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The International Journal of Robotics Research
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Motion Planning for Legged Robots on Varied Terrain

Kris Hauser

Department of Computer Science Stanford University Stanford,CA 94305-5447, USA, khauser{at}cs.stanford.edu

Timothy Bretl

University of Illinois at Urbana-Champaign, Urbana,IL 61801-2935, USA, tbretl{at}illinois.edu

Jean-Claude Latombe

Department of Computer Science Stanford University Stanford,CA 94305-5447, USA, latombe{at}cs.stanford.edu

Kensuke Harada

Humanoid Research Group Intelligent Systems ResearchInstitute National Institute of Advanced Industrial Science and Technology(AIST) Tsukuba, Ibaraki 305-8568, Japan, kensuke.harada{at}aist.go.jp

Brian Wilcox

Jet Propulsion Laboratory California Institute of TechnologyPasadena, CA 91109, Brian.H.Wilcox{at}jpl.nasa.gov

In this paper we study the quasi-static motion of large legged robots that have many degrees of freedom. While gaited walking may suffice on easy ground, rough and steep terrain requires unique sequences of footsteps and postural adjustments specifically adapted to the terrain's local geometric and physical properties. In this paper we present a planner that computes these motions by combining graph searching to generate a sequence of candidate footfalls with probabilistic sample-based planning to generate continuous motions that reach these footfalls. To improve motion quality, the probabilistic planner derives its sampling strategy from a small set of motion primitives that have been generated offline. The viability of this approach is demonstrated in simulation for the six-legged Lunar vehicle ATHLETE and the humanoid HRP-2 on several example terrains, including one that requires both hand and foot contacts and another that requires rappelling.

Key Words: Motion planning • legged robots • humanoids • probabilistic sample-based planning • motion primitives

The International Journal of Robotics Research, Vol. 27, No. 11-12, 1325-1349 (2008)
DOI: 10.1177/0278364908098447
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 The International Journal of Robotics ResearchHome page
S. Akella, N. M. Amato, W. Huang, and B. Mishra
Special Issue on the Seventh International Workshop on Algorithmic Foundations of Robotics
The International Journal of Robotics Research, November 1, 2008; 27(11-12): 1173 - 1174.
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