This hardware demonstration showcases a fully integrated UAV–UGV system executing cooperative routing and recharging operations in an outdoor environment. The UAV autonomously visits task locations while the UGV navigates on-ground roads to provide energy support through rendezvous-based recharging. The experiment validates our energy-aware replanning framework, demonstrating robust coordination between aerial and ground agents under real-world conditions. 

This demonstration showcases real-world experiments in autonomous robot navigation using GPS and sensor fusion techniques. The robots are guided to visit a set of task points outdoors without relying on pre-mapped environments.

The system integrates GPS data with IMU and odometry inputs through sensor fusion algorithms, enabling the robot to accurately localize itself and follow planned paths. In certain scenarios, SLAM (Simultaneous Localization and Mapping) modules are used for additional precision in semi-structured environments. The resulting setup supports real-time autonomous mission execution, even in GPS-denied zones when supported by SLAM.

Key capabilities include:

• GPS-based waypoint navigation

• Real-time localization using sensor fusion

• Path planning and task point coverage

• SLAM integration for map-building 

Demonstrating autonomous UAV flight with waypoint navigation and precision landing in real-world environments, leveraging computer vision, ArUco markers, and MAVSDK. These experiments highlight robust integration of perception and control for reliable autonomous operations.