Vehicle navigation in off-road environments is challenging due to terrain uncertainty. Various approaches that account for factors such as terrain trafficability, vehicle dynamics, and energy utilization have been investigated. However, these are not sufficient to ensure safe navigation of optionally manned ground vehicles that are prone to detection using thermal infrared (IR) seekers in combat missions. This work is directed towards the development of a vehicle IR signature aware navigation stack comprised of global and local planner modules to realize safe navigation for optionally manned ground vehicles. The global planner used A* search heuristics designed to find the optimal path that minimizes the vehicle thermal signature metric on the map of terrain’s apparent temperature. The local planner used a model-predictive control (MPC) algorithm to achieve integrated motion planning and control of the vehicle to follow the path waypoints provided by the global planner. Vehicle apparent temperature-aware kinodynamic motion planning MPC was developed to minimize the vehicle thermal signature metric -- while respecting local mobility constraints due to the terrain grade to prevent vehicle rollover. Additionally, a surface energy model with the inclusion of a vegetation layer was developed to simulate the apparent temperature of the background terrain. The effectiveness of the developed algorithm is demonstrated for the scenario where the adversarial threat perspective is assumed to be from the top looking down at the vehicle.
