Sampling-based motion planners are an effective means to generate collision-free motion paths. However, the quality of these motion paths (with respect to quality measures, such as path length, clearance, smoothness, or energy) is often notoriously low, especially in high-dimensional configuration spaces. We introduce a simple algorithm to merge an arbitrary number of input motion paths into a hybrid output path of superior quality, for a broad and general formulation of path quality. Our approach is based on the observation that the quality of certain subpaths within each solution may be higher than the quality of the entire path. A dynamic-programming algorithm, which we recently developed to compare and cluster multiple motion paths, reduces the running time of the merging algorithm significantly. We tested our algorithm in motion-planning problems with up to 12 degrees of freedom (DOFs), where our method is shown to be particularly effective. We show that our algorithm is able to merge a handful of input paths produced by several different motion planners to produce output paths of much higher quality.
Bibliographical noteFunding Information:
Manuscript received May 6, 2010; revised September 25, 2010; accepted December 2, 2010. Date of publication January 13, 2011; date of current version April 7, 2011. This paper was recommended for publication by Associate Editor F. Lamiraux and Editor J.-P. Laumond upon evaluation of the reviewers’ comments. This work was supported in part by the Israel Science Foundation under Grant 236/06, in part by the German–Israeli Foundation under Grant 969/07, and in part by the Hermann Minkowski–Minerva Center for Geometry, Tel Aviv University.
- Motion control
- path quality
- sampling-based motion planning