Online Planning for Autonomous Running Jumps Over Obstacles in High-Speed Quadrupeds
Name
RSS2015_Final.pdf
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2.36 MB
Format
Adobe PDF
Checksum (MD5)
1590ad45cb2ee04d17cba116fa987ec0
Author(s)
Park, Hae won
Wensing, Patrick M.
Kim, Sangbae
Date Issued
July 2015
Journal
Proceedings of the 2015 Robotics: Science and Systems Conference (RSS)
Citation
Park, Hae-Won, Patrick M. Wensing, and Sangbae Kim. "Online Planning for Autonomous Running Jumps Over Obstacles in High-Speed Quadrupeds." 2015 Robotics: Science and Systems Conference (July 13-17, 2015), Sapienza University of Rome, pp.1-9.
Version
Author's final manuscript
Abstract
This paper presents a new framework for the generation of high-speed running jumps to clear terrain obstacles in quadrupedal robots. Our methods enable the quadruped to autonomously jump over obstacles up to 40 cm in height within a single control framework. Specifically, we propose new control system components, layered on top of a low-level running controller, which actively modify the approach and select stance force profiles as required to clear a sensed obstacle. The approach controller enables the quadruped to end in a preferable state relative to the obstacle just before the jump. This multi-step gait planning is formulated as a multiple-horizon model predictive control problem and solved at each step through quadratic programming. Ground reaction force profiles to execute the running jump are selected through constrained nonlinear optimization on a simplified model of the robot that possesses polynomial dynamics. Exploiting the simplified structure of these dynamics, the presented method greatly accelerates the computation of otherwise costly function and constraint evaluations that are required during optimization. With these considerations, the new algorithms allow for online planning that is critical for reliable response to unexpected situations. Experimental results, for a stand-alone quadruped with on-board power and computation, show the viability of this approach, and represent important steps towards broader dynamic maneuverability in experimental machines.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
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Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
http://www.roboticsproceedings.org/rss11/p47.pdf
