Path Planning for a Dubins Agent with Resource Constraints and Dynamic Obstacles

Alan Cortez, Bryce Ford, Indranil Nayak, Sriram Narayanan, Mrinal Kumar

Abstract: This paper considers path planning with resource constraints and dynamic obstacles for an unmanned aerial vehicle (UAV), modeled as a Dubins agent. Ice data from the Aviation Weather Service was employed to create training data sets for learning dynamic weather (ice) phenomena. Dynamic mode decomposition (DMD) was used to learn and propagate the evolution of ice conditions at flight level. These obstacles were integrated into a Hybrid A* path-planner with backtracking to handle resource constraints. It is shown through numerical simulations that the agent is able to navigate around the dynamic obstacles to find the minimum time path to its goal.