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dc.contributor.authorGuyy, Stephen. J.en_US
dc.contributor.authorChhugani, Jatinen_US
dc.contributor.authorKim, Changkyuen_US
dc.contributor.authorSatish, Nadathuren_US
dc.contributor.authorLin, Mingen_US
dc.contributor.authorManocha, Dineshen_US
dc.contributor.authorDubey, Pradeepen_US
dc.contributor.editorEitan Grinspun and Jessica Hodginsen_US
dc.date.accessioned2016-02-18T11:50:49Z
dc.date.available2016-02-18T11:50:49Z
dc.date.issued2009en_US
dc.identifier.isbn978-1-60558-610-6en_US
dc.identifier.issn1727-5288en_US
dc.identifier.urihttp://dx.doi.org/10.1145/1599470.1599494en_US
dc.description.abstractWe 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.en_US
dc.publisherACM SIGGRAPH / Eurographics Associationen_US
dc.titleClearPath: Highly Parallel Collision Avoidance for Multi-Agent Simulationen_US
dc.description.seriesinformationEurographics/ ACM SIGGRAPH Symposium on Computer Animationen_US
dc.description.sectionheadersCrowdsen_US
dc.identifier.doi10.1145/1599470.1599494en_US
dc.identifier.pages177-188en_US


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