Foot Shape-Dependent Resistive Force Model for Bipedal Walkers on Granular Terrains

TL;DR

This paper introduces an improved resistive force model for bipedal robots on granular terrains, accounting for foot shape and gait speed, validated through experiments to enhance locomotion control.

Contribution

The paper presents a novel resistive force model that incorporates foot shape and intrusion depth correction for better locomotion prediction on granular terrains.

Findings

Model accurately predicts foot intrusion on granular terrains.

Validated model improves control strategies for bipedal robots.

Enhanced model considers gait speed and energy expenditure.

Abstract

Legged robots have demonstrated high efficiency and effectiveness in unstructured and dynamic environments. However, it is still challenging for legged robots to achieve rapid and efficient locomotion on deformable, yielding substrates, such as granular terrains. We present an enhanced resistive force model for bipedal walkers on soft granular terrains by introducing effective intrusion depth correction. The enhanced force model captures fundamental kinetic results considering the robot foot shape, walking gait speed variation, and energy expense. The model is validated by extensive foot intrusion experiments with a bipedal robot. The results confirm the model accuracy on the given type of granular terrains. The model can be further integrated with the motion control of bipedal robotic walkers.