Computationally Efficient Trajectory Generation for Fully Actuated Multirotor Vehicles

Abstract

This paper presents a computationally efficient method of generating state-to-state trajectories for fully actuated multirotor vehicles. The approach consists of computing translational and rotational motion primitives that guide the vehicle from any initial state, defined by position, velocity, and attitude, to any end state in a given time, and subsequently verifying the motion primitives’ feasibility. Computationally lightweight motion primitives for which closed-form solutions exist are presented and an efficient method to test their feasibility is derived. The algorithm is shown to be able to generate trajectories and verify their feasibility within a few microseconds and can thus be used as an implicit feedback law or in high-level path planners that involve evaluating a large number of possible trajectories to achieve some high-level goal. The algorithm's performance is analyzed by comparing it with time-optimal trajectories. An experimental demonstration that requires the computation of trajectories for a large set of end states in real time is used to evaluate the approach.