<?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%">Plaku, E.</style></author><author><style face="normal" font="default" size="100%">L. E. Kavraki</style></author><author><style face="normal" font="default" size="100%">Moshe Y. Vardi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Motion Planner for a Hybrid Robotic System with Kinodynamic Constraints</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE International Conference on Robotics and Automation (ICRA)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">hybrid systems</style></keyword><keyword><style  face="normal" font="default" size="100%">HyDICE</style></keyword><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%">path planning; multi-layered synergistic planning</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><pub-location><style face="normal" font="default" size="100%">Rome, Italy</style></pub-location><pages><style face="normal" font="default" size="100%">692--697</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The rapidly increasing complexity of tasks robotic systems are
               expected to carry out underscores the need for the development of
               motion planners that can take into account discrete changes in the
               continuous motions of the system. Completion of tasks such as
               exploration of unknown or hazardous environments often requires
               discrete changes in the controls and motions of the robot in order to
               adapt to different terrains or maintain operability during partial
               failures or other mishaps.
               The contribution of this work toward this objective is the development
               of an efficient motion planner for a hybrid robotic system. The
               controls and motion equations of the robot could change discretely in
               order to enable the robot to operate in different terrains. The
               framework in this paper blends discrete searching with sampling-based
               motion planning for continuous state spaces and is well-suited for
               robotic systems modeled as hybrid systems with numerous discrete modes
               and transitions. This multi-layered approach offers considerable
               improvements over existing methods addressing similar problems, as
               indicated by the experimental results.
               </style></abstract><work-type><style face="normal" font="default" size="100%">inproceedings</style></work-type></record></records></xml>
