3 accepted papers
Our original publication Kleinbort et al. (2019) contains an error in the analysis of the case of the kinodynamic RRT. Here, we rectify the problem by modifying the proof of Theorem <xref ref-type="theorem" rid="theorem2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/
The rapidly exploring random tree (RRT) algorithm has been one of the most prevalent and popular motion-planning techniques for two decades now. Surprisingly, in spite of its centrality, there has been an active debate under which conditions RRT is probabilistically complete. We provide two new proo
Motion planners have been recently developed that provide path quality guarantees for robots with dynamics. This work aims to improve upon their efficiency, while maintaining their properties. Inspired by informed search principles, one objective is to use heuristics. Nevertheless, comprehensive and…