On the Use of Torque Measurement in Centroidal State Estimation

TL;DR

This paper introduces a novel method for estimating the centroidal states of legged robots by utilizing joint torque measurements within an EKF framework, significantly enhancing state accuracy over traditional methods.

Contribution

It proposes a new approach that incorporates joint torque data into centroidal state estimation, leveraging constrained dynamics and the centroidal momentum matrix.

Findings

Torque-based EKF improves centroidal state accuracy

Method validated on a quadruped robot with different gaits

Significant enhancement over direct computation methods

Abstract

State of the art legged robots are either capable of measuring torque at the output of their drive systems, or have transparent drive systems which enable the computation of joint torques from motor currents. In either case, this sensor modality is seldom used in state estimation. In this paper, we propose to use joint torque measurements to estimate the centroidal states of legged robots. To do so, we project the whole-body dynamics of a legged robot into the nullspace of the contact constraints, allowing expression of the dynamics independent of the contact forces. Using the constrained dynamics and the centroidal momentum matrix, we are able to directly relate joint torques and centroidal states dynamics. Using the resulting model as the process model of an Extended Kalman Filter (EKF), we fuse the torque measurement in the centroidal state estimation problem. Through real-world experiments on a quadruped robot with different gaits, we demonstrate that the estimated centroidal states from our torque-based EKF drastically improve the recovery of these quantities compared to direct computation.