Autonomous drone racing is becoming an excellent platform to challenge quadrotors' autonomy techniques including planning, navigation and control technologies. However, most research on this topic mainly focuses on single drone scenarios. In this paper, we describe a novel time-optimal trajectory generation method for generating time-optimal trajectories for a swarm of quadrotors to fly through pre-defined waypoints with their maximum maneuverability without collision. We verify the method in the Gazebo simulations where a swarm of 5 quadrotors can fly through a complex 6-waypoint racing track in a 35m * 35m space with a top speed of 14m/s. Flight tests are performed on two quadrotors passing through 3 waypoints in a 4m * 2m flight arena to demonstrate the feasibility of the proposed method in the real world. Both simulations and real-world flight tests show that the proposed method can generate the optimal aggressive trajectories for a swarm of autonomous racing drones. The method can also be easily transferred to other types of robot swarms.

翻译：自主无人机竞速正成为挑战四旋翼飞行器自主技术（包括规划、导航与控制）的优秀平台。然而，该领域现有研究主要聚焦于单无人机场景。本文描述了一种新颖的时间最优轨迹生成方法，用于生成四旋翼飞行器集群在无碰撞条件下以最大机动性穿越预设航点的时间最优轨迹。我们在Gazebo仿真环境中验证了该方法：5架四旋翼飞行器集群可在35米×35米空间内以14米/秒的最高速度穿越包含6个航点的复杂赛道。通过在4米×2米飞行竞技场中两架四旋翼飞行器穿越3个航点的实际飞行测试，证明了该方法在现实场景中的可行性。仿真与实飞测试均表明，所提方法能为自主竞速无人机集群生成最优激进轨迹。该方法还可便捷迁移至其他类型机器人集群。