Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/76825
Title: Cooperative motion generation in a distributed network of redundant robot manipulators with noises
Authors: Jin, L
Li, S 
Xiao, L
Lu, R
Liao, B
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on systems, man, and cybernetics. Systems, 2017 (article in press) How to cite?
Journal: IEEE transactions on systems, man, and cybernetics. Systems 
Abstract: In this paper, a distributed scheme is proposed for the cooperative motion generation in a distributed network of multiple redundant manipulators. The proposed scheme can simultaneously achieve the specified primary task to reach global cooperation under limited communications among manipulators and optimality in terms of a specified optimization index of redundant robot manipulators. The proposed distributed scheme is reformulated as a quadratic program (QP). To inherently suppress noises originating from communication interferences or computational errors, a noise-tolerant zeroing neural network (NTZNN) is constructed to solve the QP problem online. Then, theoretical analyses show that, without noise, the proposed distributed scheme is able to execute a given task with exponentially convergent position errors. Moreover, in the presence of noise, the proposed distributed scheme with the aid of NTZNN model has a satisfactory performance. Furthermore, simulations and comparisons based on PUMA560 redundant robot manipulators substantiate the effectiveness and accuracy of the proposed distributed scheme with the aid of NTZNN model.
URI: http://hdl.handle.net/10397/76825
ISSN: 2168-2216
EISSN: 2168-2232
DOI: 10.1109/TSMC.2017.2693400
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