Fast Online Optimization for Terrain-Blind Bipedal Robot Walking with a Decoupled Actuated SLIP Model

TL;DR

This paper introduces a fast, reactive online control method for bipedal robots to walk blindly over uneven terrains and resist pushes, using a decoupled aSLIP model and real-time optimization.

Contribution

It develops a decoupled aSLIP-based motion planner with 1kHz MPC for robust, terrain-blind bipedal walking, integrating inverse dynamics control for execution.

Findings

Successfully demonstrated blind walking over slopes, stairs, and wave fields in simulation.

Achieved push resistance during uneven terrain walking.

Enabled high-frequency (1kHz) real-time optimization for bipedal control.

Abstract

We present a highly reactive controller which enables bipedal robots to blindly walk over various kinds of uneven terrains while resisting pushes. The high level motion planner does fast online optimization for footstep locations and Center of Mass (CoM) height using the decoupled actuated Spring Loaded Inverted Pendulum (aSLIP) model. The decoupled aSLIP model simplifies the original aSLIP with Linear Inverted Pendulum (LIP) dynamics in horizontal states and spring dynamics in the vertical state. The motion planning can be formulated as a discrete-time Model Predictive Control (MPC) and solved at a frequency of 1k~HZ. The output of the motion planner using a reduced-order model is fed into an inverse-dynamics based whole body controller for execution on the robot. A key result of this controller is that the foot of the robot is compliant, which further extends the robot's ability to be robust to unobserved terrain changes. We evaluate our method in simulation with the bipedal robot SLIDER. Results show the robot can blindly walk over various uneven terrains including slopes, wave fields and stairs. It can also resist pushes while walking on uneven terrain.