Time-Coordinated Path Following for Multiple Agile Fixed-Wing UAVs with End-Roll Expectations

This paper presents a control strategy for multiple unmanned aerial vehicle systems(multi-UAVs)time-coordinated path following with desired endpoint roll attitudes.It utilizes the strong maneuvering capabilities of agile fixed-wing UAVs and incorporates an end-roll expectation.The strategy consists of four steps:time-coordinated control,position control,roll angle planning and attitude control.The position and attitude controllers exhibit Lyapunov exponential stability.The time-coordinated controller addresses the synchronization problem by adjusting the speed based on the coordinated state to achieve progress adjustment.The position controller operates based on the cross-track error and altitude error in the Gravity-Referenced Moving frame.By employing an optimization approach and designing a penalty function,the roll angle sequence is computed.The attitude inner-loop control operates in the SO(3)space and allows for control of large deviations.High-fidelity simulation validates the effectiveness of the proposed method,with normalized coordination error and following error controlled within 2%and 1.2m.

无人–有人机协同控制关键问题

无人–有人机协同是适应无人机快速发展,提升对抗条件下无人机实战化能力的必由之路;是实现优势互补,形成新型高效作战体系的有效途径;也是确保武器控制在人手中的重要保障.无人–有人机协同运用的核心是协同控制,即通过人(飞行员)最小监督下无人机与有人机的自主协同,达成"1+1> 2"的作战效能.本文分析了无人–有人机协同控制的发展现状,基于"观察–判断–决策–行动(OODA)"任务回路,针对内回路的多机自主协同、外回路的人机智能协同,系统梳理了协同控制技术体系,并展望了下一步的研究重点.

Adaptive level of autonomy for human-UAVs collaborative surveillance using situated fuzzy cognitive maps

Collaborating with a squad of Unmanned Aerial Vehicles(UAVs)is challenging for a human operator in a cooperative surveillance task.In this paper,we propose a cognitive model that can dynamically adjust the Levels of Autonomy(LOA)of the human-UAVs team according to the changes in task complexity and human cognitive states.Specifically,we use the Situated Fuzzy Cognitive Map(Si FCM)to model the relations among tasks,situations,human states and LOA.A recurrent structure has been used to learn the strategy of adjusting the LOA,while the collaboration task is separated into a perception routine and a control routine.Experiment results have shown that the workload of the human operator is well balanced with the task efficiency.

Consensus disturbance rejection control of directed multi-agent networks with extended state observer

This paper investigates the consensus disturbance rejection problem among multiple high-order agents with directed graphs.Based on disturbance observers,distributed consensus disturbance rejection protocols are constructed in leaderless and leader-follower consensus setups.Different from the previous related papers,the consensus protocols in this paper are developed in a fully distributed fashion,relying on only the state information of each agent and its neighbors.Sufficient conditions are provided to guarantee that the asymptotic stability of high-order multi-agent systems can be reached with matched disturbances.

Topological Similarity-Based Multi-Target Correlation Localization for Aerial-Ground Systems

In this paper,an algorithm for solving the multi-target correlation and co-location problem of aerial-ground heterogeneous system is investigated.Aiming at the multi-target correlation problem,the fusion algorithm of visual axis correlation method and improved topological similarity correlation method are adopted in view of large parallax and inconsistent scale between the aerial and ground perspectives.First,the visual axis was preprocessed by the threshold method,so that the sparse targets were initially associated.Then,the improved topological similarity method was used to further associate dense targets with the relative position characteristics between targets.The shortcoming of dense target similarity with small di®erence was optimized by the improved topological similarity method.For the problem of colocation,combined with the multi-target correlation algorithm in this paper,the triangulation positioning model was used to complete the co-location of multiple targets.In the experimental part,simulation experiments and°ight experiments were designed to verify the e®ectiveness of the algorithm.Experimental results show that the proposed algorithm can e®ectively achieve multi-target correlation positioning,and that the positioning accuracy is obviously better than other positioning methods.

UAV low-altitude obstacle detection based on the fusion of LiDAR and camera

In this paper,aiming at the flying scene of the small unmanned aerial vehicle(UAV)in the low-altitude suburban environment,we choose the sensor configuration scheme of LiDAR and visible light camera,and design the static and dynamic obstacle detection algorithms based on sensor fusion.For static obstacles such as power lines and buildings in the low-altitude environment,the way that image-assisted verification of point clouds is used to fuse the contour information of the images and the depth information of the point clouds to obtain the location and size of static obstacles.For unknown dynamic obstacles such as rotary-wing UAVs,the IMM-UKF algorithm is designed to fuse the distance measurement information of point clouds and the high precision angle measurement information of image to achieve accurate estimation of the location and velocity of the dynamic obstacles.We build an experimental platform to verify the effectiveness of the obstacle detection algorithm in actual scenes and evaluate the relevant performance indexes.