On the Use of Torque Measurement in Centroidal State Estimation
This addresses state estimation challenges for legged robots, offering a method to enhance accuracy in dynamic control, though it is incremental as it builds on existing torque measurement capabilities.
The paper tackled the problem of estimating centroidal states in legged robots by incorporating joint torque measurements into an Extended Kalit Filter, demonstrating through real-world experiments on a quadruped that this approach drastically improves recovery compared to direct computation.
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.