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Robotic Task Sequencing and Motion Coordination for Multiarm Systems

2022; Institute of Electrical and Electronics Engineers; Volume: 27; Issue: 6 Linguagem: Inglês

10.1109/tmech.2022.3178019

1941-014X

Cuebong Wong, Stephen Shackleford, Darren Potter, John-Patrick Richardson, Lorraine McDermott, Jon Nolan,

Robotic Mechanisms and Dynamics

Until now, the robotic task sequencing problem (RTSP) has largely been considered from the viewpoint of a single robotic arm. However, several benefits can be derived from the extension of the problem to multiarm systems. This article presents a modular approach toward solving multiarm RTSPs, validated through simulated and physical trials involving a dual-arm setup. The proposed approach extends the Cluster-RTSP algorithm to efficiently address task allocation, configuration selection, and task sequencing subproblems. Three methods for solving the subsequent motion coordination subproblem are investigated to explore the strengths and drawbacks of each strategy for resolving motion conflict between multiple robots. The method is evaluated against a state-of-the-art baseline, where it is shown that the proposed planning pipeline excels in finding high-quality solutions within competitive planning times for RTSPs involving redundant robots and tasks comprising several hundred to thousands of points.