Deep RRT*

Authors

  • Xuzhe Dang Czech Technical University in Prague
  • Lukáš Chrpa Czech Technical University in Prague
  • Stefan Edelkamp Czech Technical University in Prague

Keywords:

Machine And Deep Learning In Search

Abstract

Sampling-based motion planning algorithms such as Rapidly exploring Random Trees (RRTs) have been used in robotic applications for a long time. In this paper, we propose a method that combines deep learning with RRT* method. We use a neural network to learn a sample strategy for RRT*.We evaluate Deep RRT* in a collection of 2D scenarios. The results demonstrate that our algorithm could find collision-free paths efficiently and fast, and can be generalized to unseen environments.

Downloads

Published

2022-07-17