In the UAV distribution center, the use of unmanned vehicles as the UAV carrier platform can perfectly compensate for the short time that UAVs are in the air, while saving manpower and material resources, autonomously completing navigation and obstacle avoidance in known environments, and at the same time. With human-computer interaction function, it provides target tracking ability, which greatly facilitates the centralized and distributed management of UAVs. In this paper, slam and yolo algorithms are utilized to implement automatic visual tracking of autonomous unmanned aerial vehicles (UAVs) and to achieve collaboration between UAVs and unmanned aerial vehicles (UAVs) in a known experimental environment.
Autonomous Unmanned Vehicle Automatic Visual Tracking Based on SLAM and YOLO Algorithm
Lect. Notes Electrical Eng.
International Conference on Man-Machine-Environment System Engineering ; 2024 ; Beijing, China October 18, 2024 - October 20, 2024
2024-09-29
8 pages
Article/Chapter (Book)
Electronic Resource
English
autonomous navigation and obstacle avoidance , Air-ground coordination , target tracking Artificial Intelligence , Manufacturing, Machines, Tools, Processes , Environmental Engineering/Biotechnology , Engineering , Aerospace Technology and Astronautics , Engineering Economics, Organization, Logistics, Marketing
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