Reciprocally-rotating Velocity Obstacles



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Modern multi-agent systems frequently use high-level planners to extract basic

paths for agents, and then rely on local collision avoidance to ensure that the agents reach
their destinations without colliding with one another or dynamic obstacles. One state-of-the-art local collision avoidance technique is Optimal Reciprocal Colli- sion Avoidance (ORCA). Despite being fast and efficient for circular-shaped agents, ORCA may deadlock when polygonal shapes are used. To address this shortcom- ing, we introduce Reciprocally-Rotating Velocity Obstacles (RRVO). RRVO extends ORCA by introducing a notion of rotation. This
extension permits more realistic motion than ORCA for polygonally-shaped agents and does not suffer from as much deadlock. In this thesis, we present the theory of RRVO and show empirically that it does not suffer from the deadlock issue ORCA has, that it permits agents to reach goals faster, and that it has a comparable collision rate at the cost of some performance overhead.