UAV Route Planning and Light Searching Method Based on Optical Sensing

Visible light communication (VLC) is a vital solution for information transmission in uncrewed aerial vehicles (UAVs), yet its effectiveness is highly dependent on the accuracy of UAV positioning. A route planning method has been developed to assist an UAV in accurately identifying the communication light source within an Internet of Things (IoT) environment. This method is designed to guide the UAV selecting an appropriate path, executing its flight, and adjusting its flight path by contentiously sensing the intensity of specific light. As the UAV progressively narrows down the search area, it can ultimately identify the effective lighting area under the lighting source. A method for success rate assessment has been proposed, evaluating potential search routes using diverse geometric shapes: triangles, quadrangles, pentagons, hexagons, and circles. Factors that could significantly impact the search success rate and search distance are taken into account, including the lighting radius of the light source, the spatial light distribution based on Lambert coefficient, the geometry of the search path, number of search attempts, and the side length of polygons. Computational results show that the method achieves nearly 100% success when the light source has an emission angle of 37.5°. Although the proposed method requires further consideration of challenges, such as algorithm integration, transmission distance, and diverse application scenarios, it offers a route search method that is both simple and highly successful, effectively mitigating the impact of inaccurate UAV positioning in a VLC-based IoT system.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-03-14
DOI
https://doi.org/10.1109/jiot.2025.3550126
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
2.55
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article

UAV Route Planning and Light Searching Method Based on Optical Sensing

Hua Xiao, Caiming Sun, Wensong Wang
2 citations
IEEE Internet of Things Journal
Robotic Path Planning Algorithms
2.55
article

UAV Route Planning and Light Searching Method Based on Optical Sensing

Hua Xiao, Caiming Sun, Wensong Wang
article en
2 citations

Abstract

Visible light communication (VLC) is a vital solution for information transmission in uncrewed aerial vehicles (UAVs), yet its effectiveness is highly dependent on the accuracy of UAV positioning. A route planning method has been developed to assist an UAV in accurately identifying the communication light source within an Internet of Things (IoT) environment. This method is designed to guide the UAV selecting an appropriate path, executing its flight, and adjusting its flight path by contentiously sensing the intensity of specific light. As the UAV progressively narrows down the search area, it can ultimately identify the effective lighting area under the lighting source. A method for success rate assessment has been proposed, evaluating potential search routes using diverse geometric shapes: triangles, quadrangles, pentagons, hexagons, and circles. Factors that could significantly impact the search success rate and search distance are taken into account, including the lighting radius of the light source, the spatial light distribution based on Lambert coefficient, the geometry of the search path, number of search attempts, and the side length of polygons. Computational results show that the method achieves nearly 100% success when the light source has an emission angle of 37.5°. Although the proposed method requires further consideration of challenges, such as algorithm integration, transmission distance, and diverse application scenarios, it offers a route search method that is both simple and highly successful, effectively mitigating the impact of inaccurate UAV positioning in a VLC-based IoT system.

IEEE Internet of Things JournalVol. 12(12)
Beijing University of Posts and Telecommunications (CN), Chinese University of Hong Kong, Shenzhen (CN), Aerospace Information Research Institute (CN), Guangdong Ocean University (CN)
Sustainable cities and communities
Openalex Percentile: Top 12%
Robotic Path Planning Algorithms
2.55
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