Cooperative Motion Planning of Multiple Automated Vehicle Robots: A Quick IoT-Based Approach

In this article, we propose a novel hybrid control approach for solving the multirobot motion planning (MRMP) problem in the Internet of Things (IoT) environment, where the closed workspace is “abstracted” as a discrete-event system (DES) that is modeled as a timed Petri net. In the DES, robot’s movement between adjacent confliction zones is viewed as a “transition,” by taking the robot kinematics into consideration. To ensure safety and efficiency, robots should not appear at the same conflict position at the same time and should not block each other. To this end, an online IoT-based approach is provided to control robots to travel in the closed workspace safely (without collisions) and efficiently (without deadlocks). Specifically, a high-level supervisory controller whose commands are in the form of transitions, is used to control robots to travel in the closed workspace. At the low level, we explicitly capture the time-driven robot kinematics, and commands from the supervisory controller are translated into appropriate input signals to the actuators of the robots, which in turn influence states of the high-level DES. Simulation results demonstrate the expressiveness of the proposed model and the effectiveness and efficiency of the proposed algorithm.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-09-03
DOI
https://doi.org/10.1109/jiot.2024.3453899
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

Cooperative Motion Planning of Multiple Automated Vehicle Robots: A Quick IoT-Based Approach

Zhongdong Wang, Donghui Li, Junhua Xi, Yonghao Tang
IEEE Internet of Things Journal
Robotic Path Planning Algorithms
article

Cooperative Motion Planning of Multiple Automated Vehicle Robots: A Quick IoT-Based Approach

Zhongdong Wang, Donghui Li, Junhua Xi, Yonghao Tang
article en

Abstract

In this article, we propose a novel hybrid control approach for solving the multirobot motion planning (MRMP) problem in the Internet of Things (IoT) environment, where the closed workspace is “abstracted” as a discrete-event system (DES) that is modeled as a timed Petri net. In the DES, robot’s movement between adjacent confliction zones is viewed as a “transition,” by taking the robot kinematics into consideration. To ensure safety and efficiency, robots should not appear at the same conflict position at the same time and should not block each other. To this end, an online IoT-based approach is provided to control robots to travel in the closed workspace safely (without collisions) and efficiently (without deadlocks). Specifically, a high-level supervisory controller whose commands are in the form of transitions, is used to control robots to travel in the closed workspace. At the low level, we explicitly capture the time-driven robot kinematics, and commands from the supervisory controller are translated into appropriate input signals to the actuators of the robots, which in turn influence states of the high-level DES. Simulation results demonstrate the expressiveness of the proposed model and the effectiveness and efficiency of the proposed algorithm.

IEEE Internet of Things JournalVol. 11(22)
National University of Defense Technology (CN), Hunan Agricultural University (CN)
Sustainable cities and communities
Openalex Percentile: Top 86%
Robotic Path Planning Algorithms
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Cooperative Motion Planning of Multiple Automated Vehicle Robots: A Quick IoT-Based Approach — Zhongdong Wang, Donghui Li, et al. · IEEE Internet of Things Journal (2024) | TGRS Research Map | TGRS