Geofenced Unmanned Aerial Robotic Defender for Deer Detection and Deterrence (GUARD)
Journal:
arXiv
Published Date:
May 16, 2025
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.
