Mapping and Tracking

This article presents the implementation of decentralized data fusion (DDF) and cooperative control algorithms on an unmanned aerial system (UAS).We conduct a number of demonstrations with a pair of unmanned aerial vehicles (UAVs) performing an information-gathering mission, and we show that significant benefits can be achieved by enabling cooperation through the sharing of information between members of the team. The objective is to utilize the UAV team to estimate the position and velocity of a number of ground-based features. The UAVs are given some prior knowledge of the feature states and are required to gather further information above a predefined threshold. This situation models a scenario where initial information is made available from an external source (e.g., a high-flying UAV or satellite imagery), which then prompts the start of the feature-localizationmission.     

Pressurized Structures–Based Unmanned Aerial Vehicle Research

Several areas of unmanned aerial vehicle (UAV) performance need to be improved for the next generation of UAVs to be used successfully in expanded future combat roles. This report describes the initial research to improve the performance of UAVs through the use of lighter-than-air or pressurized structures-based (PSB) technologies. Basically, we examined how to construct the UAV in such a way that a considerable percentage of its weight will be supported by or composed of inflatable structures containing air or helium. In this way, PSB technology will reduce the amount of energy required to keep the UAV aloft, thus allowing the use of smaller, slower, and quieter motors. Using PSB technology in tandem with improving technologies in electronics, energy storage, and materials should provide a substantial increase over current UAV performance in areas needed by the military.     

UAV Consumable Replenishment: Design Concepts for Automated Service Stations

A key requirement for the complete autonomy of an unmanned aerial vehicle (UAV) is the replenishment of its energy source and other consumables. Such processes are typically overseen and conducted by a human operator, may be time consuming and effectively reduce the operating range of the system. To satisfy the requirements of UAV customers such as military surveillance networks, that seek faster, broader and more fully autonomous systems, and hobbyists, who seek to avoid the hassle associated with changing the fuel source, we develop automated energy recharging systems. Focusing on battery operated remote control helicopters, we employ the Axiomatic Design methodology to develop design concepts of platforms to act as automatic service stations. We propose three station designs for refilling platforms and one concept for battery exchange platforms. In addition, we analyze the economic feasibility of automatic consumable replenishment stations, consider two types of station (container refilling and container exchange) and discuss the application of these systems. Refilling platforms better suit low coverage unmanned aerial systems (UAS) while exchange stations allow high coverage with fewer UAVs.     

Facility inspection using UAVs: a case study in the University of Georgia campus

ABSTRACT

Facility inspections are an essential factor to maintaining the physical integrity of a building for several years. If inspections and follow up maintenance are only performed when reported, a significant portion of building damages will go unnoticed until the interior of the building is affected. Using unmanned aerial vehicles (UAV) for facility inspections presents a preventative approach to current inspection processes. The proposed technology is based on low-cost, high performance unmanned aerial vehicles integrated with modern sensing technologies for building and infrastructure inspections. The UAV prototype is based on highly developed consumer drone modified with thermal imaging capabilities to maximize visibility for a diverse range of damages. The focus of this case study is the inspection of potential damages associated with water, heat, and the Heating, Ventilation, and Air Conditioning (HVAC) system. Inspections with the assistance of UAVs can visualize areas of a building’s exterior where it is difficult to access or poses a safety risk to the inspector. This work provides a simplistic and cost-effective method to perform spot inspections of facilities. Results confirm that early detection of potential compromising utilities is possible with UAVs, which could prolong the life of equipment and facilities, effectively making the campus more sustainable.     

高空长航时无人机技术发展新思路

根据未来航空发展的战略需要,面向新一代高空长航时无人机的系统设计,十分有必要开展探索性、创新性和面向高空长航时无人机的关键技术研究.提出了高空长航时无人机技术发展的新思路和其瓶颈问题的解决方案.重点从高空长航时无人机多目标组合优化、气动-隐身一体化、能源动力、软件使能自主控制、自主导航、测控和信息传输、空天地多机分布协同等方面给出了可行技术方案和重点研究方向.这些技术的实现可增强高空长航时无人机系统方面的可持续发展能力,支撑和引领相关领域的技术发展.     

无人飞行器集群智能调度技术综述

随着飞行器技术的快速发展, 以无人机和卫星为代表的无人飞行器在集群任务中得到广泛应用, 但日益增长的多样化任务需求和不平衡、不充足的任务资源也对无人飞行器集群调度技术提出新的挑战.针对无人飞行器任务类型特点, 分别从无人机群和多星两个角度出发, 介绍了无人机群访问、打击和察打一体化任务调度技术进展, 阐述了多星成像、数传与天地一体化任务调度研究成果.同时, 梳理了无人机群和多星任务调度问题的主要约束与收益指标, 综述了无人机群和多星任务调度常用的智能优化算法.最后, 面向未来无人飞行器技术应用需求, 指出了无人飞行器集群智能调度技术进一步的研究方向.     

基于LabVIEW Vision的无人机自主着降系统设计与实现

四旋翼无人机具有低成本、垂直起降、机动性好等优点,在民用领域诸如航拍、植保、物流、电力巡线等场合得到了广泛的关注和应用;随着四旋翼无人机应用的普及,一些新的问题也随之出现,其中一个厄待解决的问题是如何提高无人机的降落精度和可靠性,特别在超视距应用场景下,这一需求尤为突出;通过采用机器视觉技术,利用LabVIEW Vision编制视觉识别软件,可以控制四旋翼无人机实现高精度的自主降落。     

Effect of time pressure and target uncertainty on human operator performance and workload for autonomous unmanned aerial system

Autonomous unmanned aircraft systems (UAS) are being utilized at an increasing rate for a number of military applications. The role of a human operator differs from that of a pilot in a manned aircraft, and this new role creates a need for a shift in interface and task design in order to take advantage of the full potential of these systems. This study examined the effects of time pressure and target uncertainty on autonomous unmanned aerial vehicle operator task performance and workload. A 2 × 2 within subjects experiment design was conducted using Multi-Modal Immersive Intelligent Interface for Remote Operation (MIIIRO) software. The primary task was image identification, and secondary tasks consisted of responding to events encountered in typical UAS operations. Time pressure was found to produce a significant difference in subjective workload ratings as well as secondary task performance scores, while target uncertainty was found to produce a significant difference in the primary task performance scores. Interaction effects were also found for primary tasks and two of the secondary tasks. This study has contributed to the knowledge of UAS operation, and the factors which may influence performance and workload within the UAS operator. Performance and workload effects were shown to be elicited by time pressure. Relevance to industry: The research findings from this study will help the UAS community in designing human computer interface and enable appropriate business decisions for staffing and training, to improve system performance and reduce the workload.     

A Multi-Point Distance-Bounding Protocol for Securing Automatic Dependent Surveillance-Broadcast in Unmanned Aerial Vehicle Applications

The Automatic Dependent Surveillance-Broadcast (ADS-B) protocol is being adopted for use in unmanned aerial vehicles (UAVs) as the primary source of information for emerging multi-UAV collision avoidance algorithms. The lack of security features in ADS-B leaves any processes dependent upon the information vulnerable to a variety of threats from compromised and dishonest UAVs. This could result in substantial losses or damage to properties. This research proposes a new distance-bounding scheme for verifying the distance and flight trajectory in the ADS-B broadcast data from surrounding UAVs. The proposed scheme enables UAVs or ground stations to identify fraudulent UAVs and avoid collisions. The scheme was implemented and tested in the ArduPilot SITL (Software In The Loop) simulator to verify its ability to detect fraudulent UAVs. The experiments showed that the scheme achieved the desired accuracy in both flight trajectory measurement and attack detection.

     

基于运行时验证的无人飞行系统安全威胁检测方法

无人飞行系统（Unmanned Aerial Systems,UAS）的软、硬件存在缺陷以及遇到外部恶意攻击,会给UAS的安全性带来极大威胁.由于UAS的运行环境复杂多变,很多因素在开发过程中难以准确预测,因此研究有效的运行时安全保证机制具有重要意义.本文提出一种基于运行时验证的UAS安全威胁检测方法.首先对UAS可能遇到的多种安全威胁进行分析并采用离散时间时序逻辑进行描述,提出相应的UAS-DL语言描述安全监控规约;然后基于交错自动机提出了自动生成安全威胁监控器的算法,并利用参数化方法实现对多UAS的安全监控.为了提高检测的准确性,进一步研究了将运行时验证和贝叶斯网络推断结合的方法.采用实际的UAS开发仿真平台Ardupilot进行了实验,并设计了将监控器独立部署在FPGA硬件上的方法,避免对UAS计算资源的过多占用.实验结果表明上述方法能够有效检测UAS的安全威胁.     

A Survey of UAS Technologies for Command, Control, and Communication (C3)

The integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) presents many challenges including airworthiness certification. As an alternative to the time consuming process of modifying the Federal Aviation Regulations (FARs), guidance materials may be generated that apply existing airworthiness regulations toward UAS. This paper discusses research to assist in the development of such guidance material. The results of a technology survey of command, control, and communication (C3) technologies for UAS are presented. Technologies supporting both line-of-sight and beyond line-of-sight UAS operations are examined. For each, data link technologies, flight control, and air traffic control (ATC) coordination are considered. Existing protocols and standards for UAS and aircraft communication technologies are discussed. Finally, future work toward developing the guidance material is discussed.     

无人机遥感平台技术研究与应用

作为一种新型的遥感平台,UAS(无人飞行器系统)具有优于其它遥感平台的灵活性、实时性、移动性等特点,本文介绍了UAS的发展现状及其关键技术,提出了UAS遥感平台的分类方法,从技术、市场、法律制度、成本等多方面考察了UAS应用于民用遥感领域的可行性。理论和实践证明,UAS平台在遥感技术的发展中必将发挥重要的作用,成为主流的遥感平台之一。     

Modelling glacier topography in Antarctica using unmanned aerial survey: assessment of opportunities

We discuss the application of unmanned aerial systems (UASs) and UAS-derived data to model glacier topography for detecting and analysing slow and rapid changes in glacier surfaces. The study was conducted in East Antarctica in the austral summer 2016/2017. The surveyed areas included an eastern part of the Larsemann Hills, an Airfield of the Progress Station, an initial section of a Sledge route from the Progress to Vostok Stations, and a north-western margin of the Dålk Glacier. We used a Geoscan 201 Geodesy, a professional-grade flying-wing UAS. For the photogrammetric processing, we utilized the Agisoft PhotoScan software. The direct georeferencing approach was applied. Several high-resolution, multitemporal digital elevation models (DEMs) for surveyed areas were produced. The DEM accuracy was estimated in the absence of ground control points and reference DEMs. We determined the ice flow velocity within the Airfield area and the Sledge route zone, where marked points were installed and moved together with the ice surface. We found that UAS imagery can be used for real-time monitoring of open and some snow-covered crevasses of various sizes. Wind-driven snow microforms are also well recognizable on UAS-derived aerial images. The 2017 Dålk Glacier catastrophic subsidence demonstrated that monitoring and studying such events in glaciers and ice sheets are almost impossible without UASs. Optimal meteorological conditions were empirically determined for conducting unmanned aerial survey to obtain images suitable for subsequent photogrammetric processing and DEM generation. Finally, we discuss adaptation of equipment and software to the Antarctic environment.     

无人机系统自平衡容错控制与故障诊断

随着无人机的广泛普及和自主控制技术的深入研究,现代战争已经离不开无人机的身影。而无人机在其拥有特殊优势的同时也需要更多的维护来确保无人机执行任务过程中的安全。本文引入生物学思想中的自平衡理论,进行无人机容错控制与故障诊断系统设计,通过设计“平衡点”确定无人机的安全状态,并建立基于原始内驱力和次要内驱力的自平衡理论模型,将容错控制与故障诊断不仅应用于故障预测和健康管理,更创新提出将容错控制与故障诊断作为判断无人机是否可作为攻击时自杀武器的判据。仿真试验表明,无人机在穿越敌占区时,可根据自身的故障情况判断是否可以返航或作为自杀式武器,证明了算法的有效性。     

UAV instantaneous power consumption prediction using LR-TCN with simple moving average

The usage of multi-rotor unmanned aerial vehicles (UAVs) has rapidly increased in a variety of industries recently, which has caused a quick rise in the quantity of research works on the topic. Remaining battery life prediction, anomaly detection and instantaneous power consumption prediction are among the topics that attract the most attention of researchers. This article presents the development and utilization of a modified temporal convolutional network (TCN) model, a commonly employed approach for anomaly detection and instantaneous power consumption prediction in unmanned aerial vehicles (UAVs). The first modification to the TCN model was to use the Leaky ReLu activation function in place of the rectified linear unit (ReLu) activation function from the original TCN model. In the next step, instantaneous power consumption prediction for UAVs was performed by using the data obtained from both sensors and simple moving average (SMA) algorithm. As a result of the tests performed with the created simulation setup, it has been clearly shown that the proposed method gives better results compared to other deep learning models used for comparison with the lowest RMSE of 0.0496.     

Low-altitude contour mapping of radiation fields using UAS swarm

Intelligent Service Robotics - This paper addresses the design of lightweight radiation sensors for the small-scale unmanned aerial system (UAS) and its implementation for low-altitude radiation...     

A Ground Control Station for a Multi-UAV Surveillance System

This paper presents the ground control station developed for a platform composed by multiple unmanned aerial vehicles for surveillance missions. The software application is fully based on open source libraries and it has been designed as a robust and decentralized system. It allows the operator to dynamically allocate different tasks to the UAVs and to show their operational information in a 3D realistic environment in real time. The ground control station has been designed to assist the operator in the challenging task of managing a system with multiple UAVs, trying to reduce his workload. The multi-UAV surveillance system has been demonstrated in field experiments using two quadrotors equipped with visual cameras.     

无人机基站部署问题综述: 模型与算法

以无人机为空中基站, 快速构建区域无线网络, 提供应急通信服务, 在地震、洪涝、火灾等突发事件以及战场作战中发挥着重要作用. 无人机基站的部署问题是通过优化无人机空间位置, 提高区域无线网络的服务效率, 这属于无人系统运作管理和无线网络设计领域的重要研究课题. 本文对近10年来无人机基站部署问题领域的主要研究成果进行了系统综述. 首先从服务高度、容量约束、能量消耗、连通性、干扰、用户分布和外部环境等方面分析了相关影响因素, 再从选址角度对主要建模方法进行了分类总结; 然后分析了无人机基站部署优化的求解算法和实验; 最后探讨了下一步重点研究方向.     

Exploiting a fleet of UAVs for monitoring and data acquisition of a distributed sensor network

Neural Computing and Applications - This study proposes an efficient data collection strategy exploiting a team of unmanned aerial vehicles (UAVs) to monitor and collect the data of a large...     

面向目标跟踪的多机协同通信保持控制

由于无人机存在通信和测量约束的情况,远程无人机执行持续目标跟踪任务时无法直接与地面站保持通信,需要其他无人机作为通信中继方可与地面站建立可靠的通信连接.基于Dubins曲线,采用最小转弯半径和航向调整相结合的方法对具有初始和终止航向角约束的多无人机进行协同航路规划,确保所有无人机同时到达指定位置,形成多机协同通信保持的初始构型.针对随机移动目标,在多机协同通信保持的动态过程中,考虑平台性能、通信约束、碰撞规避等约束条件,采用非线性模型预测控制(NMPC)实现无人机协同分布式在线优化.在确保无人机通信中继保持的前提下,有效提高了算法的实时性.仿真结果表明了该算法的有效性.