Hypergraph-based Multi-robot Motion Planning with Topological Guidance.
CoRR(2023)
摘要
We present a multi-robot motion planning algorithm that efficiently finds
paths for robot teams up to ten times larger than existing methods in congested
settings with narrow passages in the environment. Narrow passages represent a
source of difficulty for sampling-based motion planning algorithms. This
problem is exacerbated for multi-robot systems where the planner must also
avoid inter-robot collisions within these congested spaces, requiring
coordination. Topological guidance, which leverages information about the
robot's environment, has been shown to improve performance for mobile robot
motion planning in single robot scenarios with narrow passages. Additionally,
our prior work has explored using topological guidance in multi-robot settings
where a high degree of coordination is required of the full robot group. This
high level of coordination, however, is not always necessary and results in
excessive computational overhead for large groups. Here, we propose a novel
multi-robot motion planning method that leverages topological guidance to
inform the planner when coordination between robots is necessary, leading to a
significant improvement in scalability.
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