| Summary: | This report delves into the utilization of computer vision methods for localizing drones within a swarm formation, particularly in scenarios where communication between drones is disrupted or jammed, necessitating alternative localization techniques. Employing object detection, pose estimation, and other computer vision methodologies, the study aims to derive global coordinates crucial for directing drone movement. The primary objective is to devise a cost-effective algorithm applicable across all drones, with computational tasks centralized on a PC rather than the drones themselves. Central to this research is the exploration of visual sensors as a viable solution for drone localization in the absence of reliable communication channels. By addressing the challenges of jammed communication, this study seeks to establish a robust framework for drone localization within swarm formations, thereby enhancing coordination and resilience in drone operations.
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