Human Following Robot Based on Object Detection for Aerospace Application

In this research, the Human Following Robot (HFR) prototype has been designed and implemented using YOLO v3-Tiny and Tensor Flow Lite on Raspberry Pi hardware named Rewang. The HFR Rewang is designed to assist aircraft technicians by bringing maintenance tool kits to aircraft shelters. Rewang's movement is based on a camera as a vision sensor following the movement of human entities. Image input is processed by YOLO v3-Tiny through the determination of the bounding box, the calculation of Euclidean Distance, and the determination of the pixel value of the camera as the basis of Rewang's movement which is regulated by an L298N driver motor that controls two Direct Current (DC) motors for the left and right wheels. The test results show that Rewang can move at an average speed of 0.18 m/s at 2 m with a travel time of 11 seconds with a light intensity of more than 250 lux. The minimum and maximum distance of object detection is as far as 120 cm and 400 cm, with an object detection accuracy of 95.8%. Rewang allows the HFR to have a larger carrying capacity to bring more complete aircraft maintenance tools and is prospective for other aerospace and general applications.

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Publication Details

Published
2024-12-11
DOI
https://doi.org/10.1109/icaaeei63658.2024.10899132
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.25
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article

Human Following Robot Based on Object Detection for Aerospace Application

Ika Noer Syamsiana, Arwin Datumaya Wahyudi Sumari, Ndaru Atmi Purnami, Denny Dermawan et al.
1 citations
Robotic Path Planning Algorithms
0.25
article

Human Following Robot Based on Object Detection for Aerospace Application

Ika Noer Syamsiana, Arwin Datumaya Wahyudi Sumari, Ndaru Atmi Purnami, Denny Dermawan, Ahnaf Bagus Aryandika
article en
1 citations

Abstract

In this research, the Human Following Robot (HFR) prototype has been designed and implemented using YOLO v3-Tiny and Tensor Flow Lite on Raspberry Pi hardware named Rewang. The HFR Rewang is designed to assist aircraft technicians by bringing maintenance tool kits to aircraft shelters. Rewang's movement is based on a camera as a vision sensor following the movement of human entities. Image input is processed by YOLO v3-Tiny through the determination of the bounding box, the calculation of Euclidean Distance, and the determination of the pixel value of the camera as the basis of Rewang's movement which is regulated by an L298N driver motor that controls two Direct Current (DC) motors for the left and right wheels. The test results show that Rewang can move at an average speed of 0.18 m/s at 2 m with a travel time of 11 seconds with a light intensity of more than 250 lux. The minimum and maximum distance of object detection is as far as 120 cm and 400 cm, with an object detection accuracy of 95.8%. Rewang allows the HFR to have a larger carrying capacity to bring more complete aircraft maintenance tools and is prospective for other aerospace and general applications.

State University of Malang (ID)
Openalex Percentile: Top 42%
Robotic Path Planning Algorithms
0.25
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Human Following Robot Based on Object Detection for Aerospace Application — Ika Noer Syamsiana, Arwin Datumaya Wahyudi Sumari, et al. · (2024) | TGRS Research Map | TGRS