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Conference Paper: Real-time optimization-based planning in dynamic environments using GPUs

TitleReal-time optimization-based planning in dynamic environments using GPUs
Authors
Park, ChonhyonPan, JiaManocha, Dinesh
Issue Date2013
Citation
Proceedings - IEEE International Conference on Robotics and Automation, 2013, p. 4090-4097 How to Cite?
DOI: http://dx.doi.org/10.1109/ICRA.2013.6631154
AbstractWe present a novel algorithm to compute collision-free trajectories in dynamic environments. Our approach is general and does not require a priori knowledge about the obstacles or their motion. We use a replanning framework that interleaves optimization-based planning with execution. Furthermore, we describe a parallel formulation that exploits a high number of cores on commodity graphics processors (GPUs) to compute a high-quality path in a given time interval. We derive bounds on how parallelization can improve the responsiveness of the planner and the quality of the trajectory. © 2013 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/206222
ISSN
1050-4729
2023 SCImago Journal Rankings: 1.620

 

DC FieldValueLanguage
dc.contributor.authorPark, Chonhyon-
dc.contributor.authorPan, Jia-
dc.contributor.authorManocha, Dinesh-
dc.date.accessioned2014-10-22T01:25:29Z-
dc.date.available2014-10-22T01:25:29Z-
dc.date.issued2013-
dc.identifier.citationProceedings - IEEE International Conference on Robotics and Automation, 2013, p. 4090-4097-
dc.identifier.issn1050-4729-
dc.identifier.urihttp://hdl.handle.net/10722/206222-
dc.description.abstractWe present a novel algorithm to compute collision-free trajectories in dynamic environments. Our approach is general and does not require a priori knowledge about the obstacles or their motion. We use a replanning framework that interleaves optimization-based planning with execution. Furthermore, we describe a parallel formulation that exploits a high number of cores on commodity graphics processors (GPUs) to compute a high-quality path in a given time interval. We derive bounds on how parallelization can improve the responsiveness of the planner and the quality of the trajectory. © 2013 IEEE.-
dc.languageeng-
dc.relation.ispartofProceedings - IEEE International Conference on Robotics and Automation-
dc.titleReal-time optimization-based planning in dynamic environments using GPUs-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICRA.2013.6631154-
dc.identifier.scopuseid_2-s2.0-84887269503-
dc.identifier.spage4090-
dc.identifier.epage4097-
dc.identifier.issnl1050-4729-

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