<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ioan Alexandru Sucan</style></author><author><style face="normal" font="default" size="100%">L. E. Kavraki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Kinodynamic Motion Planning by Interior-Exterior Cell Exploration</style></title><secondary-title><style face="normal" font="default" size="100%">Algorithmic Foundation of Robotics VIII (Proceedings of Workshop on the Algorithmic Foundations of Robotics)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">kavrakilab</style></keyword><keyword><style  face="normal" font="default" size="100%">kinodynamic/physics-based motion planning</style></keyword><keyword><style  face="normal" font="default" size="100%">project_KPIECE</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2009</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.springerlink.com/content/gm47pt40p0740125/</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">STAR</style></publisher><pub-location><style face="normal" font="default" size="100%">Guanajuato, Mexico</style></pub-location><volume><style face="normal" font="default" size="100%">57</style></volume><pages><style face="normal" font="default" size="100%">449-464</style></pages><abstract><style face="normal" font="default" size="100%">  This paper presents a kinodynamic motion planner, Kinodynamic Motion
  Planning by Interior-Exterior Cell Exploration (KPIECE),
  specifically designed for systems with complex dynamics, where
  physics-based simulation is necessary. A multiple-level grid-based
  discretization is used to estimate the coverage of the state
  space. The coverage estimates help the planner detect the less
  explored areas of the state space. The planner also keeps track of
  the boundary of the explored region of the state space and focuses
  exploration on the less covered parts of this boundary. Extensive
  experiments show KPIECE provides computational gain over
  state-of-the-art methods and allows solving some harder, previously
  unsolvable problems. A shared memory parallel implementation is
  presented as well. This implementation provides better speedup than
  an embarrassingly parallel implementation by taking advantage of the
  evolving multi-core technology.</style></abstract></record></records></xml>
