ClearPath: highly parallel collision avoidance for multi-agent simulation
University of North Carolina at Chapel Hill
In SCA ’09: Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation (2009), pp. 177-187
@conference{guy2009clearpath,
title={Clearpath: highly parallel collision avoidance for multi-agent simulation},
author={Guy, S. and others},
booktitle={Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation},
pages={177–187},
year={2009},
organization={ACM}
}
We present a new local collision avoidance algorithm between multiple agents for real-time simulations. Our approach extends the notion of velocity obstacles from robotics and formulates the conditions for collision free navigation as a quadratic optimization problem. We use a discrete optimization method to efficiently compute the motion of each agent. This resulting algorithm can be parallelized by exploiting data-parallelism and thread-level parallelism. The overall approach, ClearPath, is general and can robustly handle dense scenarios with tens or hundreds of thousands of heterogeneous agents in a few milli-seconds. As compared to prior collision avoidance algorithms, we observe more than an order of magnitude performance improvement.
January 8, 2011 by hgpu