A Time-Varying Hybrid Model for Dynamic Motion Planning of an Unmanned Air Vehicle
Joseph Kehoe, Adam S. Watkins, Rick Lind · AIAA Guidance, Navigation, and Control Conference and Exhibit · 2006
Future unmanned aerial vehicle (UAV) missions are likely to include those for which the characteristic dimensions of the environment are similar in scale to the characteristic dimensions of the vehicle dynamics. This class of missions will require precision trajectory planning and tracking that utilizes the full agility of the vehicle to ensure safety and performance. Hybrid models consisting of a set motion primitives allow for the safe integration of aggressive maneuvers into a motion plan; however, planning precision is limited by the finite set of primitives. This paper presents an extension of existing hybrid modeling strategies to allow for a variable set of motion primitives that are tailored to the current mission-performance requirements. A randomized sampling-based planning approach is then adopted to plan trajectories using this modeling strategy. Performance of the resulting trajectory-planning system is demonstrated through a simulated example.