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JRM Vol.35 No.1 pp. 160-170
doi: 10.20965/jrm.2023.p0160
(2023)

Paper:

Model Predictive Leg Configuration Control for Leg/Wheel Mobile Robots that Adapts to Changes in Ground Level

Naoki Takahashi and Kenichiro Nonaka

Tokyo City University
1-28-1 Tamazutsumi, Setagaya-ku, Tokyo 158-8557, Japan

Received:
February 23, 2022
Accepted:
October 26, 2022
Published:
February 20, 2023
Keywords:
model predictive control, leg/wheel mobile robot, zero moment point, locomotion
Abstract

Leg/wheel mobile robots, which have articulated legs ending in a wheel, can walk on legs as well as drive on wheels by switching between those two motive mechanisms in response to the terrain. However, effective control of the redundant degrees of freedom of leg/wheel mobile robots is complex. In this study, we propose a model predictive controller for leg configuration control that achieves both driving along the ground surface and climbing over a step. The proposed method simultaneously optimizes the robot pose, wheel positions, and joint angles. To consider the kinematic configuration of the legs explicitly, we formulate constraints on the relative position between the body and wheels. The ground contact condition of the wheels is approximately expressed as a continuous function with respect to each wheel’s relative position to the ground. This formulation induces smooth lifting of the wheels when the ground level abruptly changes, as when climbing a step. To prevent overturning, we evaluate the load distribution between each grounded wheel and constrain the body position to form a support polygon consisting of the grounded wheels. We conducted numerical simulations to verify that the proposed method achieves both driving on wheels and climbing over a step.

Leg-wheeled mobile robot overcomes uneven terrain using model predictive control

Leg-wheeled mobile robot overcomes uneven terrain using model predictive control

Cite this article as:
N. Takahashi and K. Nonaka, “Model Predictive Leg Configuration Control for Leg/Wheel Mobile Robots that Adapts to Changes in Ground Level,” J. Robot. Mechatron., Vol.35 No.1, pp. 160-170, 2023.
Data files:
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