Adaptive event-triggered control for uncalibrated visual servoing of robot manipulators |
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| Institution: | 1. Guangdong University of Technology, Guangzhou, Guangdong 510006, China;2. University of Electronic Science and Technology of China Zhongshan Institute, Zhongshan, Guangdong 528402, China;3. Guangdong Basic and Applied Basic Research Foundation, Guangzhou, Guangdong 510033, China;1. Key Laboratory of Intelligent Analysis and Decision on Complex Systems, School of Science, Chongqing University of Posts and Telecommunications, Chongqing, PR China;2. Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing, College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, PR China;3. Department of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam, Germany;4. Institute of Physics, Humboldt University of Berlin, Berlin, Germany;1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, PR China;2. School of Automation, Nanjing University of Science and Technology, Nanjing 210094, PR China;1. LAJ Laboratory, University of Jijel, Algeria;2. Université Paris-Saclay, Univ Evry, IBISC, Evry 91020, France;1. Department of Intelligent Mechatronics Engineering and Convergence Engineering for Intelligent Drone, Sejong University, Seoul 05006, South Korea;2. Department of Mathematics and Algorithms Research, Nokia Bell Labs, Murray Hill NJ 07974, USA |
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| Abstract: | In the study, an adaptive event-triggered control strategy is proposed for image-based visual servoing of eye-to-hand robot manipulators, where the camera used does not need to be calibrated, and the dynamics behavior of manipulator is considered in design and analysis. To address the uncertainty in camera parameters and the nonlinearity in robot dynamics, and accommodate the errors between the real-time control signals and the piecewise-constant event-triggered control signals, a new and novel robust adaptive estimation approach is developed, and well fused with visual feedback control design so that the boundedness of all closed-loop signals, and the asymptotic convergence of image error towards zero are established simultaneously. Besides rigorous proof in theory, the obtained results are also confirmed by comparative simulation tests. |
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