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A divide-and-conquer control strategy with decentralized control barrier function for luggage trolley transportation by collaborative robots

Published online by Cambridge University Press:  17 August 2023

Xuheng Gao
Affiliation:
Shenzhen Key Laboratory of Robotics Perception and Intelligence, Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
Hao Luan
Affiliation:
Shenzhen Key Laboratory of Robotics Perception and Intelligence, Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
Bingyi Xia
Affiliation:
Shenzhen Key Laboratory of Robotics Perception and Intelligence, Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
Ziqi Zhao
Affiliation:
Shenzhen Key Laboratory of Robotics Perception and Intelligence, Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
Jiankun Wang*
Affiliation:
Shenzhen Key Laboratory of Robotics Perception and Intelligence, Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China Jiaxing Research Institute, Southern University of Science and Technology, Jiaxing, China
Max Q.-H. Meng*
Affiliation:
Shenzhen Key Laboratory of Robotics Perception and Intelligence, Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
*
Corresponding authors: Jiankun Wang, Max Q.-H. Meng; Emails: wangjk@sustech.edu.cn, max.meng@ieee.org
Corresponding authors: Jiankun Wang, Max Q.-H. Meng; Emails: wangjk@sustech.edu.cn, max.meng@ieee.org

Abstract

This article focuses on the luggage trolley transportation problem, an essential part of robotic autonomous luggage trolley collection. To efficiently address the nonholonomic constraints derived from the formation of two collaborative robots and a queue of luggage trolleys, we propose a comprehensive framework consisting of a global planning method and a real-time divide-and-conquer control strategy. The popular Hybrid A* algorithm generates a feasible path as the global planner. A model predictive controller is designed to track this path stably and in real time. To maintain the formation so that the whole queue of robots and luggage trolleys does not split, a safety filter that consists of a discrete-time control Lyapunov function and a decentralized control barrier function is implemented in the transportation process. Finally, we conduct real-world experiments to verify the effectiveness of the proposed method on three representative paths, and the results show that our approach can achieve robust performance. The demonstration video can be found at https://www.youtube.com/watch?v=iPiT8BfLIpU.

Type
Research Article
Copyright
© The Author(s), 2023. Published by Cambridge University Press

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