Real-Time Object Tracking on the Edge
Mohana Kundurthi, Tamil Selvan Gurunathan, Md Azim Khan, Muhammad Shehrose Raza, Aryya Gangopadhyay · 2025
This paper presents a real-time detection, tracking, counting, and distance estimation framework deployed on the Boston Dynamics Spot robot, equipped with RGB and thermal cameras. Leveraging edge computing devices such as the NVIDIA Jetson Nano, the system autonomously processes data in dynamic terrains with minimal human intervention. A custom-trained YOLOv8 model, fine-tuned on a unique dataset tailored for military applications, is integrated with the StrongSORT algorithm for object tracking. Additionally, a novel geometric calculation methodology enables precise angle estimation and spatial mapping, enhancing situational awareness. The framework's capabilities include live visualization of detected objects, area-based counting, and mapping within an operational environment using ROS-based tools. Field demonstrations conducted at the Army Research Lab validate the system's effectiveness in processing complex thermal and RGB data in real-time. The proposed solution offers significant potential for enhancing autonomous robotic deployments in mission-critical applications.