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<XML><RECORDS>
<RECORD>
	<REFERENCE_TYPE>3</REFERENCE_TYPE>
	<AUTHORS>
		<AUTHOR>Bekris, K. E.</AUTHOR>
		<AUTHOR>Kavraki, L. E.</AUTHOR>
	</AUTHORS>
	<YEAR>2007</YEAR>
	<TITLE>Greedy but Safe Replanning under Kinodynamic Constraints</TITLE>
	<SECONDARY_TITLE>Intl. Conf. on Robotics and Automation</SECONDARY_TITLE>
	<PLACE_PUBLISHED>Rome, Italy</PLACE_PUBLISHED>
	<PUBLISHER>IEEE press</PUBLISHER>
	<PAGES>704-710</PAGES>
	<DATE>April</DATE>
	<KEYWORDS>
		<KEYWORD>grip</KEYWORD>
		<KEYWORD>replanning</KEYWORD>
	</KEYWORDS>
	<ABSTRACT>We consider motion planning problems for a vehicle with
               kinodynamic constraints, where there is partial
               knowledge about the environment and replanning is
               required. We present a new tree-based planner that
               explicitly deals with kinodynamic constraints and
               addresses the safety issues when planning under finite
               computation times, meaning that the vehicle avoids
               collisions in its evolving configuration space. In
               order to achieve good performance we incrementally
               update a tree data-structure by retaining information
               from previous steps and we bias the search of the
               planner with a greedy, yet probabilistically complete
               state space exploration strategy. Moreover, the number
               of collision checks required to guarantee safety is
               kept to a minimum.  We compare our technique with
               alternative approaches as a standalone planner and show
               that it achieves favorable performance when planning
               with dynamics.  We have applied the planner to solve a
               challenging replanning problem involving the mapping of
               an unknown workspace with a non-holonomic platform.</ABSTRACT>
	<URL>http://www.kavrakilab.org/sites/default/files/bekris_icra07.pdf</URL>
</RECORD>
</RECORDS></XML>