Search-based Planning for a Legged Robot over Rough Terrain - Robotics Institute Carnegie Mellon University

Search-based Planning for a Legged Robot over Rough Terrain

Paul Vernaza, Maxim Likhachev, Subhrajit Bhattacharya, Sachin Chitta, Aleksandr Kushleyev, and Daniel D. Lee
Conference Paper, Proceedings of (ICRA) International Conference on Robotics and Automation, pp. 2380 - 2387, May, 2009

Abstract

We present a search-based planning approach for controlling a quadrupedal robot over rough terrain. Given a start and goal position, we consider the problem of generating a complete joint trajectory that will result in the legged robot successfully moving from the start to the goal. We decompose the problem into two main phases: an initial global planning phase, which results in a footstep trajectory; and an execution phase, which dynamically generates a joint trajectory to best execute the footstep trajectory. We show how R* search can be employed to generate high-quality global plans in the high-dimensional space of footstep trajectories. Results show that the global plans coupled with the joint controller result in a system robust enough to deal with a variety of terrains.

BibTeX

@conference{Vernaza-2009-109723,
author = {Paul Vernaza and Maxim Likhachev and Subhrajit Bhattacharya and Sachin Chitta and Aleksandr Kushleyev and Daniel D. Lee},
title = {Search-based Planning for a Legged Robot over Rough Terrain},
booktitle = {Proceedings of (ICRA) International Conference on Robotics and Automation},
year = {2009},
month = {May},
pages = {2380 - 2387},
}