浅谈提高空中三角测量数据成果质量的3个关键环节

空中三角测量数据主要是为摄影测量提供定向框架数据,其质量决定最终产品的质量。笔者结合生产实践中遇到的实际问题,对提高空中三角测量数据成果质量的3个关键环节——航外控制测量,航内控制点量测,外业控制点的残差分析、空中三角测量成果检查及评定的重要性进行了阐述。     

一种手工进行航线设计的算法

航线设计是每次飞行的基础,在航空摄影测量中,它占有重要的地位和作用。航线设计的好坏将直接影响航拍成果的质量,所以在进行每次航拍飞行之前都要对测区内的航线进行设计,以保证航飞的顺利进行。     

车载LiDAR点云中的建筑物特征提取

针对车载LiDAR点云数据处理复杂、时间长的问题,本文以地物不同特征值作为建筑物自动提取算法的依据,通过点云数据预处理、聚类分析等一系列流程最终实现一般建筑物点云的自动提取.通过两个实验区点云数据的提取与相应的实际地物进行精度分析对比,结果表明本文算法对实例测区环境下的不同建筑物点云提取具有较好的有效性,满足数字城市三...     

车辆碾压作用下戈壁地表起尘浓度

通过野外观测车辆碾压作用下戈壁地表PM₁₀释放浓度,探讨其主要影响因素。针对戈壁区砾石、砂砾、砂质和砂土4种路面类型,应用TSI粉尘仪多次重复观测车辆碾压产生的PM₁₀浓度,进而阐明碾压次数、车速和地表水分等因素对起尘浓度的影响。结果表明：4种路面的平均起尘浓度依次为5.339、9.089、16.944、50.251 mg·m^-3,是自然状态下的5~50倍;起尘浓度随碾压次数增多而增大,其中砂土路情况下的增长最显著;随土层厚度的增大呈现出幂函数的增长趋势;降雨后路面起尘浓度显著减小,且降雨量会影响降雨后起尘浓度的变化趋势。最后提出了针对性的建议和措施以减弱车辆碾压导致的戈壁地表起尘。     

无人机倾斜摄影支持下的1∶500高精度三维测图方案及应用

研发了一种适合于大范围1∶500的无人机测图方案,围绕平面和高程点位中误差在5 cm以内这一核心目标,从无人机的平台稳定性、空中精准定位飞控、空三与三维建模及模型与影像结合的多视角测图等方面进行了设计。在广州马沥村的应用表明,本文研究的无人机倾斜摄影方案可以满足1∶500高精度的三维测图,并具有较高的效率。     

国家应急测绘调度系统设计

通过分析应急测绘指挥调度的基本特点与实际需求,结合国家应急标准规范,采用基于多通道多协议的数据通信与传输技术、基于MPP架构的分布式数据库管理技术、基于UML模型化的任务规划技术,根据无人机、多功能方舱等应急装备实时回传的位置、状态和应急测绘地理信息,以及快速处理与共享系统等产生的数据成果与作业信息,设计完成了具有应急调度方案制定、指令快速下达、测绘装备动态调度与实时跟踪、测绘任务进度监控及应急任务演练等功能的应急测绘调度系统。     

无人海洋测绘技术体系构建

随着无人技术的快速发展,无人测绘的时代即将到来。本文分析了无人时代技术特征与海洋测绘发展机遇;讨论了无人海洋测绘新理念,构建了无人海洋测绘技术体系,论述了无人海洋测绘技术关键技术;展望了无人海洋测绘技术发展趋势,及其在海洋经济、海洋可持续发展中的应用前景。     

Closed-loop randomized kinodynamic path planning for an autonomous underwater vehicle

A randomized kinodynamic path planning algorithm based on the incremental sampling-based method is proposed here as the state-of-the-art in this field applicable in an autonomous underwater vehicle. Designing a feasible path for this vehicle from an initial position and velocity to a target position and velocity in three-dimensional spaces by considering the kinematic constraints such as obstacles avoidance and dynamic constraints such as hard bounds and non-holonomic characteristic of AUV are the main motivation of this research. For this purpose, a closed-loop rapidly-exploring random tree (CL-RRT) algorithm is presented. This CL-RRT consists of three tightly coupled components: a RRT algorithm, three fuzzy proportional-derivative controllers for heading and diving control and a six degree-of-freedom nonlinear AUV model. The branches of CL-RRT are expanded in the configuration space by considering the kinodynamic constraints of AUV. The feasibility of each branch and random offspring vertex in the CL-RRT is checked against the mentioned constraints of AUV. Next, if the planned branch is feasible by the AUV, then the control signals and related vertex are recorded through the path planner to design the final path. This proposed algorithm is implemented on a single board computer (SBC) through the xPC Target and then four test-cases are designed in 3D space. The results of the processor-in-the-loop tests are compared by the conventional RRT and indicate that the proposed CL-RRT not only in a rapid manner plans an initial path, but also the planned path is feasible by the AUV.     

URANS investigation of the interaction between the free surface and a shallowly submerged underwater vehicle at steady drift

An axisymmetric underwater vehicle (UV) at a steady drift angle experiences the complex three-dimensional crossflow separation. This separation arises from the unfavorable circumferential pressure gradient developed from the windward side toward the leeward side. As is well known, the separated flow in the leeward side gives rise to the formation of a pair of vortices, which affects considerably the forces and moments acting on the UV. In this regard, the main purpose of the present study is to evaluate the role of the leeward vortical flow structure in the hydrodynamic behavior of a shallowly submerged UV at a moderate drift angle traveling beneath the free surface. Accordingly, the static drift tests are performed on the SUBOFF UV model using URANS equations coupled with a Reynolds stress turbulence model. The simulations are carried out in the commercial code STARCCM+ at a constant advance velocity based on Froude number equal to F_n = 0.512 over submergence depths and drift angles ranging from h = 1.1D to h = ∞ and from β = 0 to β = 18.11°, respectively. The validation of the numerical model is partially conducted by using the existing experimental data of the forces and moment acting on the totally submerged bare hull model. Significant interaction between the low-pressure region created by the leeward vortical flow structure and the free surface is observed. As a result of this interaction, the leeward vortical flow structure appears to be largely responsible for the behavior of the forces and moments exerted on a shallowly submerged UV at steady drift.     

Experimental Study of a Command Governor Adaptive Depth Controller for an Unmanned Underwater Vehicle

Unmanned Underwater Vehicles (UUVs) are increasingly being used in advanced applications that require them to operate in tandem with human divers and around underwater infrastructure and other vehicles. These applications require precise control of the UUVs which is challenging due to the non-linear and time varying nature of the hydrodynamic forces, presence of external disturbances, uncertainties and unexpected changes that can occur within the UUV’s operating environment. Adaptive control has been identified as a promising solution to achieve desired control within such dynamic environments. Nevertheless, adaptive control in its basic form, such as Model Reference Adaptive Control (MRAC) has a trade-off between the adaptation rate and transient performance. Even though, higher adaptation rates produce better performance they can lead to instabilities and actuator fatigue due to high frequency oscillations in the control signal. Command Governor Adaptive Control (CGAC) is a possible solution to achieve better transient performance at low adaptation rates. In this study CGAC has been experimentally validated for depth control of a UUV, which is a unique challenge due to the unavailability of full state measurement and a greater thrust requirement. These in turn leads to additional noise from state estimation, time-delays from input noise filters, higher energy expenditure and susceptibility to saturation. Experimental results show that CGAC is more robust against noise and time-delays and has lower energy expenditure and thruster saturation. In addition, CGAC offers better tracking, disturbance rejection and tolerance to partial thruster failure compared to the MRAC.