Reciprocally-Rotating Velocity Obstacles Conference Paper

abstract

• 2014 IEEE. Modern multi-agent systems frequently use highlevel 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 Collision Avoidance (ORCA). Despite being fast and efficient for circular-shaped agents, ORCA may deadlock when polygonal shapes are used. To address this shortcoming, we introduce Reciprocally-Rotating Velocity Obstacles (RRVO). RRVO generalizes ORCA by introducing a notion of rotation for polygonally-shaped agents. This generalization permits more realistic motion than ORCA and does not suffer from as much deadlock. In this paper, we present the theory of RRVO and show empirically that it does not suffer from the deadlock issue ORCA has, permits agents to reach goals faster, and has a comparable collision rate at the cost of performance overhead quadratic in the (typically small) user-defined parameter .

name of conference

• 2014 IEEE International Conference on Robotics and Automation (ICRA)

authors

• Amato, Nancy

published proceedings

• 2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)

author list (cited authors)

• Giese, A., Latypov, D., & Amato, N. M.

citation count

• 20

complete list of authors

• Giese, Andrew||Latypov, Daniel||Amato, Nancy M

publication date

• May 2014

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE International Conference on Robotics and Automation  Journal

keywords

• Autonomous Agents
• Crowd Simulation
• Local Collision Avoidance
• Multi-agent Systems
• Velocity Obstacles

Digital Object Identifier (DOI)

• 10.1109/icra.2014.6907324

URI

• https://hdl.handle.net/1969.1/152671

start page

• 3234

end page

• 3241

URL

• http://dx.doi.org/10.1109/icra.2014.6907324