Multi-robot Task Allocation and Path Planning with Maximum Range Constraints
<|reference_start|>Multi-robot Task Allocation and Path Planning with Maximum Range Constraints: This letter presents a novel multi-robot task allocation and path planning method that considers robots' maximum range constraints in large-sized workspaces, enabling robots to complete the assigned tasks within their range limits. Firstly, we developed a fast path planner to solve global paths efficiently. Subsequently, we propose an innovative auction-based approach that integrates our path planner into the auction phase for reward computation while considering the robots' range limits. This method accounts for extra obstacle-avoiding travel distances rather than ideal straight-line distances, resolving the coupling between task allocation and path planning. Additionally, to avoid redundant computations during iterations, we implemented a lazy auction strategy to speed up the convergence of the task allocation. Finally, we validated the proposed method's effectiveness and application potential through extensive simulation and real-world experiments. The implementation code for our method will be available at https://github.com/wuuya1/RangeTAP.<|reference_end|>
@article{xu2024multi-robot,
    title={Multi-robot Task Allocation and Path Planning with Maximum Range
  Constraints},
    author={Gang Xu, Yuchen Wu, Sheng Tao, Yifan Yang, Tao Liu, Tao Huang, Huifeng
  Wu, and Yong Liu},
    journal={arXiv preprint arXiv:2409.06531},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.06531},
    primaryClass={cs.RO}
}