Elevation Based Outdoor Navigation with Coordinated Heterogeneous Robot Team

Today, the use of heterogeneous robot teams is increasing in military operations and monitoring the environment. However, single 2D autonomous navigation systems fail in rough terrains. In this study, a solution to this problem is proposed using 2.5D navigation that takes into account the slopes on the elevation map. Using ROS and Gazebo, we coordinate drones and ground vehicles to process terrain elevations. The simulation world used in the study reflects a real-world rough terrain and also some urban artifacts are added to the simulation world. Husky simulation model is used as the ground vehicle utilizing 3D LIDAR, GPS and 9 DOF IMU sensors, which can output 3D map and 3D localization using 3D SLAM. Using the SLAM localization, a 2.5D map is created on the ground vehicle. Drone simulation model, similarly equipped, follows the ground vehicle with a GPS-based waypoint navigation and can create a 2.5D map using its sensors. A global plan is created for the ground vehicle by cooperative effort of both robots, using the map information from ground vehicle where available and using the map information from the drone where ground vehicle’s map is insufficient. 2.5D navigation of the ground vehicle is carried out by the local planner taking into account the calculated cooperative global path. Proposed method results in shorter routes and fewer path planning issues. This is shown by the comparative analysis where the ground vehicle or the drone is used alone.