Towards Efficient Motion Planning for UAVs: Lazy A* Search with Motion Primitives
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_ | 1866917834282500096 |
|---|---|
| author | Wang, Wentao Shen, Yi Chen, Kaiyang Lu, Kaifan |
| author_facet | Wang, Wentao Shen, Yi Chen, Kaiyang Lu, Kaifan |
| contents | Search-based motion planning algorithms have been widely utilized for unmanned aerial vehicles (UAVs). However, deploying these algorithms on real UAVs faces challenges due to limited onboard computational resources. The algorithms struggle to find solutions in high-dimensional search spaces and require considerable time to ensure that the trajectories are dynamically feasible. This paper incorporates the lazy search concept into search-based planning algorithms to address the critical issue of real-time planning for collision-free and dynamically feasible trajectories on UAVs. We demonstrate that the lazy search motion planning algorithm can efficiently find optimal trajectories and significantly improve computational efficiency. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_01230 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards Efficient Motion Planning for UAVs: Lazy A* Search with Motion Primitives Wang, Wentao Shen, Yi Chen, Kaiyang Lu, Kaifan Robotics Search-based motion planning algorithms have been widely utilized for unmanned aerial vehicles (UAVs). However, deploying these algorithms on real UAVs faces challenges due to limited onboard computational resources. The algorithms struggle to find solutions in high-dimensional search spaces and require considerable time to ensure that the trajectories are dynamically feasible. This paper incorporates the lazy search concept into search-based planning algorithms to address the critical issue of real-time planning for collision-free and dynamically feasible trajectories on UAVs. We demonstrate that the lazy search motion planning algorithm can efficiently find optimal trajectories and significantly improve computational efficiency. |
| title | Towards Efficient Motion Planning for UAVs: Lazy A* Search with Motion Primitives |
| topic | Robotics |
| url | https://arxiv.org/abs/2410.01230 |