Data Model and Simulation for Persistent Mission Planning with Energy-Sharing Autonomous Ground and Air Vehicles

We introduce the Energy-Aware Mission Planning (EAMP) problem in the context of long-endurance robotic deployments using a mixture of ground and air vehicles. Unmanned ground and air vehicles have complementary strengths, namely long battery life in the ground vehicles and maneuverability in the air vehicles. To facilitate coordinated mission planning that allows the air vehicles to dock and recharge on the ground vehicles, we introduce a routing problem and specification of solver inputs and outputs. We then incorporate a solver from the literature to create plans for a realistic scenario, and show the results in a simulated 72 h deployment.