Real-time cooperative kinematic control for multiple robots in distributed scenarios with dynamic neural networks

被引：7
|
作者：
Liu, Mei [1 ,2 ]
Zhang, Jiazheng [1 ,2 ]
Shang, Mingsheng [1 ,2 ]
机构：
[1] Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing Key Lab Big Data & Intelligent Comp, Chongqing 400714, Peoples R China
[2] Univ Chinese Acad Sci, Chongqing Sch, Chongqing 400714, Peoples R China
来源：
NEUROCOMPUTING | 2022年 / 491卷
关键词：
Multiple redundant manipulators; Cooperative control; Motion planning; Dynamic neural network; TRACKING; MANIPULATORS; COORDINATION;
D O I：
10.1016/j.neucom.2021.12.038
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This work investigates the real-time cooperative kinematic control for multiple robots in distributed sce-narios. The information interaction among robots is described as a directed topology in which each robotic manipulator is connected to specified nodes. Besides, a performance index of minimum joint velocity norm is introduced to regulate the robots' motion. Combining with the performance index and integrating the related constraints, a control scheme is developed to guide the behavior of robots with an error feedback term leveraged to improve the real-time execution accuracy of tasks. Moreover, considering that the involved parameters are time-dependent, a dynamic neural-network-assisted solver is constructed to solve the control scheme online. In the end, simulations and illustrative experiments on the virtual robot experiment platform (V-REP) are conducted by a set of UR5 robots to execute tasks in a switchable directed topology, where the corresponding results demonstrate the effectiveness of the pro-posed scheme. (c) 2021 Elsevier B.V. All rights reserved.
引用
收藏
页码：621 / 632
页数：12
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