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Jungwon Park, Junha Kim, Inkyu Jang, and H. Jin Kim

ICRA 2020 Multi-Robot Systems Award Finalist

Abstract: This paper presents a new efficient algorithm which guarantees a solution for a class of multi-agent trajectory planning problems in obstacle-dense environments. Our algorithm combines the advantages of both grid-based and optimization-based approaches, and generates safe, dynamically feasible trajectories without suffering from an erroneous optimization setup such as imposing infeasible collision constraints. We adopt a sequential optimization method with dummy agents to improve the scalability of the algorithm, and utilize the convex hull property of Bernstein and relative Bernstein polynomial to replace non-convex collision avoidance constraints to convex ones.


  title={Efficient multi-agent trajectory planning with feasibility guarantee using relative bernstein polynomial},
  author={Park, Jungwon and Kim, Junha and Jang, Inkyu and Kim, H Jin},
  booktitle={2020 IEEE International Conference on Robotics and Automation (ICRA)},