Dynamic Walking of Bipedal Robots on Uneven Stepping Stones via Adaptive-frequency MPC

TL;DR

This paper introduces an adaptive-frequency MPC framework combined with trajectory optimization and whole-body control to enable bipedal robots to walk over uneven terrain with variable stepping stones at a consistent speed.

Contribution

It presents a novel adaptive-frequency MPC approach that dynamically adjusts gait parameters for robust terrain traversal, outperforming fixed-frequency methods.

Findings

Successfully traverses uneven terrain with variable stepping stones.

Maintains an average speed of 1.5 m/s during complex terrain navigation.

Outperforms fixed-frequency MPC in numerical validations.

Abstract

This paper presents a novel Adaptive-frequency MPC framework for bipedal locomotion over terrain with uneven stepping stones. In detail, we intend to achieve adaptive foot placement and gait period for bipedal periodic walking gait with this MPC, in order to traverse terrain with discontinuities without slowing down. We pair this adaptive-frequency MPC with a kino-dynamics trajectory optimization for optimal gait periods, center of mass (CoM) trajectory, and foot placements. We use whole-body control (WBC) along with adaptive-frequency MPC to track the optimal trajectories from the offline optimization. In numerical validations, our adaptive-frequency MPC framework with optimization has shown advantages over fixed-frequency MPC. The proposed framework can control the bipedal robot to traverse through uneven stepping stone terrains with perturbed stone heights, widths, and surface shapes while maintaining an average speed of 1.5 m/s.