Glass Recognition and Map Optimization Method for Mobile Robot Based on Boundary Guidance

Current research on autonomous mobile robots focuses primarily on perceptual accuracy and autonomous performance.In commercial and domestic constructions,concrete,wood,and glass are typically used.Laser and visual mapping or planning algorithms are highly accurate in mapping wood panels and concrete walls.However,indoor and outdoor glass curtain walls may fail to perceive these transparent materials.In this study,a novel indoor glass recognition and map optimization method based on boundary guidance is proposed.First,the status of glass recognition techniques is analyzed comprehensively.Next,a glass image segmentation network based on boundary data guidance and the optimization of a planning map based on depth repair are proposed.Finally,map optimization and path-planning tests are conducted and compared using different algorithms.The results confirm the favorable adaptability of the proposed method to indoor transparent plates and glass curtain walls.Using the proposed method,the recognition accuracy of a public test set increases to 94.1%.After adding the planning map,incorrect coverage redundancies for two test scenes reduce by 59.84%and 55.7%.Herein,a glass recognition and map optimization method is proposed that offers sufficient capacity in perceiving indoor glass materials and recognizing indoor no-entry regions.

General mapping of one-dimensional non-Hermitian mosaic models to non-mosaic counterparts:Mobility edges and Lyapunov exponents

We establish a general mapping from one-dimensional non-Hermitian mosaic models to their non-mosaic counterparts.This mapping can give rise to mobility edges and even Lyapunov exponents in the mosaic models if critical points of localization or Lyapunov exponents of localized states in the corresponding non-mosaic models have already been analytically solved.To demonstrate the validity of this mapping,we apply it to two non-Hermitian localization models:an Aubry-Andre-like model with nonreciprocal hopping and complex quasiperiodic potentials,and the Ganeshan-Pixley-Das Sarma model with nonreciprocal hopping.We successfully obtain the mobility edges and Lyapunov exponents in their mosaic models.This general mapping may catalyze further studies on mobility edges,Lyapunov exponents,and other significant quantities pertaining to localization in non-Hermitian mosaic models.

Locating Global System for Mobile Communication(GSM)Base Stations Using Geographic Information System(GIS)

The global system for mobile communication(GSM)is planned to meet the needs of the whole subscribers.The number of subscribers increased as the population increased due to the acceptance of GSM services by the subscribers.Thus,there should be a way to monitor base stations that will meet the increasing demand of subscribers in any area as a population surge will lead to more subscriptions.This will allow GSM network operators to serve their subscribers better and ease network congestion.This work presents a review of mobile evolution from the first generation to the fifth generation.A review of global positioning system(GPS)technology and its applications to geographic information systems(GIS)was done.The coordinates of these base stations were taken using a GPS device.These base station coordinates were then exported to QGIS for the design of the map.Thereafter,the output map was then integrated into the website.The discussions on the results followed and some useful suggestions given will go a long way to help the operators of GSM in Nigeria and in general.If the propositions given are adhered to,it will go a long way to help the operators reduce congestion on their network and thereby increase the satisfaction of the subscribers.

Robust Iterated Sigma Point FastSLAM Algorithm for Mobile Robot Simultaneous Localization and Mapping

Simultaneous localization and mapping （SLAM） is a key technology for mobile robots operating under unknown environment. While FastSLAM algorithm is a popular solution to the SLAM problem, it suffers from two major drawbacks： one is particle set degeneracy due to lack of observation information in proposal distribution design of the particle filter; the other is errors accumulation caused by linearization of the nonlinear robot motion model and the nonlinear environment observation model. For the purpose of overcoming the above problems, a new iterated sigma point FastSLAM （ISP-FastSLAM） algorithm is proposed. The main contribution of the algorithm lies in the utilization of iterated sigma point Kalman filter （ISPKF）, which minimizes statistical linearization error through Gaussian-Newton iteration, to design an optimal proposal distribution of the particle filter and to estimate the environment landmarks. On the basis of Rao-Blackwellized particle filter, the proposed ISP-FastSLAM algorithm is comprised by two main parts： in the first part, an iterated sigma point particle filter （ISPPF） to localize the robot is proposed, in which the proposal distribution is accurately estimated by the ISPKF; in the second part, a set of ISPKFs is used to estimate the environment landmarks. The simulation test of the proposed ISP-FastSLAM algorithm compared with FastSLAM2.0 algorithm and Unscented FastSLAM algorithm is carried out, and the performances of the three algorithms are compared. The simulation and comparing results show that the proposed ISP-FastSLAM outperforms other two algorithms both in accuracy and in robustness. The proposed algorithm provides reference for the optimization research of FastSLAM algorithm.

A novel method for mobile robot simultaneous localization and mapping

A novel mobile robot simultaneous localization and mapping (SLAM) method is implemented by using the Rao- Blackwellized particle filter (RBPF) for monocular vision-based autonomous robot in unknown indoor environment. The particle filter combined with unscented Kalman filter (UKF) for extending the path posterior by sampling new poses integrating the current observation. Landmark position estimation and update is implemented through UKF. Furthermore, the number of resampling steps is determined adaptively, which greatly reduces the particle depletion problem. Monocular CCD camera mounted on the robot tracks the 3D natural point landmarks structured with matching image feature pairs extracted through Scale Invariant Feature Transform (SIFT). The matching for multi-dimension SIFT features which are highly distinctive due to a special descriptor is implemented with a KD-Tree. Experiments on the robot Pioneer3 showed that our method is very precise and stable.

Mobile Robot Hierarchical Simultaneous Localization and Mapping Using Monocular Vision

A hierarchical mobile robot simultaneous localization and mapping (SLAM) method that allows us to obtain accurate maps was presented. The local map level is composed of a set of local metric feature maps that are guaranteed to be statistically independent. The global level is a topological graph whose arcs are labeled with the relative location between local maps. An estimation of these relative locations is maintained with local map alignment algorithm, and more accurate estimation is calculated through a global minimization procedure using the loop closure constraint. The local map is built with Rao-Blackwellised particle filter (RBPF), where the particle filter is used to extending the path posterior by sampling new poses. The landmark position estimation and update is implemented through extended Kalman filter (EKF). Monocular vision mounted on the robot tracks the 3D natural point landmarks, which are structured with matching scale invariant feature transform (SIFT) feature pairs. The matching for multi-dimension SIFT features is implemented with a KD-tree in the time cost of O(lbN). Experiment results on Pioneer mobile robot in a real indoor environment show the superior performance of our proposed method.

A New Dynamic Self-Organizing Method for Mobile Robot Environment Mapping

To solve the mapping problem for the mobile robots in the unknown environment, a dynamic growing self-organizing map with growing-threshold tuning automatically algorithm (DGSOMGT) based on Self-organizing Map is proposed. It introduces a value of spread factor to describe the changing process of the growing threshold dynamically. The method realizes the network structure growing by training through mobile robot movement constantly in the unknown environment. The proposed algorithm is based on self-organizing map and can adjust the growing-threshold value by the number of network neurons increasing. It avoids tuning the parameters repeatedly by human. The experimental results show that the proposed method detects the complex environment quickly, effectively and correctly. The robot can realize environment mapping automatically. Compared with the other methods the proposed mapping strategy has better topological properties and time property.

Methodology for Road Defect Detection and Administration Based on Mobile Mapping Data

A detailed inspection of roads requires highly detailed spatial data with sufficient precision to deliver an accurate geometry and to describe road defects visually.This paper presents a novel method for the detection of road defects.The input data for road defect detection included point clouds and orthomosaics gathered by mobile mapping technology.The defects were categorized in three major groups with the following geometric primitives:points,lines and polygons.The method suggests the detection of point objects from matched point clouds,panoramic images and ortho photos.Defects were mapped as point,line or polygon geometries,directly derived from orthomosaics and panoramic images.Besides the geometric position of road defects,all objects were assigned to a variety of attributes:defect type,surface material,center-of-gravity,area,length,corresponding image of the defect and degree of damage.A spatial dataset comprising defect values with a matching data type was created to perform the attribute analysis quickly and correctly.The final product is a spatial vector data set,consisting of points,lines and polygons,which contains attributes with further information and geometry.This paper demonstrates that mobile mapping suits a large-scale feature extraction of road infrastructure defects.By its simplicity and flexibility,the presented methodology allows it to be easily adapted to extract further feature types with their attributes.This makes the proposed approach a vital tool for data extraction settings with multiple mobile mapping data analysts,e.g.,offline crowdsourcing.

Design of e-Land Record Information System with Google Map Using Mobile Commerce

e-Governance facilities are being used nowadays by citizens in various Government projects of the country. But the integration of mobile technologies with the e-Governance projects can lead to more human interaction and benefits for the society as a whole. This will result in having more impact on the lives of the common citizens and increase in awareness of such e-Governance projects. The paper introduces the features, technologies and design of the Android mobile device application, mobileLoanapp for the customer (client) of the bank for the loan approval process. The e-Land record information system has been designed and implemented with Google Map using Mobile Commerce by developing this mobile app. This m-app has been developed so as to provide improved and flexible e-Governance facility to the common citizens of the country. The proposed system if adapted will pave the way for the real-time applications to be embedded with the e-Governance facilities. This paper presents the overall system architecture along with its functional components and scope of the very appealing m-application (mobileLoanapp) for bank loan approval process in interconnection with the land server (part of Farad Kendra’s). The overall advantages of the proposed m-app have also been determined in comparison to the existing e-Governance system, giving a viable option to adopt and make use of integration of mobile technologies for providing e-Governance through this m-app.

MAP网络应用层MMS软件设计

本文首先介绍了制造信息规范(MMS:Manufacturing Message Specification)的三种服务方式以及MMS服务的主要功能,然后,提出了如何从庞大的MMS服务集中选取一个满足功能要求的MMS子集。

基于MapXMobile的嵌入式开发

MapX Mobile是MapInfo公司提供的专用于嵌入式设备上应用程序开发的控件,提供了简单、快速的方法把地图功能嵌入到手持设备的应用程序中,它可以在你的PocketPC应用程序上实现多种地图操作功能。介绍了MapXMobile的一些特性及应用,探讨用MapXMobile进行嵌入式终端———PDA(个人数字助理)的开发方法,在PDA上实现了地图的浏览、查询显示等功能,并结合GPS设备,实现了公交站点的测量功能,较好地实现了空间信息与非空间信息的结合。

An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D images.The current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time performance.To address these issues,we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space model.Then,an indoor RGB-D image semantic segmentation network is proposed,which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud model.Finally,Bayesian updating is used to conduct incremental semantic label fusion on the established spatial point cloud model.We also employ dense conditional random fields(CRF)to optimize the 3D semantic map model,resulting in a high-precision spatial semantic map of indoor scenes.Experimental results show that the proposed semantic mapping system can process image sequences collected by RGB-D sensors in real-time and output accurate semantic segmentation results of indoor scene images and the current local spatial semantic map.Finally,it constructs a globally consistent high-precision indoor scenes 3D semantic map.

Localization of Mobile Robot Aided for Large-Scale Construction Based on Optimized Artificial Landmark Map in Ongoing Scene

The effectiveness of mobile robot aided for architectural construction depends strongly on its accurate localization ability.Localization of mobile robot is increasingly important for the printing of buildings in the construction scene.Although many available studies on the localization have been conducted,only a few studies have addressed the more challenging problem of localization for mobile robot in large-scale ongoing and featureless scenes.To realize the accurate localization of mobile robot in designated stations,we build an artificial landmark map and propose a novel nonlinear optimization algorithm based on graphs to reduce the uncertainty of the whole map.Then,the performances of localization for mobile robot based on the original and optimized map are compared and evaluated.Finally,experimental results show that the average absolute localization errors that adopted the proposed algorithm is reduced by about 21%compared to that of the original map.

基于MMS模型的继电保护装置自动测试技术研究

提出一种基于MMS模型的继电保护装置自动测试技术,该技术能够自动模拟继电保护装置的输入信息,自动验证输出信息,通过MMS报文读写保护装置的定值、控制字、软压板,针对各厂家“六统一”保护型号功能配置,建立典型测试模板库,实现继电保护装置一键式测试,并通过中间模型文件解决了不同厂家的保护装置数据输出端口信息描述不统一的问题,实现模型自动映射。最后以某型号线路保护装置测试为例验证所提方法的可行性。

Interconnection of MAP and BITBUS Based on MMS

A method of implementing the interconnection of MAP and BITBUS based on MMS is presented. The important features and principles of MMS are discussed and a survey of MMS implementation in MAP network is given. The establishment of a set of MMS services in

Map Building for a Mobile Robot Based on Grey System Theory

In this paper, a new method for mobile robot map building based on grey system theory is presented, by which interpretation and integration of sonar readings can be solved robustly and efficiently. The conception of 'grey number is introduced to model and handle the uncertainty of sonar reading. A new data fusion approach based on grey system theory is proposed to construct environment model. Map building experiments are performed both on a platform of simulation and a real mobile robot. Experimental results show that our method is robust and accurate.

The Digital Age of Campus Maps on Mobile Devices

Developing mobile applications have always been a rising topic in the technology world. With the recent development in technology, mobile applications play an important role in various applications throughout the world. Mobile applications are constantly evolving. There are several ongoing research and developments in both industry and academia. In this paper, we present the design and implementation of a mobile application that creates an electronic map or e-map application for the campus of Tuskegee University. The goals for this mobile application are to make the campus map easier and user-friendly for parents, visitors, and students using mobile devices. With this mobile application, the users will be able to search and find campus buildings, as well as give feedback on the application to eliminate the need for paper documentation.

Mobile Spatial Information Service Based on Intelligent Map Agent

This paper analyzes the existing spatial structure of mobile information services and the current new characteristics of the service, proposes a new service model. The model adopts a unified deployment solution of spatial data. It extends the spatial data management and lightweight computing to the embedded computing devices, and enhanced the service flexibility and scalability. The design of mobile side achieves the integration of spatial data management, mobile computing and wireless communication, and it can meet the various needs of spatial information mobile services. The paper introduces the composition of the new model and the key contents, and pointing out that this model is the inevitable trend of spatial information mobile services.

Ant Colony Optimization with Potential Field Based on Grid Map for Mobile Robot Path Planning

For the mobile robot path planning under the complex environment,ant colony optimization with artificial potential field based on grid map is proposed to avoid traditional ant colony algorithm's poor convergence and local optimum.Firstly,the pheromone updating mechanism of ant colony is designed by a hybrid strategy of global map updating and local grids updating.Then,some angles between the vectors of artificial potential field and the orientations of current grid are introduced to calculate the visibility of eight-neighbor cells of cellular automata,which are adopted as ant colony's inspiring factor to calculate the transition probability based on the pseudo-random transition rule cellular automata.Finally,mobile robot dynamic path planning and the simulation experiments are completed by this algorithm,and the experimental results show that the method is feasible and effective.