Reciprocally-rotating Velocity Obstacles
Abstract
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.
Subject
Multi-agent systemsLocal Collision Avoidance
Autonomous Agents
Crowd Simulation
Velocity Obstacles
Citation
Giese, Andrew W (2014). Reciprocally-rotating Velocity Obstacles. Master's thesis, Texas A & M University. Available electronically from https : / /hdl .handle .net /1969 .1 /152671.