Experimental Comparison of Direct and Indirect Haptic Aids in Support of Obstacle Avoidance for Remotely Piloted Vehicles

The sense of telepresence is known to be essential in teleoperation environments, where the operator is physically separated from the vehicle. Usually only a visual feedback is provided, but it has been shown that by extending the visual interface with haptic feedback, that is complementing the visual information through the sense of touch, the teleoperator has a better perception of information from the remote environment and its constraints. This paper focuses on a novel concept of haptic cueing for an airborne obstacle avoidance task; the novel cueing algorithm was designed to appear ＂natural＂ to the operator, and to improve the human-machine interface without directly acting on the actual aircraft commands. Two different haptic aiding concepts for obstacle avoidance support are presented： an existing and widely used system, belonging to what we called the Direct Haptic Aid （DItA） approach class, and a novel one based on the Indirect Haptic Aid （IHA） approach class. Tests with human operators show that a net improvement in terms of performance （i.e., the number of collisions） is provided by employing the 1HA haptic cue as compared to both the DHA haptic cue and/or the visual cues only. The results clearly show that the IHA philosophy is a valid alternative to the other commonly used approaches, which fall in the DHA category.

Estimation and verification of green tide biomass based on UAV remote sensing

Since 2007,the Yellow Sea green tide has broken out every summer,causing great harm to the environment and society.Although satellite remote sensing(RS)has been used in biomass research,there are several shortcomings,such as mixed pixels,atmospheric interference,and difficult field validation.The biomass of green tide has been lacking a high-precision estimation method.In this study,high-resolution unmanned aerial vehicle(UAV)RS was used to quantitatively map the biomass of green tides.By utilizing experimental data from previous studies,a robust relationship was established to link biomass to the red-green-blue floating algae index(RGB-FAI).Then,the lab-based model for green tide biomass from visible images taken by the UAV camera was developed and validated by field measurements.Re sults show that the accurate and cost-effective method is able to estimate the green tide biomass and its changes in given local waters of the near and far seas.The study provided an effective complement to the traditional satellite RS,as well as high-precision quantitative techniques for decision-making in disaster management.

Remote sensing image encryption algorithm based on novel hyperchaos and an elliptic curve cryptosystem

Remote sensing images carry crucial ground information,often involving the spatial distribution and spatiotemporal changes of surface elements.To safeguard this sensitive data,image encryption technology is essential.In this paper,a novel Fibonacci sine exponential map is designed,the hyperchaotic performance of which is particularly suitable for image encryption algorithms.An encryption algorithm tailored for handling the multi-band attributes of remote sensing images is proposed.The algorithm combines a three-dimensional synchronized scrambled diffusion operation with chaos to efficiently encrypt multiple images.Moreover,the keys are processed using an elliptic curve cryptosystem,eliminating the need for an additional channel to transmit the keys,thus enhancing security.Experimental results and algorithm analysis demonstrate that the algorithm offers strong security and high efficiency,making it suitable for remote sensing image encryption tasks.

Launching an unmanned aerial vehicle remote sensing data carrier:concept,key components and prospects

Unmanned aerial vehicles(UAV)based remote sensing is an emerging and important data source.Recently,the use of UAVs for remote sensing applications has been rapidly growing owing to their greater availability and the miniaturization of sensors.UAVs are surpassing satellites and aircraft in remote sensing data supply for many local requirements.In comparison with satellite remote sensing data,most UAV remote sensing data is characterized by high resolution,small coverage area,and heterogeneous multi-sources.However,UAVs lack a unified space–time framework and standardized data process.This paper describes a UAV remote sensing data carrier that can be used as an e-commerce platform for data sharing among registered members and a mission planner for new data acquisition.To the best of our knowledge,the data carriers described herein,are the first of their kind.Through seamless docking with UAVs,the data carrier will form a national UAV network,capable of dynamically obtaining very-high-resolution UAV remote sensing images.In practice,a pilot retrieval system of UAV meta data has been developed to provide a catalogue of data product services.

Relationship between Vegetation Index and Forest Surface Fuel Load in UAV Multispectral Remote Sensing

[Objectives]To explore the relationship between vegetation index and forest surface fuel load.[Methods]UAV multispectral remote sensing was used to obtain large-scale forest images and obtain structural data of forest surface fuel load.This experimental area was located in Gaoming District,Foshan City,Guangdong Province.The average surface fuel load of the experimental area was as high as 39.33 t/ha,and the forest surface fuel load of Pinus elliottii was the highest.[Results]The normalized difference vegetation index(NDVI)and enhanced vegetation index(EVI)had a moderately strong correlation with the forest surface fuel load.The regression model of NDVI(X)and forest surface fuel load(Y)was established:Y=-5.9354X+8.4663,and the regression model of EVI(X)and forest surface fuel load(Y)was established:Y=-5.8485X+6.7271.The study also found that the linear relationship between NDVI and surface fuel load was more significant.[Conclusions]Both NDVI and EVI have moderately strong correlations with forest surface fuel load.NDVI is moderately or strongly correlated with the surface fuel load of Pinus massoniana forest,shrub grassland,broad-leaf forest and bamboo forest,while EVI is only strongly correlated with surface fuel load of broad-leaf forest and bamboo forest.It is expected that the relationship between other vegetation indices and forest surface fuel load can be obtained by the method in this study,so as to find a more universal vegetation index for calculating surface fuel load.

露天矿无人机遥感边坡地表形变提取方法研究

针对当前露天矿边坡监测过程中存在的设备留有监测死角、点位布控缺乏依据、地质隐患解译困难、无人机(Unmanned Aerial Vehicle,UAV)影像点云重构复杂度高等问题,提出了一种基于无人机遥感的边坡地表形变提取方法。首先,通过分析UAV激光点云与影像特点构建点云序列;其次,利用融合尺度不变特征变换(Scale Invariant Feature Transform,SIFT)与圆柱形邻域搜索的改进迭代最近点(Iterative Closest Point,ICP)算法,实现点云序列的精准高效配准,提高边坡形变提取精度;最终,借助数字高程模型(Digital Elevation Model,DEM)叠加分析与可视化,精准定位边坡重点形变区域,直观提取边坡形变位置和大小,并结合正射影像图像特征进行形变区域分析与解译。以南芬露天矿为工程应用实例,研究表明:边坡形变模型标准偏差为0.032 m,对比全球定位系统-实时动态差分(Global Positioning System-Real Time Kinematic,GPS-RTK)实测形变值,形变中误差为0.012 m,能够快速实现大尺度复杂边坡地表扫描与形变提取,从而为地质灾害隐患分析、盲区边坡形变监测与地面监测设备科学布控提供技术支撑。

基于无人机多光谱遥感的玉米LAI监测研究

[目的]探究更高效估测玉米LAI的无人机多光谱遥感监测模型,实现对玉米叶面积指数(Leaf area index,LAI)的快速预测估算。[方法]以全生长周期的玉米植株为研究对象,通过多光谱遥感无人机获取玉米植株影像并实地采集玉米LAI,利用多光谱信息研究植被指数与玉米LAI之间的定量关系,并选择相关的植被指数;分别使用多元线性逐步回归、支持向量机回归算法(Support vector machine regression,SVM)、随机森林回归算法(Random forest regression,RF)和基于鲸鱼算法(Whale optimization algorithm,WOA)优化的随机森林算法(WOA-RF)构建玉米LAI预测模型,通过分析对比,选择最优预测模型。[结果]筛选出的植被指数NDVI、NDRE、EVI、CIG与LAI呈极显著相关(P<0.01),构建了多元线性回归模型、SVM模型、RF模型和WOARF模型的预测模型,R2分别为0.873 2、0.878 0、0.917 7和0.940 8,RMSE分别为0.277 5、0.236 5、0.209 0和0.128 7。[结论]基于WOA-RF的玉米LAI预测模型的预测精度能够满足玉米生产的需要,对玉米生长期间的种植管理具有指导意义。

基于无人机高光谱影像的农田土壤有机碳含量估算——以湟水流域农田为例

快速、准确地估算农田土壤有机碳含量并对其进行空间分布制图,有利于土壤精细化管理和智慧农业的发展。该文以青海湟水流域3个典型农田区为例,在研究区内同步采集296个土壤样品和相应的野外原位光谱,使用无人机搭载高光谱相机进行影像获取,并对土壤样品进行室内光谱采集和有机碳含量测定。对光谱反射率进行7种不同形式的变换,通过相关性分析从中筛选出主要特征波段,利用多元线性回归、偏最小二乘回归和随机森林3种方法分别对室内光谱、野外原位光谱和无人机光谱进行建模,对比各模型的精度。用光谱直接转换法对无人机光谱进行校正,使用校正后的无人机光谱最优模型进行建模,模型代入无人机高光谱影像进行有机碳含量制图,最后对满足制图精度要求的农田区进行分析和讨论。结果表明:①除对无人机高光谱进行对数变换后的多元线性回归不能估算有机碳外(相对分析误差为1.375),实验室光谱、野外原位光谱及无人机高光谱的原始光谱及所有转换方法均能对有机碳进行估算,决定系数R 2为0.562~0.942,均方根误差为1.713~5.211,相对分析误差为1.445~4.182;②在所有光谱变换方法中,多元散射校正+一阶微分变换与有机碳含量的相关性最高,特征波段分别为429~449 nm,498~527 nm,830~861 nm和869 nm;③在所有建模结果中,随机森林模型精度最高,其次为偏最小二乘模型,多元线性回归模型精度最低,校正后的无人机光谱建模精度均有所提高;④3个农田区的反演精度均满足制图要求,R 2均在0.88以上。其中,A农田区有机碳含量均值最高,为28.88 g·kg^(-1),整体空间分布均匀;B农田区均值为13.52 g·kg^(-1),整体分布呈现出较强的空间差异性;C农田区有机碳含量均值最低,为8.54 g·kg^(-1),高值和低值的分化明显。本研究可为无人机高光谱遥感技术应用于田间尺度的土壤有机碳含量估算和数字制图提供参考。

无人机建筑垃圾影像的三维建模软件性能评估

随着我国建筑垃圾产量的快速增加,利用无人机遥感技术和三维建模软件可以弥补传统方法在建筑垃圾监督管理的弊端,但是不同的三维建模软件应用在建筑垃圾领域的性能还不明朗。该文通过层次分析法综合建模运行时间、色彩还原度和模型生成效果三方面来量化ContextCapture、Pix4Dmapper和PhotoScan三款三维建模软件在建筑垃圾建模的综合性能,较好地对比三款建模软件各自的优势和劣势,反映出各建模平台独有的特点。实验结果表明,在建模运行时间和色彩还原度方面,Pix4Dmapper表现都更加优异,而在模型生成效果方面则是ContextCapture的表现更好。综合三方面比较,ContextCapture最佳,但是Pix4Dmapper与其差距不大。PhotoScan只在建模运行时间方面表现较好,其他方面都较为一般。研究结果为后续在建筑垃圾领域选择三维建模软件提供切实的依据。

基于改进YOLOv5网络模型的无人机影像道路目标检测

针对无人机遥感道路影像内目标分布混乱且尺寸差异大、负样本所占比例较高等问题,提出了基于YOLOv5X的无人机遥感影像道路目标检测模型RA_YOLOv5。采用感受野-坐标注意力卷积替换骨干网络内的常规卷积核,然后以空洞-空间金字塔池化-通道注意力层替换原始特征金字塔池化层;在特征融合网络中引入自适应特征融合层,通过特征图加权融合解决不同尺寸检测图之间样本、背景矛盾的问题;使用解耦检测头分别计算回归、分类任务,并替换损失函数以缓解正负样本不均衡问题。实验结果表明,RA_YOLOv5在VisDrone数据集上平均精度均值达到90.42%,较YOLOv5X提高了7.85%,在测试环境下,检测帧数达到35.46帧每秒,能够实际输出检测结果,同时具有良好的稳定性,能够在道路巡检、交通流量监控、应急事故处理等多种场景下发挥重要作用。

一种适用于微型无人机的移动MUAV-MTP协议

现有Mav Link协议的设计主要面向低速率、大数据量的消息传输,存在移动通信信道特性差、环境干扰因素多等问题。为此,提出一种新型的MUAV-MTP协议,用于微型无人机移动传输身份验证、路线以及控制信息。借鉴现有的移动MavLink通信协议,将原协议转换为面向微型无人机的远程移动控制协议,通过简短的指令包完成无人机的巡航移动控制,并使其同时支持TCP、UDP协议。实验结果表明,MUAV-MTP协议具有操作简便、接口通用,具有良好的扩展性及鲁棒性,可用于基于Pixhawk飞控组装无人机的测试开发。

Leveraging the UAV to support Chinese Antarctic expeditions:a new perspective

Recent developments in Unmanned Aerial Vehicles(UAVs)and their applications in various subjects are of interest to polar communities.Due to the harsh climate and dangerous environment,these regions pose challenges for the expedition teams.Several countries have tested the UAV technology to support Antarctic research and logistics.In this trend paper,we provide insightful reviews and discussions on such a prospective topic.Based on a comprehensive literature survey,we firstly summarize the key research progress of UAV in Antarctic studies.Then the examples of risk scenarios during the field exploration are given,after which several promising applications of the UAVs in safety guarantee are illustrated.In particular,we present a case of site-selection for the Chinese first ice sheet airfield,using the data collected in the 34th Chinese National Antarctic Research Expedition(CHINARE).In the end,we highlight the unique value of the UAVs in the popularization of polar science before concluding the advantages and limitations.Considering their excellent performance,we expect more innovations for UAV’s applications in the following Antarctic expeditions.

Geometrical feature analysis and disaster assessment of the Xinmo landslide based on remote sensing data

At 5:39 am on June 24, 2017, a landslide occurred in the village of Xinmo in Maoxian County, Aba Tibet and Qiang Autonomous Prefecture(Sichuan Province, Southwest China). On June 25, aerial images were acquired from an unmanned aerial vehicle(UAV), and a digital elevation model(DEM) was processed. Landslide geometrical features were then analyzed. These are the front and rear edge elevation, accumulation area and horizontal sliding distance. Then, the volume and the spatial distribution of the thickness of the deposit were calculated from the difference between the DEM available before the landslide, and the UAV-derived DEM collected after the landslide. Also, the disaster was assessed using high-resolution satellite images acquired before the landslide. These include Quick Bird, Pleiades-1 and GF-2 images with spatial resolutions of 0.65 m, 0.70 m, and 0.80 m, respectively, and the aerial images acquired from the UAV after the landslide with a spatial resolution of 0.1 m. According to the analysis, the area of the landslide was 1.62 km2, and the volume of the landslide was 7.70 ± 1.46 million m3. The average thickness of the landslide accumulation was approximately 8 m. The landslide destroyed a total of 103 buildings. The area of destroyed farmlands was 2.53 ha, and the orchard area was reduced by 28.67 ha. A 2-km section of Songpinggou River was blocked and a 2.1-km section of township road No. 104 was buried. Constrained by the terrain conditions, densely populated and more economically developed areas in the upper reaches of the Minjiang River basin are mainly located in the bottom of the valleys. This is a dangerous area regarding landslide, debris flow and flash flood events Therefore, in mountainous, high-risk disaster areas, it is important to carefully select residential sites to avoid a large number of casualties.

无人机对地观测的遥感场景三维重建实验方案

面向航空航天信息类专业实践培养需求,以无人机航拍城市场景遥感沙盘模型为平台,设计了无人机对地观测的遥感场景三维重建实验方案,为学生提供实验室环境下探索遥感信息技术的途径。实验模拟遥感影像采集过程,设计了无人机的数据传输与相机标定方案,进而根据SFM算法得到场景的三维稀疏点云,最后进行稠密化得到最终三维重建结果。在实验中,学生通过以上步骤获取航拍城市场景沙盘模型的图像序列并通过算法得到最终结果,实验结果表明,稀疏点云与稠密点云的恢复结果与目视场景一致。该实验激发了学生对理论知识的学习兴趣,掌握三维重建相关的基本知识和原理,同时锻炼了学生的实践动手能力和解决问题能力。

Railway Transport Infrastructure Monitoring by UAVs and Satellites

Improving the rail transport security requires development and implementation of neoteric monitoring and control facilities in conditions of increasing speed and intensity of the train movement and high level of terrorist threat. Use of Earth remote sensing (ERS), permitting to obtain information from large areas with a sufficiently high resolution, can provide significant assistance in solving the mentioned problems. This paper discusses the possibility of using various means of remote sensing such as satellites and unmanned aerial vehicles (UAV), also known as drones, for receiving information in different ranges of the electromagnetic spectrum. The paper states that joint using of both these means gives new possibilities in improving railroad security.

多源遥感揭示白鹤滩库区五里坡滑坡蓄水期形变演化与复活机制

为揭示水电站蓄水期库岸滑坡形变演变趋势及复活机制,基于白鹤滩库区五里坡滑坡2021年1月—2022年8月共73景Sentinel-1影像,采用SBAS-InSAR技术提取蓄水期二维形变,并使用无人机航测技术对滑坡及次生灾害痕迹进行调查,此外利用GNSS位移实测数据对InSAR形变结果进行对比与补充,综合3种技术结果与库区水位实测数据、地质资料对五里坡滑坡进行精细化分析.结果表明:(1)五里坡滑坡形变与库区蓄水存在强相关性.在蓄水前无明显形变而在蓄水后一个月便发生可见形变,随着水位上涨,坡度方向InSAR形变速率最高达到-153 mm/a,雷达视线方向InSAR最大累积形变量达到121 mm,并表现为由下部形变逐渐带动上部形变的牵引式滑坡特征.结合水位实测数据与GNSS位移监测数据发现滑坡形变与蓄水期水位变化吻合度较高.(2)现场地质调查表明五里坡滑坡为上硬下软的反倾岩质边坡,且坡面岩体风化强烈,下部岩体容易受到库水作用软化发生压缩变形进而导致坡体沿风化层发生牵引式滑动.研究结果可为库岸滑坡蓄水期监测和防治提供科学依据.

基于无人机影像的无瓣海桑单木提取与地上生物量估算

无瓣海桑(Sonneratia apetala)是中国红树林恢复种植最早引进的优质红树树种,其生产力在红树林群落中处于较高水平,具有显著的高生物量和能量积累。然而,由于红树林群落冠层密集、结构复杂,精确描绘无瓣海桑的单木树冠存在极大挑战性。传统的卫星遥感侧重于区域或更大尺度监测需求,而新兴的低空无人机遥感在更精细尺度的红树林生态监测中具有显著优势。以广东省珠海市淇澳岛红树林自然保护区为研究区,利用消费级无人机影像生成的冠层高度模型(Canopy Height Model,CHM)和种子区域生长(Seed Region Growing,SRG)算法进行无瓣海桑单木树冠提取,并建立基于地面调查数据获取的树高和胸径两者之间的回归关系,以优化无瓣海桑地上生物量异速生长方程,进而实现研究区单木尺度的无瓣海桑地上生物量估算。结果表明:基于无人机影像可以有效提取无瓣海桑单木树冠,其提取精度达到67%;验证了树高和胸径之间较高的相关性,提出了基于树高的无瓣海桑地上生物量异速生长方程;研究区无瓣海桑平均地上生物量的范围为2.99~247.24 t/hm2,平均值为92.14 t/hm2,且单木地上质量分布具有空间聚集性。

无人机多光谱影像在稻纵卷叶螟危害监测中的应用

为探讨利用无人机多光谱影像监测稻纵卷叶螟危害的可行性,本研究于2021年6-10月开展了无人机对稻纵卷叶螟危害和田间水稻生育状况的同步观测试验,分析了15种植被指数与卷叶率(虫害指标)之间的相关关系;分别采用普通最小二乘法、多项式拟合、多元逐步回归法和偏最小二乘法建立了水稻分蘖期、拔节期和孕穗期的卷叶率反演模型;在此基础上,筛选出最优模型并分析卷叶率与水稻生理生态参数之间的关联。结果表明,(1)3个生育期的大部分植被指数与卷叶率存在极显著的相关性,每个生育期卷叶率与均一化植被指数(NDVI)的相关性都是最高的。(2)分蘖期的卷叶率反演模型效果最好,孕穗期的模型较好,拔节期的模型效果稍差。(3)在分蘖期,稻纵卷叶螟对水稻的危害反映在叶绿素浓度的下降和叶色的变化;在拔节期,虫害会引起水稻的补偿反应,导致叶绿素含量和叶面积增加;在孕穗期虫害对水稻生长的危害主要表现为叶绿素含量下降。本研究结果可为无人机遥感技术在区域范围内精确识别稻纵卷叶螟危害提供重要的参考。

基于无人机遥感的矿山重建植被功能多样性研究

植被功能多样性是反映生态系统固碳能力的重要指标,估测功能多样性对于评价生态恢复成效和指导生态修复工程具有重要意义,但中低分辨率遥感数据难以实现植被功能多样性的估测。为此,本文以半干旱区某煤矿排土场为试验区域,利用无人机遥感手段获取激光雷达与高光谱影像数据,反演重建植物群落的功能多样性,并揭示不同修复模式下功能多样性的差异。研究结果表明,无人机可以快速获取高精度的植被高光谱和激光点云数据,有效估测植物群落的形态和生理性状。基于形态和生理性状,可以有效地定量描述植物群落功能多样性。生态修复初期的植被选取和配置会对演替后的植物群落功能多样性造成显著影响,乔灌混合的植物群落在演替后的植物性状和多样性水平高于纯林和草本群落。无人机遥感可以快速获取精细的群落结构和功能数据,为生态修复成效评价和植被优化提供可靠依据。

白鹤滩库区象鼻岭—野猪塘段地质灾害综合遥感识别

在蓄水前查清库岸地质灾害数量和位置是大型水库区地质灾害防治的重要工作之一,人工或单一技术手段的调查方式往往会遗漏许多地质灾害。采用合成孔径雷达干涉测量(Interferometry Synthetic Aperture Radar, InSAR)和无人机光学遥感技术对白鹤滩库区象鼻岭—野猪塘段崩滑库岸地质灾害进行了综合遥感识别工作。通过对识别结果的复核和综合分析,结果表明:(1)通过综合遥感技术识别地质灾害114处,其中无人机光学遥感和InSAR技术分别识别89处、39处,相比人工排查新增72处;(2)通过联合升降轨影像的方法有利于改善SAR数据的几何畸变效应,增加SAR可视性区域面积,提高地质灾害识别成果的有效性;(3)对于新近发生缓慢变形地质灾害可以通过InSAR技术识别,限于光学影像精度和时效性则难以通过光学遥感识别;(4)过去发生变形的地质灾害可从无人机光学遥感和InSAR识别其宏细观特征,对于SAR数据周期内出现可探测形变,亦可同时被InSAR技术识别;(5)对于面积较大的地质灾害,InSAR技术和光学遥感手段均能有效识别,限于数据精度,InSAR技术对于较小面积的地质灾害难以有效识别。利用InSAR与无人机光学遥感等技术开展地质灾害综合遥感识别,可以获得地质灾害的地表变形信息,了解地质灾害的特征要素信息,克服星载光学遥感解译的局限性,有效避免高山峡谷地区人工或单一技术方法地质灾害识别遗漏。