Efficient Global Trajectory Planning for Multi-robot System with Affinely Deformable Formation

Global trajectory planning is crucial for long-range formation navigation tasks of multi-robot systems in efficiency improvement and energy saving, whose main challenges are the joint space constraints of the whole team and the long-range deployment. To overcome the above difficulties, we reformulate the original problem into an affine formation planning problem in parameter space. Further, we propose a front-end & back-end framework for global trajectory planning of Multi-Robot Systems (MRS) with affinely deformable formation. For the front-end, an RL-steering affine formation RRT* method is designed to search a global formation-level trajectory in affine parameter space, combining the efficient BVP-solving capability of RL and the global guidance and generalizing ability of RRT*. For the back-end, we propose a formationlevel affine parameter trajectory optimization method to refine the front-end trajectory, and further transform it into peragent trajectories for execution. Extensive benchmarks and ablation experiments in simulation show the effectiveness of our framework for the global trajectory generation of a multiUAV system with affinely deformable formation. The appendix can be seen here<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup>.

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Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10802518
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.25

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article

Efficient Global Trajectory Planning for Multi-robot System with Affinely Deformable Formation

Rong Xiong, Jun Wu, Yuxiang Cui, Dongkun Zhang et al.
1 citations
Robotic Path Planning Algorithms
0.25
article

Efficient Global Trajectory Planning for Multi-robot System with Affinely Deformable Formation

Rong Xiong, Jun Wu, Yuxiang Cui, Dongkun Zhang, Hao Sha, Yue Wang, Chaoqun Wang, Wangtao Lu
article en
1 citations

Abstract

Global trajectory planning is crucial for long-range formation navigation tasks of multi-robot systems in efficiency improvement and energy saving, whose main challenges are the joint space constraints of the whole team and the long-range deployment. To overcome the above difficulties, we reformulate the original problem into an affine formation planning problem in parameter space. Further, we propose a front-end & back-end framework for global trajectory planning of Multi-Robot Systems (MRS) with affinely deformable formation. For the front-end, an RL-steering affine formation RRT* method is designed to search a global formation-level trajectory in affine parameter space, combining the efficient BVP-solving capability of RL and the global guidance and generalizing ability of RRT*. For the back-end, we propose a formationlevel affine parameter trajectory optimization method to refine the front-end trajectory, and further transform it into peragent trajectories for execution. Extensive benchmarks and ablation experiments in simulation show the effectiveness of our framework for the global trajectory generation of a multiUAV system with affinely deformable formation. The appendix can be seen here<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup>.

Shandong University (CN), Zhejiang University of Technology (CN)
Nature
Sustainable cities and communities
Openalex Percentile: Top 43%
Robotic Path Planning Algorithms
0.25
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Efficient Global Trajectory Planning for Multi-robot System with Affinely Deformable Formation — Rong Xiong, Jun Wu, et al. · (2024) | TGRS Research Map | TGRS