<?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%">Ladd, A. M.</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%">Motion Planning in the Presence of Drift, Underactuation and Discrete System Changes</style></title><secondary-title><style face="normal" font="default" size="100%">Robotics: Science and Systems I</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%">2005</style></year><pub-dates><date><style  face="normal" font="default" size="100%">June</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.roboticsproceedings.org/rss01/p31.html</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">MIT Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Boston, MA</style></pub-location><pages><style face="normal" font="default" size="100%">233-241</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Motion planning research has been successful in
developing planning algorithms which are effective for solving
problems with complicated geometric and kinematic constraints.
Various applications in robotics and in other fields demand
additional physical realism. Some progress has been made for
non-holonomic systems. However systems with significant drift,
underactuation and discrete system changes remain challenging
for existing planning techniques particularly as the dimensionality
of the state space increases. In this paper, we demonstrate a
motion planning technique for the solution of problems with these
challenging characteristics. Our approach uses sampling-based
motion planning and subdivision methods. The problem that we
solve is a game that was chosen to exemplify characteristics
of dynamical systems that are difficult for planning. To our
knowledge, this is first application of algorithmic motion planning
to a problem of this type and complexity.</style></abstract><work-type><style face="normal" font="default" size="100%">inproceedings</style></work-type></record></records></xml>
