Geofenced Unmanned Aerial Robotic Defender for Deer Detection and Deterrence (GUARD)

• URL: http://arxiv.org/abs/2505.10770v1
• Date: Fri, 16 May 2025 00:59:31 GMT
• Title: Geofenced Unmanned Aerial Robotic Defender for Deer Detection and Deterrence (GUARD)
• Authors: Ebasa Temesgen, Mario Jerez, Greta Brown, Graham Wilson, Sree Ganesh Lalitaditya Divakarla, Sarah Boelter, Oscar Nelson, Robert McPherson, Maria Gini,
• Abstract summary: Wildlife-induced crop damage, particularly from deer, threatens agricultural productivity.<n>Traditional deterrence methods often fall short in scalability, responsiveness, and adaptability to diverse farmland environments.<n>This paper presents an integrated unmanned aerial vehicle (UAV) system designed for autonomous wildlife deterrence.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Wildlife-induced crop damage, particularly from deer, threatens agricultural productivity. Traditional deterrence methods often fall short in scalability, responsiveness, and adaptability to diverse farmland environments. This paper presents an integrated unmanned aerial vehicle (UAV) system designed for autonomous wildlife deterrence, developed as part of the Farm Robotics Challenge. Our system combines a YOLO-based real-time computer vision module for deer detection, an energy-efficient coverage path planning algorithm for efficient field monitoring, and an autonomous charging station for continuous operation of the UAV. In collaboration with a local Minnesota farmer, the system is tailored to address practical constraints such as terrain, infrastructure limitations, and animal behavior. The solution is evaluated through a combination of simulation and field testing, demonstrating robust detection accuracy, efficient coverage, and extended operational time. The results highlight the feasibility and effectiveness of drone-based wildlife deterrence in precision agriculture, offering a scalable framework for future deployment and extension.

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