Push recovery with stepping strategy based on time-projection control

TL;DR

This paper introduces a simple yet robust control framework for online push recovery in legged robots, utilizing a time-projection control method based on a 3LP model to adjust footstep placement dynamically during walking.

Contribution

The paper presents a novel time-projection control approach integrated with a 3LP model for real-time push recovery, avoiding ZMP control and enabling emergent gait behaviors.

Findings

Effective push recovery demonstrated in extreme scenarios

Robust walking gaits emerge under continuous dragging forces

Time-projection improves footstep adjustment accuracy

Abstract

In this paper, we present a simple control framework for on-line push recovery with dynamic stepping properties. Due to relatively heavy legs in our robot, we need to take swing dynamics into account and thus use a linear model called 3LP which is composed of three pendulums to simulate swing and torso dynamics. Based on 3LP equations, we formulate discrete LQR controllers and use a particular time-projection method to adjust the next footstep location on-line during the motion continuously. This adjustment, which is found based on both pelvis and swing foot tracking errors, naturally takes the swing dynamics into account. Suggested adjustments are added to the Cartesian 3LP gaits and converted to joint-space trajectories through inverse kinematics. Fixed and adaptive foot lift strategies also ensure enough ground clearance in perturbed walking conditions. The proposed structure is robust, yet uses very simple state estimation and basic position tracking. We rely on the physical series elastic actuators to absorb impacts while introducing simple laws to compensate their tracking bias. Extensive experiments demonstrate the functionality of different control blocks and prove the effectiveness of time-projection in extreme push recovery scenarios. We also show self-produced and emergent walking gaits when the robot is subject to continuous dragging forces. These gaits feature dynamic walking robustness due to relatively soft springs in the ankles and avoiding any Zero Moment Point (ZMP) control in our proposed architecture.