Multi-sensor data fusion for UAV navigation during landing operations

This paper presents a practical framework to synthesize multi-sensor navigation information for localization of a rotary-wing unmanned aerial vehicle (RUAV) and estimation of unknown ship positions when the RUAV approaches the landing deck. The estimation performance of the visual tracking sensor can also be improved through integrated navigation. Three different sensors (inertial navigation, Global Positioning System, and visual tracking sensor) are utilized complementarily to perform the navigation tasks for the purpose of an automatic landing. An extended Kalman filter (EKF) is developed to fuse data from various navigation sensors to provide the reliable navigation information. The performance of the fusion algorithm has been evaluated using real ship motion data. Simulation results suggest that the proposed method can be used to construct a practical navigation system for a UAV-ship landing system.

Multi-sensors data acquisition and information fusion for manned submersible vehicle

本文介绍了一种用于载人潜水器的导航传感器的数据采集及信息融合技术。航行控制计算机通过基于工业以太网的数据通信系统对各传感器进行数据采集,采用卡尔曼滤波器完成对各传感器数据信息的融合,以便提高数据的精度和控制系统的性能,并将结果送给监控计算机,用于载人潜水器的姿态显示。

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported

Intelligence Algorithms for Increasing Navigation Systems Accuracy

Application of neural network algorithm for increasing the accuracy of navigation systems are showing. Various navigation systems, where a couple of sensors are used in the same device in different positions and the disturbances act equally on both sensors, the trained neural network can be advantageous for increasing the accuracy of system. The neural algorithm had used for determination the interconnection between the sensors errors in two channels to avoid the unobservation of navigation system. Representation of thermal error of two- component navigation sensors by time model, which coefficients depend only on parameters of the device, its orientations relative to disturbance vector allows to predict thermal errors change, measuring the current temperature and having identified preliminary parameters of the model for the set position. These properties of thermal model are used for training the neural network and compensation the errors of navigation system in non- stationary thermal fields.

深水机器人低成本导航系统的位置估计方法研究

依据6000米自治水下机器人及其长基线声学定位系统现有的导航设备,将测距声信标和机器人载体携带的低成本导航传感器:涡轮式计程仪,压力传感器以及TCM2电子罗盘测量的导航数据相融合,分别提出两种基于EKF的导航数据融合算法,对机器人的位置以及水流参数进行估计,解决复杂环境下的深水机器人位置估计问题.蒙特卡洛仿真实验和湖上试验数据后处理表明,设计的位置估计算法收敛快,精度高,计算时间小,能够满足深水机器人的导航需要.

主从式UUV群的随从UUV导航

单只水下机器人导航方法存在着各自的缺陷,无法满足低成本UUV群的作业需要。建立由一只具有高精度自主导航能力的主UUV和多只由低成本导航传感器的随从UUV组成的一主多从式UUV群,研究随从UUV导航方法。与前人的极坐标化方法不同,在直角坐标系下对随从UUV导航系统进行了能观性证明。随从UUV通过测距传感器测量自身到主UUV的距离,采用EKF算法进行位置估计,给出了机动航行方案。仿真实验证明了有效性。

AUV自主导航航位推算算法的分析研究

地球形状的不规则性,各种导航传感器本身的误差,以及仪器的安装偏差等,使得AUV(自治水下机器人)在进行远距离自主航行时,自主导航的精度大大下降。针对以上问题及实际工程需要,论文对AUV自主导航的航位推算算法做了进一步研究并加以改进,以提高其自主导航精度。最后,利用2004年中国科学院沈阳自动化所水下机器人研究中心进行AUV湖试所获得的数据,对文中提出的算法进行了验证。结果表明,AUV的自主导航精度得到大大提高,可以用于修正原来的自主导航算法。

Autonomous Surface Vehicle Docking Manoeuvre with Visual Information

This work presents a hybrid coordinated manoeuvre for docking an autonomous surface vehicle with an autonomous underwater vehicle. The control manoeuvre uses visual information to estimate the AUV relative position and attitude in relation to the ASV and steers the ASV in order to dock with the AUV. The AUV is assumed to be at surface with only a small fraction of its volume visible. The system implemented in the autonomous surface vehicle ROAZ, developed by LSA-ISEP to perform missions in river environment, test autonomous AUV docking capabilities and multiple AUV/ASV coordinated missions is presented. Information from a low cost embedded robotics vision system (LSAVision), along with inertial navigation sensors is fused in an extended Kalman filter and used to determine AUV relative position and orientation to the surface vehicle The real time vision processing system is described and results are presented in operational scenario.

Efeitos da injunção da base nas orientações interior e exterior e nas coordenadas do espaço objeto em imagens obtidas com a estéreo vídeo-câmara de um sistema móvel de mapeamento

In general, a land-based mobile mapping system is featured by a vehicle with a pair of video cameras mounted on the top and positioning and navigation sensors loaded in the vehicle. Considering the pair of video cameras mounted on the roof of the vehicle as a stereo camera pointing forward with both optical axes parallel to each other and orthogonal to the stereo base, whose length is 0.94 m, this paper aims at analyzing the interior and exterior camera orientation and the object point coordinates estimated by phototriangulation when the length constraint related to the stereo base is considered or not. The results show that the stereo base constraint has effect ouver the convergence estimation, but does it neither improves the object point coordinate estimation at significance level of 5% and nor it influences the interior orientation parameters. Finally, it has been noticed that the optical axes are not truly parallel to each other and orthogonal to the stereo base. Additionally, it has been observed that there is a convergence of approximately 0.5 degrees in the optical axes and they are not in the same plane (approximately 0.8 degrees deviation).

Indirect georeferencing of terrestrial laser scanning data using control lines

An indirect method for the georeferencing of 3D point clouds obtained with terrestrial laser scanning (TLS) data using control lines is presented. This technique could be used for rapid data acquisition where resources do not permit the use of expensive navigation sensors or the placement of pre-signalised targets. The most important characteristic is the development of a mathematical model based on the principle that the direction vector of the TLS straight line is coplanar with the plane defined by the origin of the TLS system, one endpoint of a control line and the direction vector of the control line in the ground reference coordinate system. The transformation parameters are estimated by minimising the distance between the control lines and their corresponding TLS straight lines. The proposed method was tested using both simulated and real data, and the advantages of this new approach are compared with conventional surveying methods. © 2013 This article is a U.S. Government work and is in the public domain in the USA.

Influência da injunção da base na fototriangulação de imagens obtidas com uma unidade de mapeamento móvel

Pós-graduação em Ciências Cartográficas - FCT