Motion Planning for a Small Aerobatic Fixed-Wing Unmanned Aerial Vehicle

Abstract

A motion planner is developed for guiding a small aerobatic fixed-wing unmanned aerial vehicle to a desired goal region in a highly constrained, three-dimensional, known environment with static obstacles. The planner is based on the Rapidly-Exploring Random Trees (RRT) algorithm, and pieces together feasible trajectories from a library of motion primitives. Among other more conventional motion primitives, the library includes three extreme maneuvers: a cruise-to-hover transition, a hover-to-cruise transition, and an aggressive turn-around. The algorithm is efficient; it can be run in real-time to rapidly generate a plan starting from the aircraft's configuration at run-time. The motion planner is closely coupled to a feedback controller. Simulations using an aircraft dynamics model demonstrate the effectiveness of the system to guide and control the aircraft to a desired goal region. Preliminary flight test results are also presented.