Asymptotically Optimal Planning by Feasible Kinodynamic Planning in State-Cost Space
Abstract
This paper presents an equivalence between feasible kinodynamic planning and optimal kinodynamic planning, in that any optimal planning problem can be transformed into a series of feasible planning problems in a state-cost space whose solutions approach the optimum. This transformation gives rise to a meta-algorithm that produces an asymptotically optimal planner, given any feasible kinodynamic planner as a subroutine. The meta-algorithm is proven to be asymptotically optimal, and a formula is derived relating expected running time and solution suboptimality. It is directly applicable to a wide range of optimal planning problems because it does not resort to the use of steering functions or numerical boundary-value problem solvers. On a set of benchmark problems, it is demonstrated to perform, using the EST and RRT algorithms as subroutines, at a superior or comparable level to related planners.
Keywords
Cite
@article{arxiv.1505.04098,
title = {Asymptotically Optimal Planning by Feasible Kinodynamic Planning in State-Cost Space},
author = {Kris Hauser and Yilun Zhou},
journal= {arXiv preprint arXiv:1505.04098},
year = {2015}
}