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Science China Chemistry 1995年第7期38卷 834-846页

作者：曹家欣严润娥王欢 Department of Geography Peking UniversityBeijing 100871China Analysis and Measurement Centre Beijing Normal UniversityBeijing 100875China

The formation,age and paleoclimatic changes of the red mantle of weathering and brownish-redloam of the Miaodao Islands are dealt with for the first *** red mantle of weathering products formedthrough Fe-Al enrichment and desilication process under wet and hot climatic *** brownish-red loam isa kind of eolian loess formed under semiarid and warm climatic *** correlate,respectively,with thered clay of Pliocene and Wucheng Loess occurring in the inland of North *** indicate that an abruptchange of climatic conditions took place during the turn of Pliocene and *** change may relate to theglobal climatic change.

关键词： Miaodao Islands red mantle of weathering brownish-red loam palaeoclimate.

多传感器融合的移动机器人室外激光SLAM算法优化与系统实现

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电子测量与仪器学报 2023年第2期37卷 48-55页

作者：余联想郑明魁欧文君王占宝福州大学先进制造学院泉州362200 福州大学物理与信息工程学院福州350108

针对移动机器人室外环境开阔场景大范围建图时,激光雷达里程计位姿计算不准确从而导致SLAM算法精度下降等问题,设计了一种基于多传感器融合的SLAM优化算法。算法上,通过前端里程计优化提升SLAM算法的可靠性,将适用于室外的GNSS等传感器... 详细信息

针对移动机器人室外环境开阔场景大范围建图时,激光雷达里程计位姿计算不准确从而导致SLAM算法精度下降等问题,设计了一种基于多传感器融合的SLAM优化算法。算法上,通过前端里程计优化提升SLAM算法的可靠性,将适用于室外的GNSS等传感器信息与激光里程计融合,在技术上实现了扩展卡尔曼滤波的轻量化并将其嵌入于loam算法架构中,在尽可能不增加资源负担的情况下对前端里程计进行改进;在优化算法基础上,搭建了实际移动机器人平台并移植算法,实现了可供参考的多传感器融合硬件方案与扩展卡尔曼滤波在实际工程中处理多传感器数据的方法。真实场景下的实验结果表明,在增加了里程计运算量后算法仍能稳定保持10 Hz的室外建图,在复杂开阔环境与低成本条件下具有可靠性与可行性。

关键词：移动机器人激光SLAM 多传感器融合 loam

惯性测量单元辅助的LiDAR动态点云剔除方法

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测绘科学 2023年第5期48卷 173-182页

作者：徐爱功高佳鑫隋心袁庆陈志键辽宁工程技术大学测绘与地理科学学院辽宁阜新123000 中铁第四勘察设计院集团有限公司工程勘察研究院武汉430063

针对动态场景下动态目标影响激光雷达同时定位与建图算法(LiDAR SLAM)的精度和成图效果问题,该文提出一种基于惯性测量单元(IMU)辅助的多层次模糊综合评价动态点云剔除方法。通过标定IMU/LiDAR外参统一两类传感器坐标系,再将每帧点云聚... 详细信息

针对动态场景下动态目标影响激光雷达同时定位与建图算法(LiDAR SLAM)的精度和成图效果问题,该文提出一种基于惯性测量单元(IMU)辅助的多层次模糊综合评价动态点云剔除方法。通过标定IMU/LiDAR外参统一两类传感器坐标系,再将每帧点云聚类分割为若干点云簇,以此为基础,利用IMU信息辅助建立相邻帧各点云簇间的配对关系,构建点云运动状态多层次模糊综合评价模型,判定各点云簇的运动状态,最终将动态点云簇从原始点云数据中剔除。为验证该文方法的可行性和精确性,设计了动态点云剔除实验,并将剔除动态点云后的点云数据输入激光雷达里程计与建图算法(loam)进行定位与建图。实验结果表明,该文方法动态点云的剔除成功率为98.67%,静态点云的误剔除率为2.01%,能够有效地提高点云数据质量。相比基于原始点云数据的loam算法,均方根误差降低了66.06%,最大误差降低了72.78%,实现了厘米级精度的定位,并且优化了建图效果。

关键词： IMU LiDAR 动态点云模糊综合评价模型 loam

基于回环检测的LiDAR里程计优化和建图技术研究

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基于回环检测的LiDAR里程计优化和建图技术研究

作者：李娜北方工业大学

学位级别：硕士

随着科技的快速发展,无人驾驶与服务机器人等各类移动机器人技术在科技的带动下不断进步。SLAM(Simultaneous Localization and Mapping)算法是实现机器人自主移动的核心技术,具有重要的研究意义。SLAM算法表示机器人可以在本身位置不... 详细信息

随着科技的快速发展,无人驾驶与服务机器人等各类移动机器人技术在科技的带动下不断进步。SLAM(Simultaneous Localization and Mapping)算法是实现机器人自主移动的核心技术,具有重要的研究意义。SLAM算法表示机器人可以在本身位置不确定的情况下完成地图构建功能,并利用地图信息实现自主定位与导航任务。多线Li DAR是SLAM算法中最常用的传感器,在纹理缺失或严重缺乏光照的情况下,激光SLAM算法实现的定位和建图效果比视觉SLAM算法更好。loam(Lidar Odometry and Mapping in Real-time)算法是激光SLAM算法中最具有代表性的算法,然而该算法未考虑点云强度,也未充分利用历史帧点云信息,因此其里程计和建图精度不足。本文针对上述问题,提出了基于回环检测的Li DAR里程计优化和建图算法,主要研究内容如下:1、考虑到直接将Li DAR获得的所有激光点云数据用于Li DAR里程计和后端优化中,会极大的影响效率和定位精度,所以在原始激光点云数据上执行预处理操作,剔除较远和较近的点云实现降采样,同时过滤掉细小物体,避免不可靠激光点云影响后续配准的精确度,从而提高算法的鲁棒性。2、充分利用地面点云信息,对地面点进行单独提取并应用于后端约束,由于不同材质的物体强度信息不同,故把点云的强度值和几何值一同进行考虑完成角点和平面点提取。3、考虑到loam算法主要使用几何特征进行里程计和建图优化而忽略了Li DAR点云的强度信息,故提出使用几何信息和点云强度信息实现Li DAR里程计和建图算法,通过角点约束和面点约束实现几何信息对Li DAR里程计和建图的优化,利用强度信息构建反射率地图,并通过三线性插值获得对应网格单元反射率的测量值实现点云强度约束,完成点云强度信息对Li DAR里程计和建图的优化。4、加入回环检测模块,在基于几何信息和强度信息的Li DAR里程计优化和建图算法基础上,充分利用历史帧点云信息,通过回环信息再次提高Li DAR里程计和建图算法计算的位姿精确度。通过周围N帧点云获取回环帧数据,利用ICP(Iterative Closest Point)分数判断是否进行优化,若需要优化,则在ICP算法获取的位姿基础上进一步使用点云强度约束、地平面约束校正回环位姿,最后将回环检测因子加入至因子图算法中完成对非回环区域数据帧的校正,获得全局一致地图。5、使用KITTI公开数据集验证改进算法的精确度,在多种道路的场景下,将加入几何约束、强度约束与地面约束的IG-loam算法运算结果与加入几何约束、强度约束、地面约束、回环约束和因子图的IGCF-loam算法运算结果与Aloam算法运算结果进行比较,利用绝对位姿误差和相对位姿误差评估算法效果,并借助ROS(Robot Operating System)操作系统的工具展示实验结果。通过对误差中各项数据指标的比较,可以验证改进算法在定位和建图效果上有较大的提升。

关键词：同时定位与建图 loam 激光雷达回环检测

Soil Geomorphology of Garpanchkot Hill Area and Its Influence on Land Use and Land Cover

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Journal of Geoscience and Environment Protection 2019年第7期7卷 108-135页

作者： Arindam Sarkar Department of Geography P.K.H.N. College Howrah India Department of Geography University of Calcutta Kolkata India

The present study is about to find out different attributes of soil as well as geomorphology. It is very much relevant to the study of land use land cover (LULC). Garpanchkot hill is situated in Purulia district of West Bengal. There are two geomorphological and seven pedological parameters that have been selected for the study. Shuttle radar topographic mission (SRTM) and advanced land observing satellite (ALOS) data are analyzed by remote sensing software to find out the geomorphological character of the area. There are twenty soil samples that have been taken from top of the hill to foothill pediment area with the change of elevation and slope for laboratory analysis. Different statistical techniques are used for representation. Foot hill area of the Garpanchkot hill can be determined by less than 150 m elevation and 5o slope. Elevation and slope of rest of the hill area (greater than 150 m and 5o) are fully dominated by forest and scattered vegetation. Elevated area (greater than 205 m) with less slope (10o - 15o) is associated with dense forest. Escarpment area is associated with grass land and scattered vegetation. Foothill area is bearing the signature of scattered vegetation, bare soil ground and agriculture. The richness of clay minerals plays an important role in the foothill pediment area for development of agriculture. Sandy loam is dominating soil texture in the rest of the hill area. Percentage of organic matter (1.8%), status of salinity (6.65 - 7.72) and alkalinity (up to 138.6 μs/cm) remain high in the high elevated area due to forest cover. The area is very dry, only fed by the rainfall during monsoon season. Artificial reservoir feeds the foothill agriculture system. Rice, wheat, maize, sugarcane, pulses chili and vegetables are the main crops of this area.

关键词： Soil Geomorphology Foothill Agriculture Forest Sandy loam

面向车辆自主定位的激光雷达特征点选取方法性能分析

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面向车辆自主定位的激光雷达特征点选取方法性能分析

Lead Absorption by Radish Is Affected by Soil Texture and Cultivar

第二十届中国系统仿真技术及其应用学术年会（20thC...

作者：魏超江建文陈宗海中国科学技术大学自动化系

车辆的自主定位是智能汽车不可或缺的功能,用于自主定位和姿态估计的激光SLAM算法有赖于良好的特征点提取算法和场景模型。本文主要介绍了现有两种点云定位和配准算法:Lidar Odometry and Mapping（loam）算法和ImplicitMoving LeastSqu... 详细信息

车辆的自主定位是智能汽车不可或缺的功能,用于自主定位和姿态估计的激光SLAM算法有赖于良好的特征点提取算法和场景模型。本文主要介绍了现有两种点云定位和配准算法:Lidar Odometry and Mapping（loam）算法和ImplicitMoving LeastSquares（IMLS）算法,并分析了两种算法的异同,以及拼接两种算法的可行性。然后文章根据分析结果提出了新方法——将IMLS算法中的特征点选取算法迁移至loam框架中,并在KITTI的数据集上做验证。结果显示平均位姿估计误差为0.74%,证明了本文方法的有效性。

关键词： loam 点云配准特征点 IMLS

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Open Journal of Soil Science 2019年第4期9卷 65-74页

作者： Tracey Emmerick Takeuchi Arthur James Downer Plant Science Department California Polytechnic University Pomona CA USA Division of Agriculture and Natural Resources University of California CA USA

Lead (Pb) was detected in potential urban garden soil in Claremont Cali-fornia and was absorbed by radish cultivars and giant red mustard in a bioassay of the contaminated soil. Radish cultivars grown in two soils with two lead salts developed the same lead tissue concentrations. In a subsequent study, Cultivar “Rudolf” accumulated less lead nitrate than cultivars “French Breakfast” and “White Beauty”. Cultivar “Rudolf” grew the least biomass likely accounting for its reduced Pb accumulation. All radish cultivars accumulated more lead when grown in clay vs. sand soil and radish Pb accumulation increased when the concentration of lead was increased in either soil type. The solubility of the lead ion used was not associated with Pb uptake by radish.

关键词： Lead Pb Radish Mustard Soil Clay loam Sandy loam Plant Growth Bioassay

Diurnal Methane Fluxes as Affected by Cultivar from Direct-Seeded, Delayed-Flood Rice Production

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Journal of Environmental Protection 2017年第9期8卷 957-973页

作者： Kristofor R. Brye Alden D. Smartt Richard J. Norman Department of Crop Soil and Environmental Sciences University of Arkansas Fayetteville USA

Methane (CH4) emissions are known to differ between rice (Oryza sativa L.) cultivars, where CH4 emissions from pure-line cultivars are often greater than from hybrids. Numerous field studies have shown that CH4 emissions follow a diurnal pattern, typically reaching their maximum during afternoon hours. However, it is unknown whether cultivar affects CH4 fluxes/emissions at various measurement times of day or how those cultivar effects may differ spatially across soil textures and temporally throughout the rice growing season. The objective of this field study was to evaluate the effects of time of day (300, 800, 1200, 1800, and 2300 hours) and cultivar (one hybrid and one pure-line) on CH4 fluxes before and after heading from a silt-loam and clay soil in a direct-seeded, delayed-flood rice production system. Enclosed headspace chambers, 30 cm in diameter, were used for CH4 gas sampling on 22 July and 19 August at a silt-loam site and on 29 July and 26 August, 2014 at a clay-soil site in the Lower Mississippi River delta region of eastern Arkansas. Methane fluxes measured pre- and post-heading ranged from 0.7 to 2.2 mg CH4-C m-2· hr-1 from the clay soil and from 2 to 7 mg CH4-C m-2·hr-1 from the silt-loam soil. Hourly CH4 fluxes and estimated daily emissions differed among measurement times of day (P 4 flux or daily emissions for a given day differs by soil texture and rice growth stage, but conducting CH4 flux measurements around late morning to mid-day appear to be optimum to best capture the mean CH4 emissions for the day.

关键词： Methane Flux Methane Emissions Rice Arkansas Hybrid Pure-Line Silt loam Clay

Growing Cover Crops to Improve Biomass Accumulation and Carbon Sequestration: A Phytotron Study

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Journal of Environmental Protection 2010年第2期1卷 73-84页

作者： Qingren Wang Yuncong Li Ashok Alva 不详

Cover crop system has shown a potential approach to improving carbon sequestration and environmental quality. Six of each winter and summer cover crops were subsequently grown in two soils, Krome gravelly loam soil (KGL), and Quincy fine sandy soil (QFS), in phytotrons at 3 temperatures (10/20, 15/25, 25/30oC for winter/summer cover crops) to investigate their contributions for carbon (C) sequestration. Among winter cover crops, the highest and the lowest amounts of C accumulated were by bellbean (Vicia faba L.), 597 g/m2 and white clover (Trifolium repens), 149 g/m2, respectively, in the QFS soil. Among summer cover crops, sunn hemp (Crotalaria juncea L.) accumulated the largest quantity of C (481 g/m2), while that by castorbean (Ricinus communis) was 102 g/m2 at 30oC in the KGL soil. The mean net C remained in the residues following the 127 d decomposition were 187 g/m2 of C (73% of the total) and 91 g/m2 (52% of the total) for the winter and summer cover crops, respectively. Following a whole cycle of winter and summer cover crops grown, the mean soil organic C (SOC) increased by 13.8 and 39.1% in the KGL and QFS soil, respectively, compared to the respective soils before. The results suggest that triticale, ryegrass, and bellbean are the promising winter cover crops in the QFS soil, while sunn hemp, velvetbean (Mucuna pruriens), and sorghum sudangrass (Sorghum bicolor ×S. bicolor) are recommended summer cover crops for both soils under favorable temperatures.

关键词： Carbon to Nitrogen Ratio (C:N) Greenhouse Gas (GHG) Krome Gravelly loam (KGL) Quincy Fine Sand (QFS) Soil Organic Carbon (SOC)

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GNSS与LiDAR组合导航系统的研究

GNSS与LiDAR组合导航系统的研究

作者：任刚长济南大学

学位级别：硕士

工业自动引导车AGV在室外环境定位导航大多使用类似磁导航的有轨引导,有轨引导的路径修改复杂、后期维护成本大;而室内定位大多使用基于二维激光雷达的同步定位与建图SLAM算法,由于二维激光雷达获取环境信息量少且周围环境变化对其定位... 详细信息

工业自动引导车AGV在室外环境定位导航大多使用类似磁导航的有轨引导,有轨引导的路径修改复杂、后期维护成本大;而室内定位大多使用基于二维激光雷达的同步定位与建图SLAM算法,由于二维激光雷达获取环境信息量少且周围环境变化对其定位精度影响较大。本文为了提高AGV在室内、室外以及室内外过渡环境中的定位导航信息的精度、稳定性以及导航信息的完备性,进行了基于差分的全球导航卫星系统GNSS的室外定位系统的开发、基于三维激光雷达的室内定位系统的开发以及对于室内室外过渡区域定位系统动态切换的组合导航的研究。在室外,由于室外作业环境复杂没有固定的环境特征,受到天气的影响,室内常用的定位方法不能稳定的全天候室外运行,为了获得稳定的定位信息,使用基于实时动态载波相位差分技术的全球导航卫星系统GNSS进行室外定位,并与惯性导航系统INS组合提高室外定位数据的刷新率和稳定性,采用STM32f407芯片开发定位数据解析模块;使用高斯投影方法将大地坐标系的经纬度转化为毫米级的平面直角坐标系坐标值,在室外的作业区域构建定位数据的局部坐标系,最后通过双天线测量方式计算获得位姿信息(x,y,θ),为移动机器人提供室外的定位导航信息。在室内,导航卫星信号比较弱,全球导航卫星系统GNSS无法解算固定解,但室内环境基本稳定,具有固定的环境特征。为了更好的利用环境特征,采用基于三维激光雷达的SLAM算法进行定位与构建点云图。首先采用激光雷达里程计的同步定位与建图loam算法订阅环境点云,进行特征点的提取、相邻两帧数据里程计信息的计算、实时的三维点云与堆积三维点云图的里程计信息的计算以及对两种里程计数据的插值处理,最终输出作业环境的3D点云图以及机器人的位姿信息(x,y,θ),为移动机器人提供室内的定位导航信息。在室内室外的过渡区域,为了保证AGV或者移动机器人的定位数据稳定动态切换;首先将机器人移动到室外的作业环境附近,设置作业区域的局部坐标系原点;然后将机器人移动到室内外的过渡区域,此区域两种定位系统的数据并存,将全球导航卫星系统GNSS的位姿数据输入到loam算法中,作为构建室内作业环境的3D点云图的起始位姿,辅助loam算法构建作业环境的3D点云图,对两种定位系统的坐标系进行了统一;在机器人自主导航时根据两种定位系统对此区域的环境状态的检测进行不同数据源的动态切换,为移动机器人在室内外的过渡区域提供稳定的定位导航信息。根据以上获得的定位导航数据,首先使用八叉树的octomap＿server算法构建二维栅格地图,然后采用射线地面滤波器Ray Ground Filter算法过滤三维激光产生的地面点云,最后采用move＿base导航包进行全局路径规划和局部路径规划。经实验测试室外定位数据精度为±1.5cm,航向角数据精度为±0.12°,数据刷新率100Hz;室内定位数据精度为±2.5cm,航向角数据精度为±0.1°,数据刷新率10Hz;室内外过渡区域两定位导航系统切换前后定位数据精度为±4cm,航向角数据精度为±0.5°。实验结果表明基于差分的GNSS定位系统、基于三维激光雷达的SLAM系统以及两系统组合导航的方法充分利用了环境的有效特征,提高了室内室外定位导航数据的精度和刷新率,适合作业路线分布在室内外的工业环境中应用。

关键词： GNSS 3D LiDAR 定位组合导航 loam