A Trajectory-based Flight Assistive System for Novice Pilots in Drone Racing Scenario

Drone racing has become a popular international competition and has attained wide attention in recent years. However, the requirements of high-level operation keep the novice pilots away from participating in it. This paper presents a trajectory-based flight assistive system that enables various operators to fly the drone in a racing scene at a high speed. The whole system is structured hierarchically, consisting of both offline and online components. In the offline part, a global time-optimal trajectory is generated as the expert reference, and a dense flight corridor is constructed to provide sufficiently large safe region. In the online part, a remote control-mapped primitive is designed to fast encapsulate pilots’ inputs, and the time mapping based trajectory progress is customized to further capture intention. Then, a trajectory planner is proposed to generate intention-aligned, smooth, feasible, and safe trajectories periodically. Additionally, a yaw planning that provides the pilot with the best suitable view angle is employed to further alleviate the operation difficulty. Simulations and real world experiments are implemented to verify the performance of our system. The maximum flight speed can reach 6.0 m/s for a novice drone pilot in a real racing scene. Our code is released as an open-source package
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