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

被引:1
作者
Bai, Yifan [1 ]
Kanellakis, Christoforos [1 ]
Nikolakopoulos, George [1 ]
机构
[1] Lulea Univ Technol, Robot & AI Team, Lulea, Sweden
来源
IFAC PAPERSONLINE | 2023年 / 56卷 / 02期
基金
欧盟地平线“2020”;
关键词
task assignment; multi-robot path-finding; multi-depot vehicle routing problem; COORDINATION; SEARCH; OPTIMIZATION;
D O I
10.1016/j.ifacol.2023.10.551
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:7032 / 7037
页数:6
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