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Well-Connected Set and Its Application to Multi-Robot Path Planning

Teng Guo, Jingjin Yu

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Abstract

Parking lots and autonomous warehouses for accommodating many vehicles/robots adopt designs in which the underlying graphs are well-connected to simplify planning and reduce congestion. In this study, we formulate and delve into the largest well-connected set (LWCS) problem and explore its applications in layout design for multi-robot path planning. Roughly speaking, a well-connected set over a connected graph is a set of vertices such that there is a path on the graph connecting any pair of vertices in the set without passing through any additional vertices of the set. Identifying an LWCS has many potential high-utility applications, e.g., for determining parking garage layout and capacity, as prioritized planning can be shown to be complete when start/goal configurations belong to an LWCS. In this work, we establish that computing an LWCS is NP-complete. We further develop optimal and near-optimal LWCS algorithms, with the near-optimal algorithm targeting large maps. A complete prioritized planning method is given for planning paths for multiple robots residing on an LWCS.

Index terms

Planning Scheduling and Coordination Multi-Robot Systems Path Planning for Multiple Mobile Robots or Agents