A Behavior-based Adaptive Dynamic Programming Method for Multiple Mobile Manipulators Coordination Control
In this work, a behavior-based adaptive dynamic programming (BADP) method is proposed for coordination control of unmanned ground vehicle-manipulator systems (UGVMs). Through a null-space-based behavioral control (NSBC) framework, the multi-objective coordination control is transformed into a single...
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| Vydáno v: | International journal of control, automation, and systems Ročník 21; číslo 9; s. 3022 - 3035 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Bucheon / Seoul
Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers
01.09.2023
Springer Nature B.V 제어·로봇·시스템학회 |
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| ISSN: | 1598-6446, 2005-4092 |
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| Abstract | In this work, a behavior-based adaptive dynamic programming (BADP) method is proposed for coordination control of unmanned ground vehicle-manipulator systems (UGVMs). Through a null-space-based behavioral control (NSBC) framework, the multi-objective coordination control is transformed into a single-objective tracking control at the mission layer. Since cost functions and control constraints are simplified at control layer, the complexity of controller design is reduced. Then, an identifier-actor-critic reinforcement learning algorithm framework is introduced to learn the optimal control policy by balancing the control performance and consumption. Simulation results show that control costs are reduced around 13.5% per sampling period compared to existing multiple objective control methods. Finally, the BADP method is experimentally validated using four real UGVMs. |
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| AbstractList | In this work, a behavior-based adaptive dynamic programming (BADP) method is proposed for coordination control of unmanned ground vehicle-manipulator systems (UGVMs). Through a null-space-based behavioral control (NSBC) framework, the multi-objective coordination control is transformed into a single-objective tracking control at the mission layer. Since cost functions and control constraints are simplified at control layer, the complexity of controller design is reduced. Then, an identifier-actor-critic reinforcement learning algorithm framework is introduced to learn the optimal control policy by balancing the control performance and consumption. Simulation results show that control costs are reduced around 13.5% per sampling period compared to existing multiple objective control methods. Finally, the BADP method is experimentally validated using four real UGVMs. In this work, a behavior-based adaptive dynamic programming (BADP) method is proposed for the coordination control of unmanned ground vehicle-manipulator systems (UGVMs). Through a null-space-based behavioral control (NSBC) framework, the multi-objective coordination control is transformed into a single-objective tracking control at the mission layer. Since cost functions and control constraints are simplified at the control layer, the complexity of controller design is reduced. Then, an identifier-actor-critic reinforcement learning algorithm framework is introduced to learn the optimal control policy by balancing the control performance and consumption. Simulation results show that control costs are reduced by around 13.5% per sampling period compared to existing multiple objective control methods. Finally, the BADP method is experimentally validated using four real UGVMs. KCI Citation Count: 0 |
| Author | Chen, Jianfei Chen, Yutao Huang, Jie Zhang, Zhenyi Mo, Zhibin |
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| Cites_doi | 10.1109/TIE.2018.2884220 10.1007/s11432-018-9588-0 10.1109/TFUZZ.2017.2787561 10.1007/s41315-019-00090-7 10.1109/TSMC.2020.3042876 10.1109/ACCESS.2019.2925428 10.1177/0278364917719333 10.1002/rnc.5106 10.1016/j.automatica.2017.01.004 10.1109/TSMC.2020.3003797 10.1109/TIE.2016.2642880 10.1109/TIE.2019.2892669 10.1007/s10514-016-9590-0 10.1109/TRO.2009.2017135 10.1109/TAC.2018.2869462 10.1109/TRO.2008.921563 10.1016/j.isatra.2020.07.029 10.1109/JAS.2022.105797 10.1109/ACCESS.2019.2914669 10.1007/s12555-018-0871-6 10.1109/LCSYS.2020.2977927 10.1016/j.automatica.2015.01.015 10.1007/s12555-018-0690-9 10.1109/TASE.2018.2883343 10.1007/s12555-015-0116-x 10.1109/TIE.2017.2782229 10.23919/ACC.2019.8815335 10.23919/ChiCC.2018.8483276 |
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| Keywords | behavioral control Adaptive dynamic programming UGVMs multi-objective mission |
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| SubjectTerms | Adaptive control Algorithms Control Control methods Control systems design Controllers Coordination Cost function Design Dynamic programming Engineering Kinematics Machine learning Manipulators Mechatronics Methods Optimal control Optimization Pareto optimum Regular Papers Robot arms Robotics Tracking control Unmanned ground vehicles 제어계측공학 |
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| Title | A Behavior-based Adaptive Dynamic Programming Method for Multiple Mobile Manipulators Coordination Control |
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