Proprioceptive External Torque Learning for Floating Base Robot and its Applications to Humanoid Locomotion

TL;DR

This paper presents a proprioception-based learning method for estimating external joint torque and contact wrench in humanoid robots, enabling stable locomotion without force-torque sensors, thus reducing hardware complexity and cost.

Contribution

It introduces a GRU-based learning approach using only proprioceptive sensors for external torque estimation, validated through real robot experiments showing improved accuracy over model-based methods.

Findings

Accurately estimates external torque and contact wrench using proprioception.

Enables stable walking with ZMP feedback control without force sensors.

Maintains performance despite changes in foot and upper body inertia.

Abstract

The estimation of external joint torque and contact wrench is essential for achieving stable locomotion of humanoids and safety-oriented robots. Although the contact wrench on the foot of humanoids can be measured using a force-torque sensor (FTS), FTS increases the cost, inertia, complexity, and failure possibility of the system. This paper introduces a method for learning external joint torque solely using proprioceptive sensors (encoders and IMUs) for a floating base robot. For learning, the GRU network is used and random walking data is collected. Real robot experiments demonstrate that the network can estimate the external torque and contact wrench with significantly smaller errors compared to the model-based method, momentum observer (MOB) with friction modeling. The study also validates that the estimated contact wrench can be utilized for zero moment point (ZMP) feedback control, enabling stable walking. Moreover, even when the robot's feet and the inertia of the upper body are changed, the trained network shows consistent performance with a model-based calibration. This result demonstrates the possibility of removing FTS on the robot, which reduces the disadvantages of hardware sensors. The summary video is available at https://youtu.be/gT1D4tOiKpo.