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Distributed optimization for the multi-robot system using a neurodynamic approach
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DOI：10.1016/j.neucom.2019.08.032.png)
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摘要
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In this paper, we use a connected undirected graph to describe the multiple redundant manipulator system. An optimization model is formulated as a convex problem with coupled constraints. These constraints include equality constraints derived for path tracking, inequality constraints derived for obstacle avoidance, and convex sets built for joint physical limits. A novel distributed neurodynamics-based algorithm is developed for solving the complex problem in real time, so that there is no need for having a center coordinator in the multi-robot system. To verify the established model and the proposed algorithm, a dual-robot system is simulated to carry a rigid object following desired trajectories with obstacles considered. A more complex tri-robot system is simulated to perform as a supplementary evidence. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Distributed optimization
Multi-robot system
Trajectory tracking
Obstacle avoidance
Recurrent neural networks
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IF:
6.5
论文数:
2.5W
被引数:
6.5W
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