Near minimum-time trajectories for quadrotor UAVs in complex environments

Abstract

This paper presents a heuristic framework that generates trajectories for quadrotor UAVs in complex environments that smoothly follow a series of waypoints with desired boundary states on the derivatives. The waypoints can be chosen manually or found using a sampling-based path planner such as RRT for complex environments with obstacles. A trajectory in the virtual domain is found using polynomials parametrised by an abstract argument that are numerically optimised to give the shortest geometrical path length. A mapping function is used to ensure the kinodynamic limits on the velocity and acceleration throughout the trajectory are satisfied. The mapping function is found heuristically with an algorithm that minimises the trajectory time.