ROSYSep 9, 2021

A Unified Model with Inertia Shaping for Highly Dynamic Jumps of Legged Robots

arXiv:2109.04581v116 citations
Originality Incremental advance
AI Analysis

This work addresses the challenge of achieving stable and dynamic jumps for legged robots, which is incremental as it builds on existing motion planning methods with a focus on inertia shaping.

The paper tackled the problem of controlling rotational dynamics for highly dynamic jumps in legged robots by proposing a unified model (LL-SRBM) that approximates centroidal inertia, resulting in improved jump performance demonstrated through experiments on bipedal and quadrupedal robots.

To achieve highly dynamic jumps of legged robots, it is essential to control the rotational dynamics of the robot. In this paper, we aim to improve the jumping performance by proposing a unified model for planning highly dynamic jumps that can approximately model the centroidal inertia. This model abstracts the robot as a single rigid body for the base and point masses for the legs. The model is called the Lump Leg Single Rigid Body Model (LL-SRBM) and can be used to plan motions for both bipedal and quadrupedal robots. By taking the effects of leg dynamics into account, LL-SRBM provides a computationally efficient way for the motion planner to change the centroidal inertia of the robot with various leg configurations. Concurrently, we propose a novel contact detection method by using the norm of the average spatial velocity. After the contact is detected, the controller is switched to force control to achieve a soft landing. Twisting jump and forward jump experiments on the bipedal robot SLIDER and quadrupedal robot ANYmal demonstrate the improved jump performance by actively changing the centroidal inertia. These experiments also show the generalization and the robustness of the integrated planning and control framework.

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