Joint mission and route planning of unmanned air vehicles via a learning-based heuristic

Unmanned air vehicles(UAVs) have been regularly employed in modern wars to conduct different missions. Instead of addressing mission planning and route planning separately,this study investigates the issue of joint mission and route planning for a fleet of UAVs. The mission planning determines the configuration of weapons in UAVs and the weapons to attack targets, while the route planning determines the UAV’s visiting sequence for the targets. The problem is formulated as an integer linear programming model. Due to the inefficiency of CPLEX on large scale optimization problems, an effective learningbased heuristic, namely, population based adaptive large neighborhood search(P-ALNS), is proposed to solve the model. In P-ALNS, seven neighborhood structures are designed and adaptively utilized in terms of their historical performance. The effectiveness and superiority of the proposed model and algorithm are demonstrated on test instances of small, medium and large sizes. In particular, P-ALNS achieves comparable solutions or as good as those of CPLEX on small-size(20 targets)instances in much shorter time.

INTEGRATED DESIGN OF AN ELECTRIC POWERED UNMANNED AIR VEHICLE USING CONCURRENT SUBSPACE DESIGN

The concurrent subspace design (CSD) framework has been used to conduct a preliminary design optimization of an electric powered, unmanned air vehicle (EPUAV) operating at a low Reynolds number. A multidisciplinary system analysis that includes aerodynamics, weights, propulsion, performance and stability and control has been developed for this class of vehicles. The CSD framework employs artificial neural network based response surfaces to provide approximations to the design space. The EPUAV system includes 25 continuous and 4 discrete design variables. The CSD framework was able to identify feasible designs with significant weight reductions relative to any previously considered (i.e. initial database) designs. This was accomplished with a limited number of system analyses. The results also demonstrate the nature of this design framework adaptive to changes in design requirements.

Weapon configuration, allocation and route planning with time windows for multiple unmanned combat air vehicles

Unmanned combat air vehicles(UCAVs) mission planning is a fairly complicated global optimum problem. Military attack missions often employ a fleet of UCAVs equipped with weapons to attack a set of known targets. A UCAV can carry different weapons to accomplish different combat missions. Choice of different weapons will have different effects on the final combat effectiveness. This work presents a mixed integer programming model for simultaneous weapon configuration and route planning of UCAVs, which solves the problem optimally using the IBM ILOG CPLEX optimizer for simple missions. This paper develops a heuristic algorithm to handle the medium-scale and large-scale problems. The experiments demonstrate the performance of the heuristic algorithm in solving the medium scale and large scale problems. Moreover, we give suggestions on how to select the most appropriate algorithm to solve different scale problems.

An Air Route Planning Model of Unmanned Aerial Vehicles Under Constraints of Ground Safety

With the rapid growth of the number and flight time of unmanned aerial vehicles(UAVs),safety accidents caused by UAVs flight risk is increasing gradually.Safe air route planning is an effective means to reduce the operational risk of UAVs at the strategic level.The optimal air route planning model based on ground risk assessment is presented by considering the safety cost of UAV air route.Through the rasterization of the ground surface under the air route,the safety factor of each grid is defined with the probability of fatality on the ground per flight hour as the quantitative index.The air route safety cost function is constructed based on the safety factor of each grid.Then,the total cost function considering both air route safety and flight distance is established.The expected function of the ant colony algorithm is rebuilt and used as the algorithm to plan the air routes.The effectiveness of the new air route planning model is verified through the logistical distribution scenario on urban airspace.The results indicate that the new air route planning model considering safety factor can greatly improve the overall safety of air route under small increase of the total flight time.

Research on Water-Exit and Take-off Process for Morphing Unmanned Submersible Aerial Vehicle

This paper presents a theoretic implementation method of Morphing Unmanned Submersible Aerial Vehicle （MUSAV）, which can both submerge in the water and fly in the air. Two different shapes are put forward so that the vehicle can suit both submergence and flight, considering the tremendous differences between hydrodynamic configuration and aerodynamic configuration of a vehicle. The transition of the two shapes can be achieved by using morphing technology. The water-to-air process, including water-exit, morphing, take-off and steady flight, is analyzed. The hydrodynamic and aerodynamic model of the vehicle exiting the water surface obliquely and then taking off into the air has been founded. The control strategy after morphing is analyzed and the control method is given. Numerical method is used to validate the motion model of the water-exit process. Results of simulations show the validity of the proposed model and the feasibility of MUSAV in theory.

Unmanned Aerial Vehicles Flight Safety Improvement Using In-Flight Awareness

This paper presents a novel onboard system called In-Flight Awareness Augmentation System (IFA2S) to improve flight safety. IFA2S is designed to semi-automatically (with human supervision) avoid hazards and accidents due to either internal or external causal factors. The requirements were defined in an innovative way using Systems-Theoretic Process Analysis (STPA) method and applied next to model the system. IFA2S increases aircraft awareness regarding both itself and its environment and, at the same time, recognizes platform and operational constraints to act in accordance to predefined decision algorithms. Results are presented through simulations and flight tests using state machines designed to allow the adoption of appropriate actions for the identified hazards. The different decision algorithms are evaluated over as many as possible hazard situations by simulations conducted with software Labview and XPlane flight simulator. Flight tests are performed in a small fixed wing aircraft and make use of a limited version IFA2S, partially attending identified requirements. Results support the conclusion that IFA2S is capable of improving flight safety.

Optimal confrontation position selecting games model and its application to one-on-one air combat

In the air combat process,confrontation position is the critical factor to determine the confrontation situation,attack effect and escape probability of UAVs.Therefore,selecting the optimal confrontation position becomes the primary goal of maneuver decision-making.By taking the position as the UAV’s maneuver strategy,this paper constructs the optimal confrontation position selecting games(OCPSGs)model.In the OCPSGs model,the payoff function of each UAV is defined by the difference between the comprehensive advantages of both sides,and the strategy space of each UAV at every step is defined by its accessible space determined by the maneuverability.Then we design the limit approximation of mixed strategy Nash equilibrium(LAMSNQ)algorithm,which provides a method to determine the optimal probability distribution of positions in the strategy space.In the simulation phase,we assume the motions on three directions are independent and the strategy space is a cuboid to simplify the model.Several simulations are performed to verify the feasibility,effectiveness and stability of the algorithm.

基于无人机巡检与深度学习的河道整治施工进度图像识别

长线性小流域治理工程中的河道衬砌、生态护岸等距离长、范围广、布置分散,且工区交通不便,人工巡检费时费力,难以及时掌握工程的整体施工进度形象面貌。提出了基于无人机巡检与深度学习的河道整治施工进度智能图像识别方法,通过定位施工节点(施工区域起点和终点)的位置计算施工进度。首先,建立了施工区域目标检测模型,针对无人机航拍影像进行河道衬砌护岸施工区域的识别以及施工节点的定位;然后,利用尺度不变特征变换(scale-invariant feature transform,SIFT)算法对不同视频帧中的施工节点进行匹配,并基于单目视觉的运动视差法,计算施工节点的实际工区坐标;最后,计算当前衬砌护岸施工进度,并分析进度偏差。结果表明:该方法得到的施工节点定位平均误差为1.026 m,平均相对误差为0.74%,该方法能够较为准确地从航拍图像中识别得到当前衬砌护岸的施工进程,从而实现长线性工区快速巡检,及时掌控现场施工进度,提高工程管理的智能化水平。

跨介质航行器动力学前沿技术研究进展

近年来跨介质装备受到船舶与海洋、航空航天以及兵器等领域的高度重视,与跨介质航行器相关的总体方案、关键技术、研究方法以及使用效能等成为研究热点。文章阐述了跨介质航行器动力学相关研究背景,综述了航行器入水砰击、出入水流固耦合、跨介质仿生、跨介质动力与推进、新质跨介质装备、跨介质动力学试验与仿真技术等方面的最新研究成果和研究进展,并展望了跨介质航行器发展需要解决的若干前沿关键技术,以期为促进海空界面动力学与无人系统研究提供借鉴。

基于分组教与学的无人战斗机自适应路径规划

针对无人战斗机(unmanned combat air vehicle,UCAV)处于存在威胁区域的战场中路径规划问题,提出一种基于分组教与学算法的UCAV自适应路径规划方法。通过分析UCAV路径评价指标,提出一种自适应的UCAV路径评价模型,根据作战环境规划出距离短、威胁小的任务路径。针对教与学算法寻优精度低、耗时长的问题,提出一种分组教与学算法,引入动态分组和高斯分布扰动策略,提高算法寻优性能。通过仿真实验,该方案求解的最优路径更短且安全。

Unmanned air/ground vehicles heterogeneous cooperative techniques:Current status and prospects

Multiple unmanned air/ground vehicles heterogeneous cooperation is a novel and challenging filed.Heterogeneous cooperative techniques can widen the application fields of unmanned air or ground vehicles,and enhance the effectiveness of implementing detection,search and rescue tasks.This paper mainly focused on the key issues in multiple unmanned air/ground vehicles heterogeneous cooperation,including heterogeneous flocking,formation control,formation stability,network control,and actual applications.The main problems and future directions in this field were also analyzed in detail.These innovative technologies can significantly enhance the effectiveness of implementing complicated tasks,which definitely provide a series of novel breakthroughs for the intelligence,integration and advancement of future robot systems.

Unmanned air vehicle flow separation control using dielectric barrier discharge plasma at high wind speed

The present paper described an experimental investigation of separation control of an Unmanned Aerial Vehicle(UAV)at high wind speeds.The plasma actuator was based on Dielectric Barrier Discharge(DBD)and operated in a steady manner.The flow over a wing of UAV was performed with smoke flow visualization in theΦ0.75 m low speed wind tunnel to reveal the flow structure over the wing so that the locations of plasma actuators could be optimized.A full model of the UAV was experimentally investigated in theΦ3.2 m low speed wind tunnel using a six-component internal strain gauge balance.The effects of the key parameters,including the locations of the plasma actuators,the applied voltage amplitude and the operating frequency,were obtained.The whole test model was made of aluminium and acted as a cathode of the actuator.The results showed that the plasma acting on the surface of UAV could obviously suppress the boundary layer separation and reduce the model vibration at the high wind speeds.It was found that the maximum lift coefficient of the UAV was increased by 2.5%and the lift/drag ratio was increased by about 80%at the wind speed of 100 m/s.The control mechanism of the plasma actuator at the test configuration was also analyzed.

基于通信信号管制的城市空中交叉口设计研究

为确保城市低空空域内无人机规模化运行安全,缓解低空交通运行瓶颈,本文借鉴地面交通较为成熟的研究成果,结合城市低空及无人机运行特色,提出一种基于通信信号管制的城市空中交叉口设计模型。首先,考虑航路构型设计与航路运行主体,构建无人机运行所需的城市低空航路。其次,从进出口道、冲突响应距离2方面对空中交叉口几何结构进行设计,再从进口航道划分、通信信号管制、无人机高度调整3方面对交通组织进行设计,实现对空中交叉口的基本模型设计。最后,设置仿真实验验证该模型的可行性,并分析不同参数组合下的交叉口综合通行效率。实验结果表明:当飞行速度为18 m/s,纵向间隔为50 m,管制信号周期时长为226 s时,综合通行效率达到最佳。本研究可为未来城市空中交通航路网络精细划设与管理提供支撑,增强低空无人机交通的实践性。

基于需求的城市低空无人机航路网络构建方法

针对城市低空无人机运行需求不断增加的问题,综合考虑城市区域交通需求、空域环境以及无人机性能等限制条件,以最小化网络节点、最大化覆盖需求点和需求量为目标,提出了一种城市低空无人机航路网络构建方法.建立网络节点生成模型和航路网络构建模型;通过改进的greedy算法生成网络节点;结合使用k近邻(k-Nearest Neighbor,K-NN)和Prims算法构建无人机航路网络;选取上海地区物流业务需求量数据进行仿真验证,并运用复杂网络相关指标分析所构建的航路网络性能.结果表明:本文提出的城市低空无人机航路网络构建方法可以同时实现干线和支线航路网络的构建,且干线航路网络实现了网络全连通,还可以结合无人机任务需求设置网络节点实现航路网络灵活规划.

无人机辅助智能边缘网络技术综述

简要介绍了无人机作为空基信息平台的主要应用场景,结合6G多接入网络和用户为中心网络架构,讨论了无人机在构建智能边缘网络中的重要作用。结合无人机平台在不同场景下的通、感、算能力特点,介绍无人机自组网、无人机通感一体化、无人机边缘计算等无人机辅助智能边缘网络关键技术。最后,围绕无人机在构建智能边缘网络过程中与无线接入网新技术结合时产生的新问题,探讨无人机通信信道建模、三维立体部署与路径规划、携能有限与续航问题、无人机网络安全、无人机集群异构网络融合等关键技术挑战和未来研究方向。

基于自由空间光的无人机通信网络关键技术与发展趋势

在当前电磁频谱拥堵和无线电干扰严重的情况下,基于自由空间光(FSO)的无人机(UAV)通信网络作为推进空天地一体化进程的重要一环,得到了学术界和工业界的广泛关注。与传统射频通信相比,FSO通信具有高数据传输速率、低时延和高安全性等优势。然而,FSO链路易受大气信道条件影响,同时UAV高移动性、网络高动态性以及机载资源的有限性给FSO的稳定连接与可靠通信带来了巨大挑战。因此,该文在介绍了FSO传输特性的基础上,着重分析了提升基于FSO的UAV通信网络稳定性与通信质量的关键技术,在此基础上,归纳出高可靠、强智能、长续航的发展趋势,以期为基于FSO的UAV通信网络发展提供参考与借鉴。

基于图卷积深度强化学习的协同空战机动决策方法

针对多无人机智能协同空战对抗决策问题,提出了一种基于长短期记忆与竞争图卷积深度强化学习的多机协同空战机动对抗决策方法.首先,对多机协同空战对抗问题进行描述;其次,在竞争Q网络中,引入长短期记忆网络用于处理带有强时序相关性的空战信息,接着,搭建图卷积网络作为多机之间的通信基础,提出基于长短期记忆与竞争图卷积深度强化学习算法的协同空战训练框架,并对协同空战决策训练算法进行了设计.二对一空战仿真结果验证了本文所提出的协同智能对抗决策方法的有效性,其具有决策速度快、学习过程稳定的特点以及适应空战环境快速变化下的协同策略学习能力.

城市低空空中交通及无人机路径规划研究综述

随着城市交通拥堵的日益严重和社会的智能化发展,城市空中交通(UAM)的概念逐步形成。近年来,电动垂直起降(eVTOL)航空器发挥着越来越重要的作用,无人驾驶航空器(简称无人机)在城市低空空域的运行应受到更加有序的管理。简要概述了城市空中交通的基本概念及国内外的发展和应用现状。分别概述了城市低空空域设计概念、城市低空航路规划和城市低空无人机路径规划方法。结合国内外研究现状,从不同方面提出了城市低空空中交通研究展望。

国外无人机空空打击作战典型样式及关键技术研究

无人机在现代战争中正发挥着日益重要的作用。本文针对国外无人机用于现代空空作战的研究进展、典型作战样式及其关键技术进行了分析,梳理分析了当前国外无人机用于空空打击作战的典型装备和技术发展现状,结合当前国外无人机装备发展现状分析了无人机直接应用于空空打击作战的优势和劣势;基于当前国外典型无人机平台性能特点,提出了无人机参与空空打击作战的三类潜在典型应用样式;针对无人机用于空空打击作战的实际需要,分析了无人机应用于未来空空作战的关键支撑性技术。

面向自杀式无人机饱和攻击的海空跨域无人协同反制策略

针对海洋环境下反制自杀式无人机饱和攻击问题,文中研究了目标数量远超我方情况下的海空跨域无人平台协同反制策略,提出一种结合改进的遗传算法与联盟形成博弈的协同算法。首先根据海空跨域无人平台攻击特性与运动特性,结合最大最小策略设计代价函数;然后结合任务需求对遗传算法进行改进,对交叉和变异过程进行引导和限制,在提升遗传算法效率的基础上生成可行的反制方案;最后设计联盟形成规则,通过联盟之间的成员变动使各联盟达到纳什稳定状态,在算子数量较多的情况下仍能使反制方案被持续稳定优化。仿真对比实验表明所提策略具有可行性和优越性,能在目标遭受饱和攻击时提供合理高效的反制方案,可为大规模跨域无人集群作战研究提供参考。