and
analysis of the proposed method amd finally section 4 concludes the paper.
2. Extended Kalman Filter and Fuzzy Logic Approaches in SLAM
2.1. Extended Kalman Filter in SLAM
SLAM normally consists of two general processes which are the kinematics or process
step and the measurement step. The process stage defines the mathematical analysis of the
model focusing on the kinematics of the mobile robot with consideration of the landmarks
location being recognized. SLAM uses the mobile robot velocity and angular velocity to
determine its location. The measurement step on the other hand calculates the relative angle
and distance between mobile robot and any observed landmarks. Both of process and
measurement stages utilizes the mobile robot sensors to determine the positions and map
building. The process step is as follows.
(1)
where is an augmented state consisting of the mobile robot heading angle and x,y positions
with landmarks x,y locations. A and B are the transition matrix and control matrix respectively. U
is the control input of mobile robot velocity and angular velocity, while ω is the process noise of
the mobile robot. The measurement process takes the following mathematical equation.
(2)
is the measurement matrix containing information about relative distance and relative
angle between mobile robot to each landmark. H is the measurement matrix and ν is the
measurement noise occurred during mobile robot observations. EKF works based on the above
two SLAM model to estimate the mobile robot and landmarks positions. There are two main
stages to be computed which are predict and update stages. Table 1 shows the EKF steps to
perform the estimation. Tables and Figures are presented center, as shown below and cited in
the manuscript.
Table 1. Kalman Filter Algorithm
Kalman Filter
Prediction State model ̂ ̂
State covariance
Update State model ̂ ̂ ̂
State covariance
Kalman Gain
3. ISSN: 1693-6930
TELKOMNIKA Vol. 16, No. 1, February 2018 : 134 – 141
136
As shown in Table 1 above, ̂ is the estimated augmented state. is the state
covariance while the sign of “+”, “-“ defines the priori and posteriori estimation at time k. Kalman
Gain plays important role in Kalman Filter where it leads to better estimation. Remarks that, A,
B, H are the linearized matrices as this study considers EKF as it filter for estimation. The
process noise and measurement noise covariances are presented by Q and R and these two
noises are uncorrelated throughout the analysis.
From Table 1, the updated state model consists of element ̂ which
determines the measurement innovation of the system. If the value of this measurement
innovation is too big, then Kalman Gain attempts to reduce it so that the updated state model
remains holding a very small error during mobile robot observations. From above table 1, this is
also means that the measurement innovation must be kept very small at all time. In normal EKF,
this cannot be guarantees at all time as sometimes due to environment conditions, there is a
possibility of sensor fault which in turns exhibits higher error to the readings. As one of the
family of Bayes Filter, EKF only depends on its latest update. Hence, the estimation may
becomes erroneous if no further action being made to the system. Having said that, Fuzzy Logic
is being proposed to control the amount of information gathered by the sensor. If the
measurement innovation accidentally produced higher amount of noises, then the Fuzzy Logic
reduced it for better estimation results.
2.2. Fuzzy Logic Technique
As mentioned on previous subsection, Fuzzy Logic is proposed to reduced the noises
or error developed by the measurement innovation computations. Figure 1 presents the design
of Fuzzy Logic to the proposed system. To design the Fuzzy Logic, there are three main phases
to be considered i.e Fuzzification, Rule Evaluation and Defuzzification[14]. Fuzzification
describes the conditions that needs to be assessed which are in this case the measured relative
angle and measured relative distances between mobile robot and landmarks. It is essential to
have prior knowledge on the system performance before beginning to design Fuzzy Logic. The
input and output of Fuzzy Logic is same as the main objectives of Fuzzy Logic is to reduce the
measurement innovation. By knowing these situation, then the fuzzy sets and membership
function are selected. Mamdani technique is chosen with three fuzzy sets each for both input
and output.
The rule evaluation determines the best configuration of the designed rule to the whole
system. It computes the fuzziness of the system based on the rules. Defuzzification is then
evaluates using Center of Gravity to obtain the reduced measurement innovation to be
calculated with Kalman Gain in achieving small error to the updated system. The fuzzy sets and
triangular memberships are included in Figure 2 for references. Triangular membership was
selected as it compute faster and regularly used for design compared to other available
membership types. The fuzzy sets are defined based on preliminary results of simulations.
Figure 1. Modified measurement innovation calculation with the presence of fuzzy logic
controller to the proposed system
4. TELKOMNIKA ISSN: 1693-6930
A Solution to Partial Observability in Extended Kalman Filter Mobile Robot… (Hamzah Ahmad)
137
(a) (b)
(c) (d)
Figure 2. Input to the fuzzy logic (a) Measured relative angle (b) Measured relative distance.
Output of the fuzzy logic (c) Calculated relative angle (d) Calculated relative distance
3. Results and Analysis
This section explains the results of research and at the same time is given the
comprehensive discussion about our proposed technique. The simulation settings are described
in Table 2 for reference. The parameters are chosen based on our previous experimental
analysis. Global coordinate system is referred as the reference for the system to operate. The
simulation considers two different environmental noises which are Gaussian and non-Gaussian
noise to assess the EKF performance in both situations where suboptimal conditions take place
during observation. The environment is also assume to be planar and mobile robot received all
the observation during its measurements.
3.1. EKF based SLAM with suboptimal conditions
This subsection explains the effect of having an EKF as estimator in navigation
especially in SLAM problem. It is undeniable, a normal EKF do the estimation nicely in
Gaussian noise conditions but with a full computational cost of analysis. By doing some
modifications on the state covariance update as shown in Table 1, the computational cost can
be reduced hence produces faster computations. Figures 3 presents the performance of normal
EKF and EKF with partial observability respectively. Mobile robot movements estimation as well
as landmarks estimation determines that the EKF with partial observability conditions has better
estimation. Remark that in partial observability, only certain landmarks are considered. Only
three number of the landmarks are treated for reference while other landmarks are excluded
0.060.15
1
0
0.18 0.23 0.38
Degreeofmembership
0.040.05
1
0
0 0.02 0.05
Degreeofmembership
7-5
1
0
12 35
De
gr
ee
of
me
m
be
rsh
ip
-10
-0.05 -0.04
1
0
0.05 0.08
Degreeofmembership
0.01-0.08
5. ISSN: 1693-6930
TELKOMNIKA Vol. 16, No. 1, February 2018 : 134 – 141
138
from measurement innovation calculations. The mobile robot also holds very high confidence
about its location compared to the normal conditions as depicted in Figure 3(b).
An interesting results happen when the environment conditions are changed to include
non-Gaussian noise. If the mobile robot operates in non-Gaussian noise, then the results
becomes not as promising as the previous case and this is shown in Figure 4. The estimation
exhibits erroneous results especially for the landmarks estimation even when the mobile robot
has higher confidence about its location(refer to Figure 4(b)). Notice that, the state covariance
for suboptimal conditions are also producing lower uncertainties that eventually makes EKF
becomes optimistics about its estimation [5]. For this case, minor modifications on the approach
especially on measurement innovations must be made to guarantee better results.
Table 2. Simulation Parameters
Variable Values
Process Noise 10e-7
Measurement Noise
Angular noise=0.001
Distance noise=0.001
Random noise
Process noise
(minimum -0.002, maximum 0.001)
Measurement noise
(minimum -0.15,
maximum 0,01)
Landmarks locations
[ -20; 60;
60; 120;
-30; 180;
-200; 230;
-220; 160;
200; 160;
-190; -40;
170; -50;
20; 240;
-10; -200;
-80; -60;
10; 130
3 ; 4];
Initial state covariance
Mobile robot=0.001
Landmarks=100
Mobile Robot initial position (x,y, theta)=(0,0,0)
3.2. EKF based SLAM in Suboptimal Condition with Fuzzy Logic
As shown in previous subsection, EKF becomes erroneous especially when non-
Gaussian noise exist during mobile robot observations. In order to overcome such inconsistency
in estimation, Fuzzy Logic is proposed to correct the estimation. The Fuzzy Logic is then
attached after the measurement innovation step to ensure that the updated state estimation
becomes better and producing less error.
Preliminary results in Figure 5 have shown that by applying Fuzzy Logic, the landmarks
estimation has become way better than the one being predicted by the EKF with suboptimal
condition especially about its landmarks estimations. Additional simulations with different mobile
robot movements are also being carried to obtain the consistency of the proposed technique.
The results in figure 6 depicts that the proposed technique guarantees a good estimation can be
achieved for different mobile robot movements compared to the normal EKF estimations. It is
worth to mention that, if the mobile robot operates in different environment, Fuzzy Logic must be
modified and re-design to suit with the new environment. Otherwise, the results can be not
promising as expected. Based on the observations and literatures [9], the angle measurement
plays an important role to guarantee good estimation.
6. TELKOMNIKA ISSN: 1693-6930
A Solution to Partial Observability in Extended Kalman Filter Mobile Robot… (Hamzah Ahmad)
139
(a) (b)
Figure 3 (a) Comparison between Normal EKF(red dash line) and EKF with suboptimal
conditions(blue dash line).(b) State covariance performances for mobile robot and landmarks
(a) (b)
Figure 4 (a) Comparison between Normal EKF(red dash line) and EKF with suboptimal
conditions(blue dash line) in non-Gaussian noise conditions. (b) State covariance performances
for mobile robot and landmarks
(a) (b)
Figure 5. Comparison between suboptimal EKF(blue line) and Fuzzy EKF(black line) in non-
Gaussian noise conditions for both (a) mobile robot and landmarks estimation and (b) Updated
state covariance performances
7. ISSN: 1693-6930
TELKOMNIKA Vol. 16, No. 1, February 2018 : 134 – 141
140
(a)
(b)
Figure 6. The performance of the proposed fuzzy EKF in suboptimal condition(blue) in various
mobile robot (a), (b) movements compared to normal EKF performance
4. Conclusion
This paper has presented an analysis of Fuzzy Logic in Extended Kalman Filter
navigation to prevent error in partial observability problem. Two different noise conditions are
being analyzed to determine any inconsistency of the proposed method. Based on the results,
the Fuzzy Logic technique can further improved the estimation results especially for the
landmarks estimation for both gaussian and non-gaussian noise environments even with
different mobile robot movements. Note that, as the proposed technique is only designed for a
static landmarks conditions, the system performance can varies if more dynamic environment is
taken into account for observation and require modifications on Fuzzy Logic design.
Acknowledgements
The author would like to thank Ministry of Higher Education and Universiti Malaysia
Pahang for their continuous supports in this research through RDU160145 and RDU160379.
Special thanks to Namerikawa Laboratory in Keio University for their participation and advises.
References
[1] S Thrun, et al. Probabilistic Robotic. 1st Edition. MIT Press. 2009; pp. 1-9.
8. TELKOMNIKA ISSN: 1693-6930
A Solution to Partial Observability in Extended Kalman Filter Mobile Robot… (Hamzah Ahmad)
141
[2] H DurrantWhyte, et al. Simultaneous Localization and Mapping: Part 1. IEEE Robotics & Automation
Magazine. 2006; 13(2): 99-110.
[3] J Andrade Cetto, et al. The Effects of Partial Observability in SLAM. IEEE International Conference on
Robotics & Automation, 2004; 1: 397-402.
[4] Guoquan P Huang, et al. On Filter Consistency of Discrete-Time nonlinear systems with partial-state
measurements. in American Control Conference. 2013: 5468-5475.
[5] H.Ahmad, et al. EKF based Slam with FIM Inflation. 2011 8th Asian Control Conference(ASCC2011).
2011: 782-787.
[6] B.Noack, et al. Treatment of Biased and Dependent Sensor Data in Graph-Based SLAM. 18th
International Conference on Information Fusion. 2015: 1862-1867.
[7] T Vidal-Valleja, et.al. Conditions for Suboptimal Filter Stability in SLAM. 2004 IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS). 2004; 1: 27-32.
[8] RC Smith, P Cheereman. On the representation and estimation of spatial uncertainty. Robol. Res,
1986; 5(4): 56-68.
[9] MWMG Disranayake, P Newman, S Clark, HF Durrant-Whyte, M Csorba. A solution to the
simultaneous localization and map building (SLAM) problem . IEEE Trsns. Robot. Automation. 2001;
17(3): 229-241.
[10] J Simanek, et al. Evaluation of the EKF-Based Estimation Architectures for Data Fusion in Mobile
Robots. IEEE/ASME Transaction on Mechatronics. 2015; 20(2): 985-990.
[11] D.Gualda.Partially Constrained Extended Kalman Filter for Navigation Inluding Mapping Information.
IEEE Sensor Journal, 2016; 16(24): 9036-9046.
[12] T Zhang, et al. Convergence and Consistency Analysis for a 3-D Invariant-EKF SLAM. IEEE Robotic
and Automatic Letters. 2017; 2(2): 733-740.
[13] SS Kia, et al. Cooperative Localization for Mobile Agents: A Recursive Decentralized Algorithm Based
on Kalman-Filter Decoupling. IEEE Control System, 2016; 36(2): 86-101.
[14] M Negnevitsty. Artificial Intelligence: A Guide to Intelligent Systems . 3rd Edition, Addison-Wesley
Pearson. 2011: 12-17.