A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines

Mustafa Çoban; Gökhan Gelen

doi:10.38088/jise.1482853

EN

A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines

Abstract

Automated guided vehicles are transportation systems that are widely used in factories, warehouses, and distribution centers. It is of great importance to ensure the control and coordination of vehicles for safe and efficient transportation in multi-vehicle systems. In this study, a control strategy is proposed to enforce collision avoidance of automated guided vehicles operating in a shared zone and overlapping route environment. In the proposed method, while finite state machines are used to model the movement of automated guided vehicles in the environment, the Q-learning method, one of the most common reinforcement learning algorithms, is used for collision avoidance. The presented approach uses the decentralized node-based approach to reduce computational complexity. The proposed method has been validated through simulation performed with vehicle applications that can move both unidirectional and bidirectional. The simulation results show that our presented approach can avoid potential collisions and greatly increase overall efficiency.

Keywords

References

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Details

Primary Language

English

Subjects

Control Engineering, Mechatronics and Robotics (Other)

Journal Section

Research Article

Authors

Mustafa Çoban ^*
0000-0002-6508-5901
Türkiye

Gökhan Gelen
0000-0002-2780-3386
Türkiye

Early Pub Date

December 11, 2024

Publication Date

December 31, 2024

Submission Date

May 13, 2024

Acceptance Date

July 4, 2024

Published in Issue

Year 2024 Volume: 8 Number: 2

DOI

https://doi.org/10.38088/jise.1482853

IZ

https://izlik.org/JA86PJ26BC

Cite

RIS / Bibtex

APA

Çoban, M., & Gelen, G. (2024). A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines. Journal of Innovative Science and Engineering, 8(2), 179-198. https://doi.org/10.38088/jise.1482853

AMA

1.Çoban M, Gelen G. A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines. JISE. 2024;8(2):179-198. doi:10.38088/jise.1482853

Chicago

Çoban, Mustafa, and Gökhan Gelen. 2024. “A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines”. Journal of Innovative Science and Engineering 8 (2): 179-98. https://doi.org/10.38088/jise.1482853.

EndNote

Çoban M, Gelen G (December 1, 2024) A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines. Journal of Innovative Science and Engineering 8 2 179–198.

IEEE

[1]M. Çoban and G. Gelen, “A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines”, JISE, vol. 8, no. 2, pp. 179–198, Dec. 2024, doi: 10.38088/jise.1482853.

ISNAD

Çoban, Mustafa - Gelen, Gökhan. “A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines”. Journal of Innovative Science and Engineering 8/2 (December 1, 2024): 179-198. https://doi.org/10.38088/jise.1482853.

JAMA

1.Çoban M, Gelen G. A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines. JISE. 2024;8:179–198.

MLA

Çoban, Mustafa, and Gökhan Gelen. “A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines”. Journal of Innovative Science and Engineering, vol. 8, no. 2, Dec. 2024, pp. 179-98, doi:10.38088/jise.1482853.

Vancouver

1.Mustafa Çoban, Gökhan Gelen. A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines. JISE. 2024 Dec. 1;8(2):179-98. doi:10.38088/jise.1482853

A New Collision Avoidance Approach for Automated Guided Vehicle Systems Based on Finite State Machines

Abstract

Keywords

Öz

References

Details

Primary Language

Subjects

Journal Section

Authors

Early Pub Date

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite