Online Friction Coefficient Identification for Legged Robots on Slippery Terrain Using Smoothed Contact Gradients

TL;DR

This paper introduces an online method for accurately identifying the friction coefficient of slippery terrain for legged robots by using smoothed contact gradients and data filtering, validated on a quadrupedal robot.

Contribution

It presents a novel online friction identification framework leveraging smoothed contact gradients and a rejection method to improve accuracy on slippery terrains.

Findings

Achieves fast and consistent friction coefficient estimation

Validates effectiveness on a quadrupedal robot platform

Handles various initial conditions effectively

Abstract

This paper proposes an online friction coefficient identification framework for legged robots on slippery terrain. The approach formulates the optimization problem to minimize the sum of residuals between actual and predicted states parameterized by the friction coefficient in rigid body contact dynamics. Notably, the proposed framework leverages the analytic smoothed gradient of contact impulses, obtained by smoothing the complementarity condition of Coulomb friction, to solve the issue of non-informative gradients induced from the nonsmooth contact dynamics. Moreover, we introduce the rejection method to filter out data with high normal contact velocity following contact initiations during friction coefficient identification for legged robots. To validate the proposed framework, we conduct the experiments using a quadrupedal robot platform, KAIST HOUND, on slippery and nonslippery terrain. We observe that our framework achieves fast and consistent friction coefficient identification within various initial conditions.