Pub Date : 2013-08-01DOI: 10.2316/Journal.206.2013.1.206-3601
Chia-How Lin, K. Song
{"title":"An Interactive Control Architecture for Mobile robots","authors":"Chia-How Lin, K. Song","doi":"10.2316/Journal.206.2013.1.206-3601","DOIUrl":"https://doi.org/10.2316/Journal.206.2013.1.206-3601","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134609133","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 : 2012-07-23DOI: 10.2316/Journal.206.2012.3.206-3558
M. S. Erden, J. Jonkman
{"title":"Physical Human-robot Interaction by Observing actuator currents","authors":"M. S. Erden, J. Jonkman","doi":"10.2316/Journal.206.2012.3.206-3558","DOIUrl":"https://doi.org/10.2316/Journal.206.2012.3.206-3558","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124642727","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 : 2012-05-01DOI: 10.2316/Journal.206.2012.2.206-3498
Yan Zhuang, Ke Wang, Wei Wang, Huosheng Hu
This paper presents a hybrid sensing system for mobile robot localization in large-scale indoor environments. The system operates in two sensing modes, either omni-directional vision or laser scanning, according to the environmental characteristics. For a structured corridor environment, the vision information is adopted to track the robot pose with a predefined hybrid metric-topological map. For a semi-structured office room, the laser scanning mode is chosen to generate a sequence of relative pose transformations based on a scan matching algorithm. Kalman filters are deployed to smooth multiple scan matching results. The proposed hybrid sensing system can perform localization tasks on-the-fly, with the features of efficient map modelling and computational simplicity. Experimental results are provided to demonstrate the performance and effectiveness of the proposed techniques.
{"title":"A Hybrid Sensing Approach to Mobile Robot Localization in Complex Indoor Environments","authors":"Yan Zhuang, Ke Wang, Wei Wang, Huosheng Hu","doi":"10.2316/Journal.206.2012.2.206-3498","DOIUrl":"https://doi.org/10.2316/Journal.206.2012.2.206-3498","url":null,"abstract":"This paper presents a hybrid sensing system for mobile robot localization in large-scale indoor environments. The system operates in two sensing modes, either omni-directional vision or laser scanning, according to the environmental characteristics. For a structured corridor environment, the vision information is adopted to track the robot pose with a predefined hybrid metric-topological map. For a semi-structured office room, the laser scanning mode is chosen to generate a sequence of relative pose transformations based on a scan matching algorithm. Kalman filters are deployed to smooth multiple scan matching results. The proposed hybrid sensing system can perform localization tasks on-the-fly, with the features of efficient map modelling and computational simplicity. Experimental results are provided to demonstrate the performance and effectiveness of the proposed techniques.","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114674029","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 : 2011-12-28DOI: 10.2316/Journal.206.2011.4.206-3510
P. Wu, Chung-Shu Liao, W. Chieng
{"title":"Optimization Setting of Dynamics parameters for an ATV Simulator","authors":"P. Wu, Chung-Shu Liao, W. Chieng","doi":"10.2316/Journal.206.2011.4.206-3510","DOIUrl":"https://doi.org/10.2316/Journal.206.2011.4.206-3510","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114950343","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 : 2011-06-07DOI: 10.2316/Journal.206.2011.1.206-3399
O. Kuljaca, J. Gadewadikar, R. Selmic
{"title":"Adaptive Neural Network Frequency Control for Thermopower Generators Power System","authors":"O. Kuljaca, J. Gadewadikar, R. Selmic","doi":"10.2316/Journal.206.2011.1.206-3399","DOIUrl":"https://doi.org/10.2316/Journal.206.2011.1.206-3399","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116453244","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 : 2010-12-01DOI: 10.2316/Journal.206.2010.4.206-3372
Ming-Shaung Chang, Jung-Hua Chou
{"title":"A Novel Machine Vision-Based Mobile Robot Navigation System in an Unknown Environment","authors":"Ming-Shaung Chang, Jung-Hua Chou","doi":"10.2316/Journal.206.2010.4.206-3372","DOIUrl":"https://doi.org/10.2316/Journal.206.2010.4.206-3372","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121385517","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 : 2009-12-01DOI: 10.2316/JOURNAL.206.2009.3.206-3273
Dongbing Gu, Huosheng Hu
This paper presents a distributed particle filter (DPF) over sensor networks. We propose two major steps to make a particle filter to work in a distributed way. The first step is the estimation of global mean and covariance of weighted particles by using an average consensus filter. Through this consensus filter, each sensor node can gradually diffuse its local mean and covariance of weighted particles over the entire network and asymptotically obtain the estimated global mean and covariance. The second step is the propagation of the estimated global mean and covariance through state transition distribution and likelihood distribution by using an unscented transformation (UT). Through this transformation, partial high order information of the estimated global mean and covariance can be incorporated into the estimates for non-linear models. Simulations of tracking tasks in a sensor network with 100 sensor nodes are given.
{"title":"Target Tracking by Using Particle Filter in Sensor Networks","authors":"Dongbing Gu, Huosheng Hu","doi":"10.2316/JOURNAL.206.2009.3.206-3273","DOIUrl":"https://doi.org/10.2316/JOURNAL.206.2009.3.206-3273","url":null,"abstract":"This paper presents a distributed particle filter (DPF) over sensor networks. We propose two major steps to make a particle filter to work in a distributed way. The first step is the estimation of global mean and covariance of weighted particles by using an average consensus filter. Through this consensus filter, each sensor node can gradually diffuse its local mean and covariance of weighted particles over the entire network and asymptotically obtain the estimated global mean and covariance. The second step is the propagation of the estimated global mean and covariance through state transition distribution and likelihood distribution by using an unscented transformation (UT). Through this transformation, partial high order information of the estimated global mean and covariance can be incorporated into the estimates for non-linear models. Simulations of tracking tasks in a sensor network with 100 sensor nodes are given.","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123897155","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 : 2009-12-01DOI: 10.2316/JOURNAL.206.2009.2.206-3235
Joo H. Kim, Y. Xiang, R. Bhatt, Jingzhou Yang, Hyun-Joon Chung, J. Arora, K. Abdel-Malek
{"title":"Generating Effective Whole-Body Motions of a Human-like Mechanism with Efficient ZMP Formulation","authors":"Joo H. Kim, Y. Xiang, R. Bhatt, Jingzhou Yang, Hyun-Joon Chung, J. Arora, K. Abdel-Malek","doi":"10.2316/JOURNAL.206.2009.2.206-3235","DOIUrl":"https://doi.org/10.2316/JOURNAL.206.2009.2.206-3235","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"133 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120927349","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 : 2008-12-08DOI: 10.2316/Journal.206.2008.3.206-3065
Ralf Gomm, Vivek Bhaskar, S. Cetinkunt
{"title":"Automated Real-Time Motion Planning and Control of Construction Equipment Mechanism","authors":"Ralf Gomm, Vivek Bhaskar, S. Cetinkunt","doi":"10.2316/Journal.206.2008.3.206-3065","DOIUrl":"https://doi.org/10.2316/Journal.206.2008.3.206-3065","url":null,"abstract":"","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126824898","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 : 2008-03-01DOI: 10.2316/Journal.206.2008.2.206-3123
F. Belkhouche, B. Belkhouche
The problem of collision course between a mobile robot and a moving object is modeled in polar coordinates using the kinematics equations. A model of the relative motion of the moving object as seen by the robot is then derived. This model consists of the relative velocities along and across the visibility line, and gives the range rate and the turning rate of the moving object with respect to the robot. The conditions for the collision course are derived in terms of the robot's and the moving object's states. We define two types of collision course: the exact collision course and the weak collision course. The exact collision course always results in a collision, and is clearly characterized by a given set of equations. The weak collision course may become an exact collision course near collision and allows an early detection of the collision course in various scenarios. Several examples and scenarios illustrating the theory are shown using simulation.
{"title":"Kinematics-Based Characterization of the Collision Course","authors":"F. Belkhouche, B. Belkhouche","doi":"10.2316/Journal.206.2008.2.206-3123","DOIUrl":"https://doi.org/10.2316/Journal.206.2008.2.206-3123","url":null,"abstract":"The problem of collision course between a mobile robot and a moving object is modeled in polar coordinates using the kinematics equations. A model of the relative motion of the moving object as seen by the robot is then derived. This model consists of the relative velocities along and across the visibility line, and gives the range rate and the turning rate of the moving object with respect to the robot. The conditions for the collision course are derived in terms of the robot's and the moving object's states. We define two types of collision course: the exact collision course and the weak collision course. The exact collision course always results in a collision, and is clearly characterized by a given set of equations. The weak collision course may become an exact collision course near collision and allows an early detection of the collision course in various scenarios. Several examples and scenarios illustrating the theory are shown using simulation.","PeriodicalId":206015,"journal":{"name":"Int. J. Robotics Autom.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133268513","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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