<?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%">Jonathan F. Kruse</style></author><author><style face="normal" font="default" size="100%">Mark Yim</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 with Hardware Demonstrations</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE/RSJ International Conference on Intelligent Robots and Systems</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%">modular robots</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><pub-location><style face="normal" font="default" size="100%">Nice, France</style></pub-location><pages><style face="normal" font="default" size="100%">1661--1666</style></pages><abstract><style face="normal" font="default" size="100%">  This paper provides proof-of-concept that state-of-the-art
  sampling-based motion planners that are tightly integrated with a
  physics-based simulator can compute paths that can be executed by a
  physical robotic system. Such a goal has been the subject of
  intensive research during the last few years and reflects the desire
  of the motion planning community to produce paths that are directly
  relevant to realistic mechanical systems and do not need a huge
  post-processing step in order to be executed on a robotic
  platform. To evaluate this approach, a recently developed motion
  planner is used to compute paths for a modular robot constructed
  from seven modules. These paths are then executed on hardware and
  compared with the paths predicted by the planner.  For the system
  considered, the planner prediction and the paths achieved by the
  physical robot match, up to small errors. This work reveals the
  potential of modern motion planning research and its implications in
  the design and operation of complex robotic platforms.</style></abstract></record></records></xml>
