TAMOLS: Terrain-Aware Motion Optimization for Legged Systems

• Published in: IEEE transactions on robotics Vol. 38; no. 6; pp. 3395 - 3413
• Main Authors: Jenelten, Fabian, Grandia, Ruben, Farshidian, Farbod, Hutter, Marco
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computational modeling; Contact force; Dynamics; Friction; Legged locomotion; Legged robots; Motion control; Numerical stability; optimization and optimal control; perceptive locomotion; Robot control; Stability criteria; Terrain; Trajectory optimization
• ISSN: 1552-3098; 1941-0468
• DOI: 10.1109/TRO.2022.3186804

Terrain geometry is, in general, nonsmooth, nonlinear, nonconvex, and, if perceived through a robot-centric visual unit, appears partially occluded and noisy. This article presents the complete control pipeline capable of handling the aforementioned problems in real-time. We formulate a trajectory optimization problem that jointly optimizes over the base pose and footholds, subject to a height map. To avoid converging into undesirable local optima, we deploy a graduated optimization technique. We embed a compact, contact-force free stability criterion that is compatible with the nonflat ground formulation. Direct collocation is used as transcription method, resulting in a nonlinear optimization problem that can be solved online in less than ten milliseconds. To increase robustness in the presence of external disturbances, we close the tracking loop with a momentum observer. Our experiments demonstrate stair climbing, walking on stepping stones, and over gaps, utilizing various dynamic gaits.