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

Ke Wang,Petar Kormushev,Hengyi Fei

doi:10.3389/frobt.2022.812258

Ke Wang, Petar Kormushev + Show 1 more

Open Access

https://doi.org/10.3389/frobt.2022.812258

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Abstract

We present an online optimization algorithm which enables bipedal robots to blindly walk over various kinds of uneven terrains while resisting pushes. The proposed optimization algorithm performs high-level motion planning of footstep locations and center-of-mass height variations 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) problem and solved at a frequency of 1 kHz. The output of the motion planner is fed into an inverse-dynamics–based whole body controller for execution on the robot. A key result of this controller is that the feet of the robot are compliant, which further extends the robot’s ability to be robust to unobserved terrain variations. We evaluate our method in simulation with the bipedal robot SLIDER. The results show that the robot can blindly walk over various uneven terrains including slopes, wave fields, and stairs. It can also resist pushes of up to 40 N for a duration of 0.1 s while walking on uneven terrains.

Highlights

To make bipedal robots really suitable for many applications, it is important that they can go out of the lab and walk in the complex real world environment
Most existing controllers that allow a bipedal robot to walk over uneven terrains require predefined footstep locations or exact information about the terrain height variations (Mordatch et al, 2010; Englsberger et al, 2015; Liu et al, 2015)
The proposed method is applied to the SLIDER robot and demonstrates successful blind walking on various uneven terrains and the robustness to disturbances due to fast model predictive control (MPC)

Summary

Introduction

To make bipedal robots really suitable for many applications, it is important that they can go out of the lab and walk in the complex real world environment. Real-world environments contain various kinds of uneven terrains: slopes, stairs, and hills. Most existing controllers that allow a bipedal robot to walk over uneven terrains require predefined footstep locations or exact information about the terrain height variations (Mordatch et al, 2010; Englsberger et al, 2015; Liu et al, 2015). Even with most advanced sensors, there are some uncertainties on the perception of the terrain. Humans can walk on uneven terrains, such as outdoor environments, and without extra thought or careful planning. It is important to have a reactive controller that is robust to unobserved uneven terrain variations

Results

Discussion

Conclusion