KAUST Grant NumberKUS-C1-016-04
Permanent link to this recordhttp://hdl.handle.net/10754/597397
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AbstractProbabilistic roadmaps (PRMs) are a sampling-based approach to motion-planning that encodes feasible paths through the environment using a graph created from a subset of valid positions. Prior research has shown that PRMs can be augmented with useful information to model interesting scenarios related to multi-agent interaction and coordination. © 2012 IEEE.
CitationMahadevan A, Amato NM (2012) A sampling-based approach to probabilistic pursuit evasion. 2012 IEEE International Conference on Robotics and Automation. Available: http://dx.doi.org/10.1109/ICRA.2012.6225217.
SponsorsThis research supported in part by NSF awards CRI-0551685, CCF-0833199, CCF-0830753, IIS-096053, IIS-0917266 by THECB NHARPaward 000512-0097-2009, by Chevron, IBM, Intel, Oracle/Sun and byAward KUS-C1-016-04, made by King Abdullah University of Science andTechnology (KAUST).