Trajectory Predictions with Details in a Robotic Twin-Crane System

Ning Zhao; Gabriel Lodewijks; Zhuorui Fu; Yu Sun; Yue Sun

doi:10.23919/CSMS.2021.0028

Complex System Modeling and Simulation 2022, 2(1): 1-17 https://doi.org/10.23919/CSMS.2021.0028

Open Access | Issue | Published: 30 March 2022

Trajectory Predictions with Details in a Robotic Twin-Crane System

Show Author's Information Hide Author's Information Ning Zhao^¹, Gabriel Lodewijks^²(

), Zhuorui Fu^¹, Yu Sun^¹, Yue Sun^¹

1 School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China

2 School of Aviation, University of New South Wales, Sydney 2052, Australia

Keywords:

velocity, interference, trajectory prediction, twin-crane systems, acceleration

Cite this article:

Zhao N, Lodewijks G, Fu Z, et al. Trajectory Predictions with Details in a Robotic Twin-Crane System. Complex System Modeling and Simulation, 2022, 2(1): 1-17. https://doi.org/10.23919/CSMS.2021.0028

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Abstract

Nowadays, more automated or robotic twin-crane systems (RTCSs) are employed in ports and factories to improve material handling efficiency. In a twin-crane system, cranes must travel with a minimum safety distance between them to prevent interference. The crane trajectory prediction is critical to interference handling and crane scheduling. Current trajectory predictions lack accuracy because many details are simplified. To enhance accuracy and lessen the trajectory prediction time, a trajectory prediction approach with details (crane acceleration/deceleration, different crane velocities when loading/unloading, and trolley movement) is proposed in this paper. Simulations on different details and their combinations are conducted on a container terminal case study. According to the simulation results, the accuracy of the trajectory prediction can be improved by 20%. The proposed trajectory prediction approach is helpful for building a digital twin of RTCSs and enhancing crane scheduling.

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About this article

Trajectory Predictions with Details in a Robotic Twin-Crane System

Show Author's information Hide Author's Information Ning Zhao^¹, Gabriel Lodewijks^²(

), Zhuorui Fu^¹, Yu Sun^¹, Yue Sun^¹

1 School of Mechanical Engineering, University of Science and Technology Beijing, Beijing 100083, China

2 School of Aviation, University of New South Wales, Sydney 2052, Australia

Abstract

Keywords: velocity, interference, trajectory prediction, twin-crane systems, acceleration

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Publication history

Received: 23 September 2021

Revised: 08 November 2021

Accepted: 22 November 2021

Published: 30 March 2022

Issue date: March 2022

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This work was supported by the National Natural Science Foundation of China (No. 52075036).

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