Autonomous Formation Flight Control of Large-Sized Flapping-Wing Flying Robots Based on Leader–Follower Strategy

Birds in nature exhibit excellent long-distance flight capabilities through formation flight,which could reduce energy consumption and improve flight efficiency.Inspired by the biological habits of birds,this paper proposes an autonomous formation flight control method for Large-sized Flapping-Wing Flying Robots(LFWFRs),which can enhance their search range and flight efficiency.First,the kinematics model for LFWFRs is established.Then,an autonomous flight controller based on this model is designed,which has multiple flight control modes,including attitude stabilization,course keeping,hovering,and so on.Second,a formation flight control method is proposed based on the leader–follower strategy and periodic characteristics of flapping-wing flight.The up and down fluctuation of the fuselage of each LFWFR during wing flapping is considered in the control algorithm to keep the relative distance,which overcomes the trajectory divergence caused by sensor delay and fuselage fluctuation.Third,typical formation flight modes are realized,including straight formation,circular formation,and switching formation.Finally,the outdoor formation flight experiment is carried out,and the proposed autonomous formation flight control method is verified in real environment.

Multitarget tracking control algorithm under local information selection interaction mechanism

This study focuses on the problem of multitarget tracking.To address the existing problems of current tracking algorithms,as manifested by the time consumption of subgroup separation and the uneven group size of unmanned aerial vehicles(UAVs)for target tracking,a multitarget tracking control algorithm under local information selection interaction is proposed.First,on the basis of location,number,and perceived target information of neighboring UAVs,a temporary leader selection strategy is designed to realize the local follow-up movement of UAVs when the UAVs cannot fully perceive the target.Second,in combination with the basic rules of cluster movement and target information perception factors,distributed control equations are designed to achieve a rapid gathering of UAVs and consistent tracking of multiple targets.Lastly,the simulation experiments are conducted in two-and three-dimensional spaces.Under a certain number of UAVs,clustering speed of the proposed algorithm is less than 3 s,and the equal probability of the UAV subgroup size after group separation is over 78%.