Citation
Abstract
Unmanned aerial vehicle (UAV) usage is increasing drastically worldwide as UAVs are used in various industries for many applications, such as inspection, logistics, agriculture, and many more. This is because performing a task using UAV makes the job more efficient and reduces the workload needed. However, for a UAV to be operated manually or autonomously, the UAV must be equipped with proper safety features. An anti-collision system is one of the most crucial and fundamental safety features that UAVs must be equipped with. The anti-collision system allows the UAV to maintain a safe distance from any obstacles. The anti-collision technologies are of crucial relevance to assure the survival and safety of UAVs. Anti-collision of UAVs can be varied in the aspect of sensor usage and the system’s working principle. This article provides a comprehensive overview of anti-collision technologies for UAVs. It also presents drone safety laws and regulations that prevent a collision at the policy level. The process of anti-collision technologies is studied from three aspects: Obstacle detection, collision prediction, and collision avoidance. A detailed overview and comparison of the methods of each element and an analysis of their advantages and disadvantages have been provided. In addition, the future trends of UAV anti-collision technologies from the viewpoint of fast obstacle detection and wireless networking are presented.
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Official URL or Download Paper: https://www.mdpi.com/1424-8220/23/15/6810
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Engineering Institute of Tropical Forestry and Forest Products |
DOI Number: | https://doi.org/10.3390/s23156810 |
Publisher: | MDPI |
Keywords: | Anti-collision methods; Detection system; Sensors; Unmanned aerial vehicle; Industry; Innovation and infrastructure |
Depositing User: | Mohamad Jefri Mohamed Fauzi |
Date Deposited: | 16 Oct 2024 02:51 |
Last Modified: | 16 Oct 2024 02:51 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/s23156810 |
URI: | http://psasir.upm.edu.my/id/eprint/110303 |
Statistic Details: | View Download Statistic |
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