Robust Physics-Based Locomotion Using Low-Dimensional Planning




This paper presents a physics-based locomotion controller based on online planning. At each time-step, a planner optimizes locomotion over multiple phases of gait. Stance dynamics are modeled using a simplified Spring-Load Inverted (SLIP) model, while flight dynamics are modeled using projectile motion equations. Full-body control at each instant is optimized to match the instantaneous plan values, while also maintaining balance. Different types of gaits, including walking, running, and jumping, emerge automatically, as do transitions between different gaits. The controllers can traverse challenging terrain and withstand large external disturbances, while following high-level user commands at interactive rates.


Igor Mordatch, Martin de Lasa, Aaron Hertzmann, Robust Physics-Based Locomotion Using Low-Dimensional Planning, ACM Transactions on Graphics, 2010, 29, 3, (Proc. SIGGRAPH). BibTex | Errata


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The authors are indebted to Simon Breslav for his assistance with video production and to Jack Wang for inspiring technical discussions. We thank Nikolaus Hansen for his publicly available CMA implementation. This research is supported in part by NSERC, CFI, and Ontario MRI. Part of this work was done while Aaron Hertzmann was on a sabbatical visit at Pixar Animation Studios.