Representation-Free Model Predictive Control for Dynamic Motions in Quadrupeds

This article presents a novel representation-free model predictive control (RF-MPC) framework for controlling various dynamic motions of a quadrupedal robot in three-dimensional (3-D) space. Our formulation directly represents the rotational dynamics using the rotation matrix, which liberates us fro...

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Bibliographic Details
Published in:IEEE transactions on robotics 2021-08, Vol.37 (4), p.1154-1171
Main Authors: Ding, Yanran, Pandala, Abhishek, Li, Chuanzheng, Shin, Young-Ha, Park, Hae-Won
Format: Article
Language:English
Subjects:
Control theory
Cost function
Dynamics
Euler angles
Legged locomotion
legged robots
Maneuvers
Mathematical model
model predictive control (MPC)
Predictive control
Quaternions
Representations
Robot kinematics
Robots
underactuated robots
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Summary:This article presents a novel representation-free model predictive control (RF-MPC) framework for controlling various dynamic motions of a quadrupedal robot in three-dimensional (3-D) space. Our formulation directly represents the rotational dynamics using the rotation matrix, which liberates us from the issues associated with the use of Euler angles and quaternion as the orientation representations. With a variation-based linearization scheme and a carefully constructed cost function, the MPC control law is transcribed to the standard quadratic program form. The MPC controller can operate at real-time rates of 250 Hz on a quadruped robot. Experimental results including periodic quadrupedal gaits and a controlled backflip validate that our control strategy could stabilize dynamic motions that involve singularity in 3-D maneuvers.
ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2020.3046415