<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Konstantinos I. Tsianos</style></author><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%">Sampling-based robot motion planning: Towards realistic applications</style></title><secondary-title><style face="normal" font="default" size="100%">Computer Science Review</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">kavrakilab</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year><pub-dates><date><style  face="normal" font="default" size="100%">August</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">1</style></volume><pages><style face="normal" font="default" size="100%">2--11</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">This paper presents some of the recent improvements in sampling-based robot motion planning. Emphasis is placed on work that brings motion-planning algorithms closer to applicability in real environments. Methods that approach increasingly difficult motion planning problems including kinodynamic motion planning and dynamic environments are discussed. The ultimate goal for such methods is to generate plans that can be executed with few modifications in a real robotics mobile platform.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><work-type><style face="normal" font="default" size="100%">article</style></work-type></record></records></xml>
