Journal of Machine and Computing

DNN-Based Relative Localization Technique for Real-Time Positioning of Moving Unmanned Swarm Robots

Journal of Machine and Computing

Received On : 31 August 2023

Revised On : 02 November 2023

Accepted On : 18 March 2024

Published On : 05 April 2024

Volume 04, Issue 02

Pages : 504-511


The unmanned swarm robot system, which enables multiple robots to collaborate and perform a variety of tasks, is extensively researched for its potential applications. Accurate determination of the location of swarm robots during operation is of paramount importance, and various positioning algorithms are employed to achieve this. Specifically, in situations where global positioning system (GPS) signals are unavailable, fixed anchor nodes with known location information can be utilized for localization. However, in scenarios where fixed anchor nodes are not present, and the robots operate in a swarm, applying this technology poses challenges, necessitating a localization technique that relies solely on distance information between the robots. This paper proposes a deep neural network (DNN) technique that utilizes only the distance information between moving nodes to predict the real-time relative coordinates of each node. It is assumed that the distances between nodes are updated sequentially and periodically according to a predetermined measurement cycle. A grid-based localization technique is used as the existing method for performance comparison. Computer simulation results demonstrate that the proposed DNN-based relative Localization technique exhibits superior localization performance compared to the existing Grid-based method. Furthermore, the proposed technique shows similar performance regardless of the distance measurement cycle, indicating that it is not significantly affected by the cycle. Therefore, applying the proposed relative Localization algorithm to swarm robots could enable real-time and accurate relative positioning, facilitating precise location tracking of the swarm.


Relative Localization, Deep Neural Network, Distance, Swarm Robots, Moving Nodes.

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The authors would like to thank to the reviewers for nice comments on the manuscript.


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In-Young Hyun, Seung-Mi Yun and Eui-Rim Jeong, “DNN-Based Relative Localization Technique for Real-Time Positioning of Moving Unmanned Swarm Robots", pp. 504-511, April 2024. doi: 10.53759/7669/jmc202404048.


© 2024 In-Young Hyun, Seung-Mi Yun and Eui-Rim Jeong. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.