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SA-reCBS: Multi-robot task assignment with integrated reactive path generation

Yifan Bai, Christoforos Kanellakis, George Nikolakopoulos

Year
2023
Citations
5

Abstract

In this paper, we study the multi-robot task assignment and path-finding problem (MRTAPF), where a number of robots are required to visit all given tasks while avoiding collisions with each other. We propose a novel two-layer algorithm SA-reCBS that cascades the simulated annealing algorithm and conflict-based search to solve this problem. Compared to other approaches in the field of MRTAPF, the advantage of SA-reCBS is that without requiring a pre-bundle of tasks to groups with the same number of groups as the number of robots, it enables a part of robots needed to visit all tasks in collision-free paths. We test the algorithm in various simulation instances and compare it with state-of-the-art algorithms. The result shows that SA-reCBS has a better performance with a higher success rate, less computational time, and better objective values.

Keywords

RobotSimulated annealingComputer scienceTask (project management)Path (computing)AlgorithmArtificial intelligenceMathematical optimizationMathematicsEngineering

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