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TAMOLS: Terrain-Aware Motion Optimization for Legged Systems

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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… Click to show full abstract

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.

Keywords: aware motion; motion optimization; optimization legged; tamols terrain; terrain aware; optimization

Journal Title: IEEE Transactions on Robotics
Year Published: 2022

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