基于操控技能映射的扑翼机器人自主飞行控制

The complicated aerodynamics of bionic flapping-wing flying robots made accurate modeling challenging and pre-sented a significant hurdle for autonomous flight control. Using this information as a foundation, this research proposes an autonomous flight control method for flapping-wing flying robots that mimics the control behavior of the operator and incorporates control skills into the control algorithm. This method enables autonomous flight control in a variety of scenarios without an accurate dynamics model. Experiments are used to develop a mapping relationship be-tween the control behavior of the operator and the robot’s flight state. The state identification and control mode of the operator is translated into a skill library, and the control methods of maneuvering flight, such as pointing flight, straight-line trajectory tracking, circular flight, and obstacle avoidance flight in constrained space are designed. The control value is produced by mimicking the operator’s control behavior and combined with sensor fusion to generate the control decisions that match to the skill library. Finally, a flight controller is developed and integrated with the flapping-wing flying robot to conduct outdoor flight experiments to validate the proposed method. The results show that reliable flight control can be achieved by imitating the operator’s control behavior with strong flexibility and scalability.