SLIP Embodied Robust Quadruped Robot Control

Abstract

Recent research on quadruped robots has been achieving high-performance motion control based on optimization and reinforcement learning (RL). However, there is still ongoing research aimed at demonstrating that implementing high-performance motion based on simple and dominant dynamic principles is possible. In this paper, we proposed a novel control approach that projects Spring-Loaded Inverted Pendulum (SLIP) dynamics to articulated legs, utilizing admittance control based force observer within a rotating workspace (RWFOB). Unlike other legged robots that depend on sensor-based estimation of external forces, the proposed method presents an alternative approach that reduces the reliance on sensors. Additionally, we introduce a comprehensive control framework for quadruped robot motion control, establishing the connection between trunk and SLIP-realized leg movements using Jacobian. Through comparative analysis with Virtual Model Control (VMC) in simulations, we illustrate the effectiveness of the proposed framework as a robust and reliable trunk feedback controller.