Decentralized Vision-Based Autonomous Aerial Wildlife Monitoring

• URL: http://arxiv.org/abs/2508.15038v1
• Date: Wed, 20 Aug 2025 20:05:05 GMT
• Title: Decentralized Vision-Based Autonomous Aerial Wildlife Monitoring
• Authors: Makram Chahine, William Yang, Alaa Maalouf, Justin Siriska, Ninad Jadhav, Daniel Vogt, Stephanie Gil, Robert Wood, Daniela Rus,
• Abstract summary: We propose a decentralized vision-based multi-quadrotor system for wildlife monitoring.<n>Our approach enables robust identification and tracking of large species in their natural habitat.
• Score: 55.159556673975544
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Wildlife field operations demand efficient parallel deployment methods to identify and interact with specific individuals, enabling simultaneous collective behavioral analysis, and health and safety interventions. Previous robotics solutions approach the problem from the herd perspective, or are manually operated and limited in scale. We propose a decentralized vision-based multi-quadrotor system for wildlife monitoring that is scalable, low-bandwidth, and sensor-minimal (single onboard RGB camera). Our approach enables robust identification and tracking of large species in their natural habitat. We develop novel vision-based coordination and tracking algorithms designed for dynamic, unstructured environments without reliance on centralized communication or control. We validate our system through real-world experiments, demonstrating reliable deployment in diverse field conditions.

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