Integration of Riemannian Motion Policies and Whole-body control for Dynamic Legged Locomotion

Daniel Marew, Misha Lvovsky, Shangqun Yu, Shotaro Sessions, Donghyun Kim

Abstract

In this paper, we present a novel Riemannian Motion Policy (RMP)flow-based whole-body control framework for improved dynamic legged locomotion. RMPflow is a differential geometry-inspired algorithm for fusing multiple task-space policies (RMPs) into a configuration space policy in a geometrically consistent manner. RMP-based approaches are especially suited for designing simultaneous tracking and collision avoidance behaviors and have been successfully deployed on serial manipulators. However, one caveat of RMPflow is that it is designed with fully actuated systems in mind. In this work, we, for the first time, extend it to the domain of dynamic-legged systems, which have unforgiving under-actuation and limited control input. Thorough push recovery experiments are conducted in simulation to validate the overall framework. We show that expanding the valid stepping region with an RMP-based collision-avoidance swing leg controller improves balance robustness against external disturbances by up to 53% compared to a baseline approach using a restricted stepping region. Furthermore, a point-foot biped robot is purpose-built for experimental studies of dynamic biped locomotion. A preliminary unassisted in-place stepping experiment is conducted to show the viability of the control framework and hardware. You can find the full article here https://arxiv.org/abs/2210.03713 .

We execute tasks specified in terms of Riemannian motion policies in the null space of Higher priority tasks such as floating base position and orientation using the modified pullback operation in the green box.

Push recovery simulation results (a) The green and red boxes represent the valid stepping region of the proposed strategy and baseline strategies, respectively. The red and green dashed lines represent the foot trajectory under the baseline and proposed strategy in response to the external disturbance. (b) Snapshots of the robot trajectory under three scenarios. First row (baseline strategy), second row: leg crossing movement without collision avoidance, bottom row (proposed strategy): safe leg crossing movement with collision avoidance. (c) polar coordinate representation of the the applied disturbance forces. Successful outcomes are shown for the proposed (green) and baseline (red) strategies at four different disturbance timings. T1 and T3 correspond to the double stance phase and T2 and T4 correspond to the right swing and left swing phases. Note that failed trials are not represented in these plots.

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