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Distributed k-WTA Network for Multi-Manipulator Competition With Experimental Verifications
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DOI：10.1049/cit2.70164.png)
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Abstract
En 中文
In this article, a new distributed 𝑘 k $k$-winner-take-all (D𝑘 k $k$-WTA) network is designed and used to construct a dynamic allocation scheme for competitive coordination tasks of multiple manipulators as embodied agents. The scheme is constructed based on the following two aspects. On one hand, with reference to a perspective that the Laplacian matrix is introduced into a 𝑘 k $k$-WTA network, a quadratic programming (QP) problem used for the competitive coordination of multiple manipulators is designed. Then, inspired by a noise-suppressing neural dynamics (NSND) method, a D𝑘 k $k$-WTA network is established by solving this QP problem. On the other hand, combined with the forward kinematics, a D𝑘 k $k$-WTA dynamic allocation scheme is constructed. In addition, theoretical analyses on the constructed scheme are conducted regarding convergence and robustness. Finally, for verification of the feasibility of the proposed D𝑘 k $k$-WTA network, simulations and experiments based on multiple manipulators for trajectory-tracking tasks are conducted. Notably, the proposed scheme has the potential to be extended to other embodied multi-agent systems.
Keywords:
k-winner-take-all (k-WTA) network
laplacian matrix
multiple-manipulator coordination
noise-suppressing neural dynamics (NSND)
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