Distributed Inverse Dynamics Control for Quadruped Robots using Geometric Optimization

TL;DR

This paper introduces a distributed inverse dynamics controller for quadruped robots that enforces exact friction constraints using geometric optimization, leading to improved stability, faster convergence, and efficient embedded implementation.

Contribution

It presents a novel geometric optimization-based solver for inverse dynamics control that accurately enforces friction constraints and enhances real-time performance.

Findings

Reduces foot slippage significantly.

Improves orientation tracking accuracy.

Converges at least twice as fast as existing methods.

Abstract

This paper presents a distributed inverse dynamics controller (DIDC) for quadruped robots that addresses the limitations of existing reactive controllers: simplified dynamical models, the inability to handle exact friction cone constraints, and the high computational requirements of whole-body controllers. Current methods either ignore friction constraints entirely or use linear approximations, leading to potential slip and instability, while comprehensive whole-body controllers demand significant computational resources. Our approach uses full rigid-body dynamics and enforces exact friction cone constraints through a novel geometric optimization-based solver. DIDC combines the required generalized forces corresponding to the actuated and unactuated spaces by projecting them onto the actuated space while satisfying the physical constraints and maintaining orthogonality between the base and joint tracking objectives. Experimental validation shows that our approach reduces foot slippage, improves orientation tracking, and converges at least two times faster than existing reactive controllers with generic QP-based implementations. The controller enables stable omnidirectional trotting at various speeds and consumes less power than comparable methods while running efficiently on embedded processors.