Paper Accepted at WAFR 2014 on Asymptotically Optimal Kinodynamic Planning
The paper Sparse Methods for Efficient Asymptotically Optimal Kinodynamic Planning (Yanbo Li, Zakary Littlefield, Kostas Bekris) has been accepted to appear in the 2014 Workshop on the Algorithmic Foundations of Robotics (WAFR) in Istanbul, Turkey, August 3-5.
This paper describes a method for sampling-based motion planning, which is the first to the best of our knowledge that achieves all of the following objectives:
- provides asymptotic (near-)optimality for kinodynamic planning without access to a steering function,
- maintains only a sparse set of samples,
- converges fast to high-quality paths and
- achieves competitive running time to RRT, which provides only probabilistic completeness.