Pattern Generation for Walking on Slippery Terrains

TL;DR

This paper extends Model Predictive Control to enable safe bipedal walking on slippery terrains by balancing velocity, ZMP, and friction regulation, with simulation results demonstrating the trade-offs involved.

Contribution

It introduces a novel MPC-based approach that explicitly considers friction and contact stability for walking on slippery surfaces.

Findings

Higher walking velocity increases slippage risk.

Reducing slippage conflicts with tip-over prevention.

Simulation confirms the effectiveness of the approach.

Abstract

In this paper, we extend state of the art Model Predictive Control (MPC) approaches to generate safe bipedal walking on slippery surfaces. In this setting, we formulate walking as a trade off between realizing a desired walking velocity and preserving robust foot-ground contact. Exploiting this formulation inside MPC, we show that safe walking on various flat terrains can be achieved by compromising three main attributes, i. e. walking velocity tracking, the Zero Moment Point (ZMP) modulation, and the Required Coefficient of Friction (RCoF) regulation. Simulation results show that increasing the walking velocity increases the possibility of slippage, while reducing the slippage possibility conflicts with reducing the tip-over possibility of the contact and vice versa.