Multi-robot Task Allocation and Path Planning with Maximum Range Constraints
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917772394496000 |
|---|---|
| author | Xu, Gang Wu, Yuchen Tao, Sheng Yang, Yifan Liu, Tao Huang, Tao Wu, Huifeng Liu, Yong |
| author_facet | Xu, Gang Wu, Yuchen Tao, Sheng Yang, Yifan Liu, Tao Huang, Tao Wu, Huifeng Liu, Yong |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_06531 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multi-robot Task Allocation and Path Planning with Maximum Range Constraints Xu, Gang Wu, Yuchen Tao, Sheng Yang, Yifan Liu, Tao Huang, Tao Wu, Huifeng Liu, Yong Robotics 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. |
| title | Multi-robot Task Allocation and Path Planning with Maximum Range Constraints |
| topic | Robotics |
| url | https://arxiv.org/abs/2409.06531 |