Efficient robot tracking system using single-image-based object detection and position estimation

This study proposes a mother-slave robot tracking system that identifies the target, predicts its location, and tracks it based on a single image. The proposed system utilizes a Convolutional Neural Network (CNN) for object detection, to identify the target robot. The distance and angle between the...

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Bibliographic Details
Published inICT express Vol. 10; no. 1; pp. 125 - 131
Main Authors Lim, Dongsun, Kim, Jonghoek, Kim, Hyuntai
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.02.2024
Elsevier
한국통신학회
Subjects
Deep learning
Image processing
Linear regression tracking
PID control
전자/정보통신공학
Deep learning
Linear regression tracking
PID control
Image processing
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Summary:This study proposes a mother-slave robot tracking system that identifies the target, predicts its location, and tracks it based on a single image. The proposed system utilizes a Convolutional Neural Network (CNN) for object detection, to identify the target robot. The distance and angle between the robots are then calculated through linear regression analysis, which offers a more efficient and cost-effective solution than traditional methods. The performance of the system was evaluated, resulting in an accuracy of 99.59% for object detection, and an average distance error of 2.04% for the estimated location.
ISSN:2405-9595
2405-9595
DOI:10.1016/j.icte.2023.07.009