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General Information
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2024 Vol.14(2): 88-93
DOI: 10.7763/IJMO.2024.V14.854

Reinforcement Learning Based Communication Relay for Small Indoor Robots

Hyojun Ahn*, Sejin Kim1, Eunseo Baek1, Mingyu Shin1, Sungjun Shim2, Jooyoung Kim2, Yongjin Kwon1, *
1. 1Department of Industrial Engineering, College of Engineering, Ajou University, Suwon, South Korea
2. Intelligent/Autonomous Control SW Team, LIG Nex1, Sungnam, South Korea
3. School of Ecomomics, University of Valencia, Spain
Email: monikacies@gmail.com(M.C.); Email: hyojunahn000713@ajou.ac.kr (H.J.A.); jkn6873@ajou.ac.kr (S.J.K.); eunseo5343@ajou.ac.kr (E.S.B.); saycode99@ajou.ac.kr (M.G.S.); sungjun.shim@lignex1.com (S.J.S.); jooyoung.kim@lignex1.com (J.Y.K.); yk73@ajou.ac.kr (Y.J.K.) *Corresponding author

Manuscript received July 31, 2023; revised September 11, 2023; accepted January 12, 2024; published June 19, 2024.

Abstract—Communication relay among small indoor robots performing surveillance tasks within complex indoor environments is a vital element. In situations where communication is impeded, such as GPS blockage or disaster situations, robots moving within buildings must install repeaters or relay robots in appropriate locations to maintain the link. However, research on optimized methodologies for when and where to install relay robots is lacking. This is due to the complexity and diversity of indoor environments, making it difficult to present standardized solutions. To address these challenges, this paper proposes an algorithm for optimized communication relays by combining reinforcement learning and traditional shortest path algorithms. As a result of applying this algorithm, the distance traveled was reduced by 30%, and the sustained communication time increased by 36%. In addition, this approach demonstrated potential for future applications in dynamic mission planning for small indoor robots.

Keywords—reinforcement learning, small indoor robots, communication relay, A* algorithm, dynamic mission planning, simulation


Cite: Hyojun Ahn, Sejin Kim, Eunseo Baek, Mingyu Shin, Sungjun Shim, Jooyoung Kim, and Yongjin Kwon, "Reinforcement Learning Based Communication Relay for Small Indoor Robots," International Journal of Modeling and Optimization, vol. 14, no. 2, pp. 88-93, 2024.

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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