Location estimation of autonomous driving robot and 3D tunnel mapping in underground mines using pattern matched LiDAR sequential images

In this study,a machine vision-based pattern matching technique was applied to estimate the location of an autonomous driving robot and perform 3D tunnel mapping in an underground mine environment.The autonomous driving robot continuously detects the wall of the tunnel in the horizontal direction using the light detection and ranging(Li DAR)sensor and performs pattern matching by recognizing the shape of the tunnel wall.The proposed method was designed to measure the heading of the robot by fusion with the inertial measurement units sensor according to the pattern matching accuracy;it is combined with the encoder sensor to estimate the location of the robot.In addition,when the robot is driving,the vertical direction of the underground mine is scanned through the vertical Li DAR sensor and stacked to create a 3D map of the underground mine.The performance of the proposed method was superior to that of previous studies;the mean absolute error achieved was 0.08 m for the X-Y axes.A root mean square error of 0.05 m^(2)was achieved by comparing the tunnel section maps that were created by the autonomous driving robot to those of manual surveying.

Feasibility study applied to mapping tidal effects in the Pannonian basin--An effort to check location dependencies atμGal level

This paper summarizes the main instrumental and methodological points of the tidal research which was performed in the framework of the National Scientific Research Fund Project K101603. Since the project is still running the tidal analysis results published here are only preliminary. Unmodelled tidal effects have been highlighted in some recent absolute gravity measurements carried out in the Pannonian basin resulting in a periodic modulation exceeding the typical standard deviations （±1microGal） of the drop sets. Since the most dominant source of the daily gravity variation is the bulk tidal effect, the goal of the project is to check its location dependency at BGal level. Unfortunately Hungary has had no dedicated instrumentation, so an effort was made to make the available LaCoste- Romberg spring G meters capable for continuous recording. As a reference instrument the GWR SG025 operated in the Conrad Observatory, Austria was also used and in the mean time of the project, a Scintrex CG-5 became also available, Eventually 6 instruments at 5 different locations were operated for 3 9 months mainly in co-located configuration. Although many experiments （moving mass calibrations） were done to determine the scale factors and scale functions of the instruments, the direct comparison of the tidal parameters obtained from the observations is still questionable. Therefore the ratio of the delta factors of O1 and M2 tidal constituents was investigated supposing that M2 is much more influenced by the ocean loading effect than O1. The slight detected increase of δ（O1 ）/δ（M2） （≈0.2%） toward east does not contradict to theory. This result has to be validated in the near future by analyzing available ocean loading models.

RFID Complex Event Processing: Applications in Real-Time Locating System

Complex event processing (CEP) can extract meaningful events for real-time locating system (RTLS) applications. To identify complex event accurately in RTLS, we propose a new RFID complex event processing method GEEP, which is based on the timed automata (TA) theory. By devising RFID locating application into complex events, we model the timing diagram of RFID data streams based on the TA. We optimize the constraint of the event streams and propose a novel method to derive the constraint between objects, as well as the constraint between object and location. Experiments prove the proposed method reduces the cost of RFID complex event processing, and improves the efficiency of the RTLS.

Analyzing the Impact of Scene Transitions on Indoor Camera Localization through Scene Change Detection in Real-Time

Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems.The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed.This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence.An annotated image dataset trains the proposed system and predicts the camera pose in real-time.The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera pose.It also recognizes the scene changes during the sequence and evaluates the effects of these changes.This system achieved high accuracy and real-time performance.The scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact evaluation.Overall,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.

Real-time acquisition of compact volumetric maps

Building compact 3D maps of the environment models has become an important research topic. This paper presented an efficient stream decimation algorithm of massive meshes. The algorithm adapted the pre-processing step leading to lower in-corn memory consumption. This algorithm is applied to reconstructing compact terrain with mobile robot, achieving satisfying results.

Performance Evaluation of Three-Dimensional UWB Real-Time Locating Auto-Positioning System for Fire Rescue

Fire rescue challenges and solutions have evolved from straightfor-ward plane rescue to encompass 3D space due to the rise of high-rise city buildings.Hence,this study facilitates a system with quick and simplified on-site launching and generates real-time location data,enabling fire rescuers to arrive at the intended spot faster and correctly for effective and precise rescue.Auto-positioning with step-by-step instructions is proposed when launching the locating system,while no extra measuring instrument like Total Station(TS)is needed.Real-time location tracking is provided via a 3D space real-time locating system(RTLS)constructed using Ultra-wide Bandwidth technology(UWB),which requires electromagnetic waves to pass through concrete walls.A hybrid weighted least squares with a time difference of arrival(WLS/TDOA)positioning method is proposed to address real path-tracking issues in 3D space and to meet RTLS requirements for quick computing in real-world applications.The 3D WLS/TDOA algorithm is theoretically constructed with the Cramer-Rao lower bound(CRLB).The computing complexity is reduced to the lower bound for embedded hardware to directly compute the time differential of the arriving signals using the time-to-digital converter(TDC).The results of the experiments show that the errors are controlled when the positioning algorithm is applied in various complicated situations to fulfill the requirements of engineering applications.The statistical analysis of the data reveals that the proposed UWB RTLS auto-positioning system can track target tags with an accuracy of 0.20 m.

Research on Ubiquitous Map Information Organization Oriented to Location-Based Aggregation

In the era of information and communication technology (ICT) and big data, the map gradually shows a new qualitative feature of “spatiotemporal ubiquitous” due to the extension of its object space and the geographic information it contains, which brings new challenges to map information organization. This paper analyzes the concept and information characteristics of the ubiquitous map. Based on that, it proposes a ubiquitous map information organization model oriented to location-based aggregation. This new model includes three parts as “ubiquitous map instance”, “location-based aggregation mode” and “map scene”. This paper focuses on the “map scene” part which is the core of the model and contains two mutually mapped aspects as “content scene” and “representation scene”. And both aspects are divided into three levels as “features” ←→ “elements” ←→ “scenes” according to ubiquitous map information characteristics and location-based aggregation mode. With cases of map decomposition, the application of the model is explained to illustrate its effectiveness. The model is expected to provide powerful data organization and management capabilities for ubiquitous map production and use.

Scalability and Security in Identifier-to-Locator Mapping: Case Study for Locator/ID Separated Networks

The locator/ID separation paradigm has been widely discussed to resolve the serious scalability issue that today's Internet is facing. Many researches have been carried on with this issue to alleviate the routing burden of the Default Free Zone (DFZ), improve the traffic engineering capabilities and support efficient mobility and multi-homing. However, in the locator/ID split networks, a third party is needed to store the identifier-to-locator pairs. How to map identifiers onto locators in a scalable and secure way is a really critical challenge. In this paper, we propose SS-MAP, a scalable and secure locator/ID mapping scheme for future Internet. First, SS-MAP uses a near-optimal DHT to map identifiers onto locators, which is able to achieve the maximal performance of the system with reasonable maintenance overhead relatively. Second, SS-MAP uses a decentralized admission control system to protect the DHT-based identifier-to-locator mapping from Sybil attacks, where a malicious mapping server creates numerous fake identities (called Sybil identifiers) to control a large fraction of the mapping system. This is the first work to discuss the Sybil attack problem in identifier-to-locator mapping mechanisms with the best knowledge of the authors. We evaluate the performance of the proposed approach in terms of scalability and security. The analysis and simulation results show that the scheme is scalable for large size networks and can resistant to Sybil attacks.

The Improvement of Earthquake Real-Time Monitoring System of Chinese National Digital Seismic Network

The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In recent years,with the continuous improvement of monitoring technology and increase of public demands,the original real-time monitoring system needs to be upgraded and improved in terms of timeliness,stability,accuracy and ease of operation.Therefore,by accessing a total of more than 1,000 seismic stations,reducing the seismic trigger threshold of the monitoring system,eliminating the false trigger stations and optimizing the seismic waveform display interface,the current earthquake monitoring demands can be satisfied on the basis of ensuring the stable operation of the system.

Real-time localization for underwater equipment using an extremely low frequency electric field

A new real-time underwater equipment location method adopting an electric field induced by a standard current source is proposed.Our goals were real-time tracking and location of stationary or moving underwater equipment both in shallow and deep seas,under noisy conditions.The main features of this method are as follows:(1)a standard current source on the water surface,which can be towed by a vehicle,consisting of two electrodes,a signal generator,and a GPS unit;(2)measurement of the extremely low frequency(ELF)electric field emitted by the current source,made possible by electric field sensors on the underwater equipment;(3)position of the underwater equipment is estimated in real time based on a progressive update extended Kalman filter(PUEKF),which is carried out using the propagation model of an ELF electric field because the electric field at the position of the underwater equipment and the current source position are known.We verified the accuracy of our method and confirmed real-time location feasibility through numerical,physical scale,and real-time sea experiments.Through numerical experiments,we verified that our method works for underwater equipment location in real-world conditions,and the location error can be less than 0.2 m.Next,real-time location experiments for stationary underwater measuring equipment in water tank were conducted.The result shows that the location error can be less than 0.1 m.We also confirmed real-time location feasibility through the use of offshore experiment.We expect that our method will complement conventional underwater acoustic location methods for underwater equipment in acoustically noisy environments.

A User Proprietary Obfuscate System for Positions Sharing in Location-Aware Social Networks

A user’s trajectory can be maliciously monitored by adversaries when they share the positions in location-aware social networking applications which require users to update their own locations continuously. An adversary infers user’s locations from the trajectories, and gleans user’s private information through them via location-aware social networking applications and public available geographic data. In this paper, we propose a user proprietary obfuscate system to suit situations for position sharing and location privacy preserving in location-aware social network. Users transform the public available geographic data into personal obfuscate region maps with pre-defined profile to prevent the location leaking in stationary status. Our obfuscation with size restricted regions method tunes user’s transformed locations fitting into natural movement and prevents unreasonable snapshot locations been recorded in the trajectory.

An Algorithm and Data Process Scheme for Indoor Location Based on Mobile Devices

Limited by the sampling capacity of the mobile devices, many real-time indoor location systems have such problems as low accuracy, large variance, and non-smooth movement of the estimated position. A new positioning algorithm and a new processing method for sampled data are proposed. Firstly, a positioning algorithm is designed based on the cluster-based nearest neighbour or probability. Secondly, a weighted average method with sliding window is used to process the sampled data as to overcome the mobile devices’ weak capability of signal sampling. Experimental results show that, for the general mobile devices, the accuracy of indoor position estimation increases from 56.5% to 76.6% for a 2-meter precision, and from 77.4% to 90.9% for a 3-meter precision. Therefore, the proposed methods can significantly and stably improve the positioning accuracy.

基于Gmapping和A*算法的运输机器人系统的设计

在流行病毒活跃的季节,为了降低室内隔离点的病毒交叉感染几率,减轻医护人员负担,设计了可以根据医护人员指令完成室内医疗货物运输的防疫辅助机器人。机器人由背部的NVIDIA Tegra X2计算单元运行Ubuntu操作系统用于算法设计与功能开发,配有显示器、键盘摄像头、激光雷达。系统利用GMapping算法实现了机器人的定位与建图,并利用改进的A*算法和动态窗口法融合的方式进行路径规划。仿真实验结果表明,机器人建图轮廓清晰,误差在允许范围内,午间运行轨迹平滑且成功躲避行人,可以在确保安全性的前提下应用在运输机器人领域。

Design and implementation of user information sharing system using location-based services for social network services

Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communicating with others is focused on around the world.And location-based service(LBS)is a service that provides various life conveniences like improving productivity through location information,such as GPS and WiFi.This paper suggests an application combining LBS and SNS based on Android OS.By using smart phone which is personal mobile information equipment,it combines location information with user information and SNS so that the service can be developed.It also maximizes sharing and use of information via twit based on locations of friends.This proposed system is aims for users to show online identity more actively and more conveniently.

MapX在车辆定位信息管理系统中的应用

本文介绍了利用ＭａｐＸ控件开发车辆定位信息管理系统的基本原理和方法。介绍了ＭａｐＩｎｆｏ系列软件的组成结构和功能，并将它成功地应用于车辆定位信息管理系统，解决了用Ｖｉｓｕａｌ Ｃ＋＋对它编程的应用实践问题。

基于GSM和Google Map的定位与地图标注关键技术研究

介绍了一种基于GSM Modem和Google Map API的定位技术及其实现的解决方案.该方法借助和计算机连接的GSM Modem获取附近移动通信网络基站的信息,以此为条件查询获取基站经纬度数据,利用Google Map API在应用程序中嵌入电子地图,用查询的经纬度数据在电子地图上标定位置,从而实现了定位和电子地图上地理位置的标定.应用结果表明,该方法简单实用、成本低廉,可以在跟踪定位系统、物流监控等系统发挥积极作用.

基于MapX的农田无线设备的GPS定位系统设计研究

通过比较MapX控件在不同的开发环境下的应用特点,在LabVIEW开发环境下完成了冬枣栽培环境因子监测系统中的无线设备GPS定位功能。该功能还包括地图放大、地图缩小、漫游、测距等。运行结果表明,定位精度可以满足农业要求。

MapInfo电子海图技术在船舶导航系统中的应用

导航系统为船舶航行提供关键的位置信息服务和通讯服务,是船舶上不可缺少的组成部分。基于Map Info格式的电子海图具有图像处理性能高、成本低和兼容性强等优点,近年来逐渐引起研究人员的重视,并应用到船舶导航系统中。本文系统介绍Map Info电子海图的理论基础和结构组成,设计基于Map Info电子海图技术的船舶综合导航系统。

基于Eye Map和SIFT特征的人眼定位

人脸对齐是人脸识别的前提,精确的人眼定位是人脸对齐的主要手段,为此提出了一种基于eye map和SIFT特征的人眼定位方法。首先根据人眼眼球部分的像素灰度比周围像素灰度更黑的特点,在人脸图像中选出满足该特征的像素点,接着通过排序滤波器得到这些像素点的连续区域及它们的几何中心,然后根据人眼特征点的几何限制粗选出候选的眼球像素点,最后在候选点的特定区域内提取SIFT特征,并采用支持向量机回归的方法得到响应值最大的像素点,该点即为人眼的精确定位点。实验结果分析表明该方法既具有较高的定位精度又具有较快的计算速度。