@inproceedings{2090c30430514f8f83a2079c79d1f756,
title = "Model predictive control based path following for a wheel-legged robot",
abstract = "This paper proposes a model predictive control (MPC) based path following approach for tracking control of a wheel-legged robot named BIT-NAZA. The accuracy and stability of tracking control are still the main challenges for the autonomous wheel-legged robot due to its complex mechanical system. The wheel-legged robot has four legs and four wheels, and the wheels are installed on the end of the foot. To guarantee the tracking performance of the wheel-legged robot, effective approaches for reliable tracking control should be investigated with the consideration of the robot modeling, kinematics and dynamics constraints designing. In this paper, model predictive control based path following controller is designed and employed to improve the tracking performance for the wheel-legged robot BIT-NAZA. Experiments with the wheel-legged robot are performed to validate the performance of the proposed control strategy. The results demonstrate that the proposed methodology can achieve promising tracking performance in terms of accuracy.",
keywords = "Model Predictive Control, Modeling, Path Following, Wheel-legged Robot",
author = "Ke Zhang and Junzheng Wang and Hui Peng and Yunpei Dang",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 32nd Chinese Control and Decision Conference, CCDC 2020 ; Conference date: 22-08-2020 Through 24-08-2020",
year = "2020",
month = aug,
doi = "10.1109/CCDC49329.2020.9164598",
language = "English",
series = "Proceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "3925--3930",
booktitle = "Proceedings of the 32nd Chinese Control and Decision Conference, CCDC 2020",
address = "United States",
}