Learning footstep planning on irregular surfaces with partial placements

Germán Castro; Claude Sammut

IROS 2019poster1 citations

Learning footstep planning on irregular surfaces with partial placements

Abstract

We present two contributions built upon on a previous footstep planner based on the ARA* search. Firstly, we have developed an improved foothold selection method using support polygons, to increase foothold availability in rough terrain. Secondly, we present a footstep classification method using the C5.0 algorithm, that takes advantage of cost similarity between adjacent steps. This is intended to learn feasibility and approximate transition costs for the ARA* planner.These contributions extend capabilities of the planner by increasing footstep availability and allowing to generate more complex plans, without compromising safety.

BibTeX

@inproceedings{iros2019_learningfootstep,
  title = {Learning footstep planning on irregular surfaces with partial placements},
  author = {Germán Castro and Claude Sammut},
  booktitle = {IROS 2019},
  year = {2019}
}