Name
Title | ||
|---|---|---|
Refined Analysis of Asymptotically-Optimal Kinodynamic Planning in the State-Cost Space. |
Abstract | ||
|---|---|---|
We present a novel analysis of AO-RRT: a tree-based planner for motion planning with kinodynamic constraints, originally described by Hauser and Zhou (AO-X, 2016). AO-RRT explores the state-cost space and has been shown to efficiently obtain high-quality solutions in practice without relying on the availability of a computationally-intensive two-point boundary-value solver. Our main contribution is an optimality proof for the single-tree version of the algorithm—a variant that was not analyzed before. Our proof only requires a mild and easily-verifiable set of assumptions on the problem and system: Lipschitz-continuity of the cost function and the dynamics. In particular, we prove that for any system satisfying these assumptions, any trajectory having a piecewise-constant control function and positive clearance from the obstacles can be approximated arbitrarily well by a trajectory found by AORRT. We also discuss practical aspects of AORRT and present experimental comparisons of variants of the algorithm. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ICRA40945.2020.9197236 | ICRA |
DocType | Volume | Issue |
Conference | 2020 | 1 |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michal Kleinbort | 1 | 7 | 2.21 |
| Edgar Granados | 2 | 0 | 0.34 |
| Kiril Solovey | 3 | 71 | 10.30 |
| Riccardo Bonalli | 4 | 0 | 1.35 |
| Kostas E. Bekris | 5 | 938 | 99.49 |
| Dan Halperin | 6 | 1291 | 105.20 |