Vision-Based Tracking and Following of a Moving Target Using an Unmanned Aerial Vehicle
This work introduces an autonomous system for mobile target tracking and follow ing using vision-based (RGB) uni-modal data, specifically designed for unmanned aerial vehicles (UAVs) and enhanced by multi-target information. It addresses the gap in current research by applying state-of-the-art multi...
| Autor: | |
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10256/28363 |
| Acceso en línea: | http://hdl.handle.net/10256/28363 https://hdl.handle.net/10256/28363 |
| Access Level: | acceso abierto |
| Palabra clave: | Autonomous aerial vehicles Vehicles aeris autònoms UAV (Vehicle aeri no tripulat) Drone aircraft Object tracking (Computer vision) Pattern recognition systems Patrons, Sistemes de reconeixement de Algorithms Algorismes Seguiment d’objectes (visió per computador) |
| Sumario: | This work introduces an autonomous system for mobile target tracking and follow ing using vision-based (RGB) uni-modal data, specifically designed for unmanned aerial vehicles (UAVs) and enhanced by multi-target information. It addresses the gap in current research by applying state-of-the-art multi-object tracking (MOT) techniques to target following scenarios, moving beyond traditional single-object tracking (SOT) methods. The system combines the real-time object detector YOLOv8 with MOT algorithms BoT-SORT and ByteTrack to extract and uti lize multi-target data, improving re-identification performance and reducing ID switches, especially under partial or full occlusions in dynamic environments. A 3D flight control mechanism is implemented to enable responsive target following, maintaining line-of-sight despite changes in target speed or direction. The system is validated through simulation testing, demonstrating accurate and robust track ing that effectively differentiates the intended target from surrounding bystanders. By tackling key challenges, this work paves the way for practical UAV applications in vision-based target following using multi-target information. |
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