Advanced Camouflaged Target Detection with Quadrapod Drone – A Fusion of Air and Land Technology

Abstract

In order to identify camouflaged objects in challenging situations, we describe a unique system that combines air and land technologies. The platform, known as a quadrapod drone, combines quadrapod flying with legs to conduct intimate inspection at ground level as well as aerial environment. The drone is about being able to fly and walk; it’s about using both abilities to get best possible view of the environments. This fusion of locomotion modes enables the systems to take position itself for optimal target detection in the environments. Data from the sensors are processed by enhanced YOLOv8 and deep learning framework, which has been gets for the challenges of Camouflaged Object Detection. Our detection process combines a hierarchical sensor-fusion module for air- ground collaboration, multiple imaging, and a deep camouflaged object detection backbone. Using a bespoke dataset, we assess the method in mixed-terrain settings and demonstrate enhanced detection recall. The benefits of using an air-land hybrid to the object detection problem are demonstrated by an experimental evaluation, perceptual algorithms, hardware design, and data-fusion approach. The paper presents complete system architecture, details the camouflaged detection framework and outlines a methodology for its future validation. A robot like this has the potential to make real difference in the world, whether it’s making military missions safer, helping find survivors after a disaster or allowing scientists to study hard to find animals in the wild.