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.

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。

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.

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.

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.

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.

Mobile robot simultaneous localization and map building based on improved particle filter

We present an investigation into the use of pan tilt zoom camera and sonar sensors for simuhaneous localization and mapping with artificial colored landmarks. An improved particle filter is applied to estimate a posterior of the pose of the robot, in which each particle has associated it with an entire map. The distributions of landmarks are also represented by particle sets, where separate particles are used to represent the robot and the landmarks. Hough transform is used to extract line segments from sonar observations and build map simultaneously. The key advantage of our method is that the full posterior over robot poses and landmarks can be nonlinearly approximated at every point in time by particles. Especially the landmarks are affixed on the moving robots, which can reduce the impact of the depletion problem and the impoverishment problem produced by basic particle filter. Experimental results show that this approach has advantages over the basic particle filter and the extended Kalman filter.

基于Mobile SVG的移动通信地图服务

分析了目前移动通信服务技术,采用Mobile SVG组织地图数据,选择J2ME利用手机提供地图服务,设计了基于J2ME/Mobile SVG的手机地图服务,并对关键技术进行了解析。

基于SMS和Windows Mobile的手持式地理信息汇报系统

介绍一种基于SMS和Windows Mobile的手持式地理信息汇报系统,探讨了一种利用目前现成的移动通信设施实现对带有GPS定位功能的手持智能设备持有者监控的系统。本系统利用目前流行的短信系统(SMS)作为数据传输手段,传送手持智能设备持有者的地理信息数据。使用SMS传输数据通信可靠,费用低廉,且覆盖范围广。

A Switching Controller System for a Wheeled Mobile Robot

A wheeled mobile mechanism with a passive and/or active linkage mechanism for rough terrain environment is developed and evaluated. The wheeled mobile mechanism which has high mobility in rough terrain needs sophisticated system to adapt various environments. We focus on the development of a switching controller system for wheeled mobile robots in rough terrain. This system consists of two sub-systems： an environment recognition system using link angles and an adaptive control system. In the environment recognition system, we introduce a Self-Organizing Map （SOM） for clustering link angles. In the adaptive controllers, we introduce neural networks to calculate the inverse model of the wheeled mobile robot. The environment recognition system can recognize the environment in which the robot travels, and the adjustable controllers are tuned by experimental results for each environment. The dual sub-system switching controller system is experimentally evaluated. The system recognizes its environment and adapts by switching the adjustable controllers. This system demonstrates superior performance to a well-tuned single PID controller.

A Mobile GIS Application to Heavily Resource-Constrained Devices

GIS applications to mobile devices are becoming i nc reasingly popular, utilizing a di-verserange of devices. Many of these devices suffer from serious constraints in three main areas: processor speed, memory space and screen size. This paper presents a GIS application, called "MacaoMap", that is intended for heavily resource-co nstrained handheld devices. MacaoMap is a tourism-oriented map application of t he Macao territory for PalmOS and Pocket PC personal digital assistants. It was designed to perform satisfactorily on devices with as little as 16 MHz processor speed, and requires only 500 KB available memory for the GIS application and al l GIS data. Memory requirements are kept low through a specially designed data f ormat. The main challenge of satisfactory map drawing speed is addressed through a variety of techniques that were developed for this application. The paper des cribes the application’s data format, outlines the map drawing techniques, and points out the areas for future development.