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Distributed Motion Control for Multiple Mobile Robots Using Discrete-Event Systems and Model Predictive Control

delete2024-02-01
delete4
PRE
AI
周
周圆 (Yuan Zhou)
H
Hesuan Hu *
G
Gelei Deng
K
Kun Cheng
S
Shang‐Wei Lin
刘
刘洋 (Yang Liu)
Z
Zuohua Ding
DOI:10.1109/TSMC.2023.3322154delete
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摘要

摘要

En 中文
Distributed motion control is critical in multiple mobile robot systems (MMRSs). Current research usually focuses on either discrete approaches, which aim to deal with high-level collisions and deadlocks without considering the low-level motion commands, or continuous approaches, which can optimize low-level continuous commands to mobile robots but cannot deal with deadlocks efficiently. In this article, by combining discrete and continuous methods, we design a hybrid motion control method for MMRSs where each robot should move along a predefined path. First, each robot's motion is modeled as a discrete transition system, based on which a real-time supervisory control policy is illustrated to avoid collisions and deadlocks. Second, according to the discrete decisions, the continuous speed at each discrete state is computed using model predictive control and sequential convex programming. The proposed hybrid approach brings two advantages. First, the discrete control component guarantees collision and deadlock avoidance and reduces the scale of the optimization problems. Second, continuous control optimizes the continuous speed in real time and fulfills other performance requirements like time and energy costs. To move in a fully distributed way, each robot needs to predict the motion of its neighbors by retrieving their immediately available information through communications. The simulation and real-world experimental results show the effectiveness of our approach.
Keyword:
Collision and deadlock avoidance
hybrid control
motion planning
multiple mobile robot systems (MMRSs)

期刊

IEEE Transactions on Cybernetics 封面图
IEEE Transactions on Cybernetics
IF:
10.5
论文数:
1.1W
被引数:
5.0W

机构

Z
Zhejiang Sci-Tech University
学者数:
1.7W
论文数: 1.0W
被引数: 1.3W
B
Beihang University
学者数:
5.2W
论文数: 4.1W
被引数: 37
N
Nanyang Technological University
学者数:
4.9W
论文数: 4.8W
被引数: 8.1W
X
Xidian University
学者数:
2.4W
论文数: 1.9W
被引数: 9.7K
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引用论文

引用论文

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