Pub Date : 2023-03-01DOI: 10.11591/ijra.v12i1.pp41-53
P. Thai, Ngoc Hung Nguyen
Nowadays, there are various research on transformable robot. The use of origami pattern for transformable robot can be found in many research. The disadvantages of traditional origami model are the suitable material for folding is zero thickness, complicated patterns and overconstrained mechanism. In this paper, the idea of designing 1 degree-of-freedom box-shaped robot is proposed and two types of robot design have been analyzed. The first design is the waterbomb robot, that uses the traditional origami pattern. The second model takes the Sarrus linkage as the main mechanism for the mobile robot. In both designs, only one motor is required for the transformation of the robot, making the robot light-weight and portable. This paper analyzes the kinematic and dynamic properties of two transformable robots by using MATLAB. The comparison of the torque required for forming 3D shape has been done for optimizing robot design. Finally, the real model optimized design is introduced to illustrate the proposed method.
{"title":"On solving the kinematics and Controlling of Origami Box-shaped robot, 405-415. Si","authors":"P. Thai, Ngoc Hung Nguyen","doi":"10.11591/ijra.v12i1.pp41-53","DOIUrl":"https://doi.org/10.11591/ijra.v12i1.pp41-53","url":null,"abstract":"Nowadays, there are various research on transformable robot. The use of origami pattern for transformable robot can be found in many research. The disadvantages of traditional origami model are the suitable material for folding is zero thickness, complicated patterns and overconstrained mechanism. In this paper, the idea of designing 1 degree-of-freedom box-shaped robot is proposed and two types of robot design have been analyzed. The first design is the waterbomb robot, that uses the traditional origami pattern. The second model takes the Sarrus linkage as the main mechanism for the mobile robot. In both designs, only one motor is required for the transformation of the robot, making the robot light-weight and portable. This paper analyzes the kinematic and dynamic properties of two transformable robots by using MATLAB. The comparison of the torque required for forming 3D shape has been done for optimizing robot design. Finally, the real model optimized design is introduced to illustrate the proposed method. ","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131189170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-17DOI: 10.2316/Journal.206.2017.4.206-4782
Y. V. Karteek, I. Kar, S. Majhi
This paper proposes two algorithms, namely "back-tracking" and "history following", to reach consensus in case of communication loss for a network of distributed agents with switching topologies. To reach consensus in distributed control, considered communication topology forms a strongly connected graph. The graph is no more strongly connected whenever an agent loses communication.Whenever an agent loses communication, the topology is no more strongly connected. The proposed back-tracking algorithm makes sure that the agent backtracks its position unless the communication is reestablished, and path is changed to reach consensus. In history following, the agents use their memory and move towards previous consensus point until the communication is regained. Upon regaining communication, a new consensus point is calculated depending on the current positions of the agents and they change their trajectories accordingly. Simulation results, for a network of six agents, show that when the agents follow the previous history, the average consensus time is less than that of back-tracking. However, situation may arise in history following where a false notion of reaching consensus makes one of the agents stop at a point near to the actual consensus point. An obstacle avoidance algorithm is integrated with the proposed algorithms to avoid collisions. Hardware implementation for a three robots system shows the effectiveness of the algorithms.
{"title":"Consensus of Multi-Agent Systems using Back-tracking and History following Algorithms","authors":"Y. V. Karteek, I. Kar, S. Majhi","doi":"10.2316/Journal.206.2017.4.206-4782","DOIUrl":"https://doi.org/10.2316/Journal.206.2017.4.206-4782","url":null,"abstract":"This paper proposes two algorithms, namely \"back-tracking\" and \"history following\", to reach consensus in case of communication loss for a network of distributed agents with switching topologies. To reach consensus in distributed control, considered communication topology forms a strongly connected graph. The graph is no more strongly connected whenever an agent loses communication.Whenever an agent loses communication, the topology is no more strongly connected. The proposed back-tracking algorithm makes sure that the agent backtracks its position unless the communication is reestablished, and path is changed to reach consensus. In history following, the agents use their memory and move towards previous consensus point until the communication is regained. Upon regaining communication, a new consensus point is calculated depending on the current positions of the agents and they change their trajectories accordingly. Simulation results, for a network of six agents, show that when the agents follow the previous history, the average consensus time is less than that of back-tracking. However, situation may arise in history following where a false notion of reaching consensus makes one of the agents stop at a point near to the actual consensus point. An obstacle avoidance algorithm is integrated with the proposed algorithms to avoid collisions. Hardware implementation for a three robots system shows the effectiveness of the algorithms.","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"64 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122656954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Stabilizing control Algorithm for nonholonomic wheeled Mobile robots using adaptive integral sliding mode","authors":"W. Abbasi, F. Rehman, Ibrahim Shah, Arshad Rauf","doi":"10.2316/J.2019.206-4803","DOIUrl":"https://doi.org/10.2316/J.2019.206-4803","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133372958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-23DOI: 10.2316/Journal.206.2018.1.206-4938
Zheng Zhu, Wei Zou, Qingbin Wang, Feng Zhang
Aiming at the problem of tracking delay and large errors when conventional image-based visual servo is applied to tracking moving objects, a velocity compensation image-based visual servo controller is proposed for head-fixed oculomotor control in this paper, which covers saccade, smooth pursuit and vergence. The controller consists of a basic visual servo sub-controller and a velocity compensation sub-controller. The former is used to eliminate position error and the latter takes into account the target’s velocity. Corresponding Jacobian matrixes are derived to implement the controller. At the same time, a novel adaptive gain is designed to boost the control law and continuous velocities are implemented to avoid abrupt changes. A simple but stable fixation point detection method is proposed to provide the input for the whole system. Extensive experiments are conducted and analysed in a real binocular platform implemented with off-the-shelf set-ups, which demonstrate the effectiveness of the
{"title":"A velocity compensation Visual servo method for oculomotor control of bionic eyes","authors":"Zheng Zhu, Wei Zou, Qingbin Wang, Feng Zhang","doi":"10.2316/Journal.206.2018.1.206-4938","DOIUrl":"https://doi.org/10.2316/Journal.206.2018.1.206-4938","url":null,"abstract":"Aiming at the problem of tracking delay and large errors when conventional image-based visual servo is applied to tracking moving objects, a velocity compensation image-based visual servo controller is proposed for head-fixed oculomotor control in this paper, which covers saccade, smooth pursuit and vergence. The controller consists of a basic visual servo sub-controller and a velocity compensation sub-controller. The former is used to eliminate position error and the latter takes into account the target’s velocity. Corresponding Jacobian matrixes are derived to implement the controller. At the same time, a novel adaptive gain is designed to boost the control law and continuous velocities are implemented to avoid abrupt changes. A simple but stable fixation point detection method is proposed to provide the input for the whole system. Extensive experiments are conducted and analysed in a real binocular platform implemented with off-the-shelf set-ups, which demonstrate the effectiveness of the","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128439654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.2316/Journal.206.2018.6.206-5184
Ran Zhao, D. Sidobre
This paper aims to propose an on-line trajectory generation algorithm that is able to address not only constant but also time-variant kinematic motion constraints for multi-DOFs robot manipulators. By using a concatenation of cubic polynomials, the proposed method can provide a smooth trajectory that is synchronized and bounded in the robot kinematic motion constraints which are expressed as upper bounds on the absolute values of velocity, acceleration, and jerk. An additional decision tree will select intermediate motion profiles when the motion constraints are abruptly changed. Due to direct computation without optimization computation or randomized algorithms, the proposed solution requires only a short execution time. Simulations and experiments were conducted to verify the feasibility and effectiveness of this algorithm in smooth trajectory generation from arbitrary states of motion. With the proposed approach, robot motion can be limited by the kinematic motion constraints which will reduce manipulator wear and improve tracking accuracy and speed. The proposed algorithm can be used in real time due to the low computational complexity.
{"title":"On-Line trajectory Generation considering kinematic motion Constraints for robot manipulators","authors":"Ran Zhao, D. Sidobre","doi":"10.2316/Journal.206.2018.6.206-5184","DOIUrl":"https://doi.org/10.2316/Journal.206.2018.6.206-5184","url":null,"abstract":"This paper aims to propose an on-line trajectory generation algorithm that is able to address not only constant but also time-variant kinematic motion constraints for multi-DOFs robot manipulators. By using a concatenation of cubic polynomials, the proposed method can provide a smooth trajectory that is synchronized and bounded in the robot kinematic motion constraints which are expressed as upper bounds on the absolute values of velocity, acceleration, and jerk. An additional decision tree will select intermediate motion profiles when the motion constraints are abruptly changed. Due to direct computation without optimization computation or randomized algorithms, the proposed solution requires only a short execution time. Simulations and experiments were conducted to verify the feasibility and effectiveness of this algorithm in smooth trajectory generation from arbitrary states of motion. With the proposed approach, robot motion can be limited by the kinematic motion constraints which will reduce manipulator wear and improve tracking accuracy and speed. The proposed algorithm can be used in real time due to the low computational complexity.","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127310826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-01-30DOI: 10.2316/Journal.206.2018.1.206-5044
Malu Zhang, Hong Qu, Jianping Li, A. Belatreche, Xiurui Xie, Zhi Zeng
Humans and primates are remarkably good at pattern recognition and outperform the best machine vision systems with respect to almost any measure. Building a computational model that emulates the architecture and information processing in biological neural systems has always been an attractive target. To build a computational model that closely follows the information processing and architecture of the visual cortex, in this paper, we have improved the latency-phase encoding to express the external stimuli in a more abstract manner. Moreover, inspired by recent findings in the biological neural system, including architecture, encoding, and learning theories, we have proposed a feedforward computational model of spiking neurons that emulates object recognition of the visual cortex for pattern recognition. Simulation results showed that the proposed computational model can perform pattern recognition task well. In addition, the success of this computational model suggests a plausible proof for feedforward architecture of pattern recognition in the visual cortex.
{"title":"Feedforward Computational Model for Pattern Recognition with Spiking neurons","authors":"Malu Zhang, Hong Qu, Jianping Li, A. Belatreche, Xiurui Xie, Zhi Zeng","doi":"10.2316/Journal.206.2018.1.206-5044","DOIUrl":"https://doi.org/10.2316/Journal.206.2018.1.206-5044","url":null,"abstract":"Humans and primates are remarkably good at pattern recognition and outperform the best machine vision systems with respect to almost any measure. Building a computational model that emulates the architecture and information processing in biological neural systems has always been an attractive target. To build a computational model that closely follows the information processing and architecture of the visual cortex, in this paper, we have improved the latency-phase encoding to express the external stimuli in a more abstract manner. Moreover, inspired by recent findings in the biological neural system, including architecture, encoding, and learning theories, we have proposed a feedforward computational model of spiking neurons that emulates object recognition of the visual cortex for pattern recognition. Simulation results showed that the proposed computational model can perform pattern recognition task well. In addition, the success of this computational model suggests a plausible proof for feedforward architecture of pattern recognition in the visual cortex.","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121950818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2017-11-08DOI: 10.2316/Journal.206.2017.1.206-4624
Hongkai Chen, Xiaoguang Zhao, M. Tan, Shiying Sun
State recognition in disconnecting switches is important during substation automation. Here, an effective computer vision-based automatic detection and state recognition method for disconnecting switches is proposed. Taking advantage of some important prior knowledge about a disconnecting switch, the method is designed using two important features of the fixed-contact facet of such disconnecting switches. First, the Histograms of Oriented Gradients (HOG) of the fixed-contact are used to design a Linear Discriminant Analysis (LDA) target detector to position the disconnecting switches and distinguish their loci against a usual cluttered background. Then a discriminative Norm Gradient Field (NGF) feature is used to train the Support Vector Machine (SVM) state classifier to discriminate disconnecting switch states. Finally, experimental results, compared with other methods, demonstrate that the proposed method is effective and achieves a low miss rate while delivering high performance in both precision and recall rate. In addition, the adopted approach is efficient and has the potential to work in practical substation automation scenarios.
{"title":"Computer Vision-based Detection and State Recognition for disconnecting Switch in Substation Automation","authors":"Hongkai Chen, Xiaoguang Zhao, M. Tan, Shiying Sun","doi":"10.2316/Journal.206.2017.1.206-4624","DOIUrl":"https://doi.org/10.2316/Journal.206.2017.1.206-4624","url":null,"abstract":"State recognition in disconnecting switches is important during substation automation. Here, an effective computer vision-based automatic detection and state recognition method for disconnecting switches is proposed. Taking advantage of some important prior knowledge about a disconnecting switch, the method is designed using two important features of the fixed-contact facet of such disconnecting switches. First, the Histograms of Oriented Gradients (HOG) of the fixed-contact are used to design a Linear Discriminant Analysis (LDA) target detector to position the disconnecting switches and distinguish their loci against a usual cluttered background. Then a discriminative Norm Gradient Field (NGF) feature is used to train the Support Vector Machine (SVM) state classifier to discriminate disconnecting switch states. Finally, experimental results, compared with other methods, demonstrate that the proposed method is effective and achieves a low miss rate while delivering high performance in both precision and recall rate. In addition, the adopted approach is efficient and has the potential to work in practical substation automation scenarios.","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131945612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiple 3D Marker localization and tracking System in Image-Guided Radiotherapy","authors":"Songan Mao, Huanmei Wu, Minghui Lu, Chee-Wai Cheng","doi":"10.2316/Journal.206.2017.5.206-5027","DOIUrl":"https://doi.org/10.2316/Journal.206.2017.5.206-5027","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131341817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-18DOI: 10.2316/Journal.206.2016.2.206-4524
Feihu Sun, Junzhi Yu, Peng Zhao, De Xu
{"title":"Tracking control for a biomimetic robotic fish Guided by Active Vision","authors":"Feihu Sun, Junzhi Yu, Peng Zhao, De Xu","doi":"10.2316/Journal.206.2016.2.206-4524","DOIUrl":"https://doi.org/10.2316/Journal.206.2016.2.206-4524","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"71 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128242594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-03-01DOI: 10.2316/Journal.206.2016.4.206-4255
Yunfei Zhang, Weilin Li, C. D. Silva
This paper presents arobust Q-learning method for path planningin a dynamic environment. The method consists of three steps: first, a regime-switching Markov decision process (RSMDP) is formed to present the dynamic environment; second a probabilistic roadmap (PRM) is constructed, integrated with the RSMDP and stored as a graph whose nodes correspond to a collision-free world state for the robot; and third, an onlineQ-learning method with dynamic stepsize, which facilitates robust convergence of the Q-value iteration, is integrated with the PRM to determine an optimal path for reaching the goal. In this manner, the robot is able to use past experience for improving its performance in avoiding not only static obstacles but also moving obstacles, without knowing the nature of the obstacle motion. The use ofregime switching in the avoidance of obstacles with unknown motion is particularly innovative. The developed approach is applied to a homecare robot in computer simulation. The results show that the online path planner with Q-learning is able torapidly and successfully converge to the correct path.
{"title":"Rsmdp-Based robust Q-Learning for Optimal Path Planning in a Dynamic Environment","authors":"Yunfei Zhang, Weilin Li, C. D. Silva","doi":"10.2316/Journal.206.2016.4.206-4255","DOIUrl":"https://doi.org/10.2316/Journal.206.2016.4.206-4255","url":null,"abstract":"This paper presents arobust Q-learning method for path planningin a dynamic environment. The method consists of three steps: first, a regime-switching Markov decision process (RSMDP) is formed to present the dynamic environment; second a probabilistic roadmap (PRM) is constructed, integrated with the RSMDP and stored as a graph whose nodes correspond to a collision-free world state for the robot; and third, an onlineQ-learning method with dynamic stepsize, which facilitates robust convergence of the Q-value iteration, is integrated with the PRM to determine an optimal path for reaching the goal. In this manner, the robot is able to use past experience for improving its performance in avoiding not only static obstacles but also moving obstacles, without knowing the nature of the obstacle motion. The use ofregime switching in the avoidance of obstacles with unknown motion is particularly innovative. The developed approach is applied to a homecare robot in computer simulation. The results show that the online path planner with Q-learning is able torapidly and successfully converge to the correct path.","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130661937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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