Radar style transfer for metric robot localisation on lidar maps

Lidar and visual data are affected heavily in adverse weather conditions due to sensing mechanisms,which bring potential safety hazards for vehicle navigation.Radar sensing is desirable to build a more robust navigation system.In this paper,a cross-modality radar localisation on prior lidar maps is presented.Specifically,the proposed workflow consists of two parts:first,bird's-eye-view radar images are transferred to fake lidar images by training a generative adversarial network offline.Then with online radar scans,a Monte Carlo localisation framework is built to track the robot pose on lidar maps.The whole online localisation system only needs a rotating radar sensor and a pre-built global lidar map.In the experimental section,the authors conduct an ablation study on image settings and test the proposed system on Oxford Radar Robot Car Dataset.The promising results show that the proposed localisation system could track the robot pose successfully,thus demonstrating the feasibility of radar style transfer for metric robot localisation on lidar maps.

Feature extraction of gear-localized defect using adaptive lifting scheme and local gradient maps

In this paper,the adaptive lifting scheme (ALS) and local gradient maps (LGM) are proposed to isolate the transient feature components from the gearbox vibration signals. Based on entropy minimization rule,the ALS is employed to change properties of an initial wavelet and design adaptive wavelet. Then LGM is applied to characterize the transient feature components in detail signal of decomposition results using ALS. In the present studies, the orthogonal Daubechies 4 (Db 4) wavelet is used as the initial wavelet. The proposed method is applied to both simulated signals and vibration signals acquired from a gearbox for periodic impulses detection. The two conventional methods (cepstrum analysis and Hilbert envelope analysis) and the orthogonal Db4 wavelet are also used to analyze the same signals for comparison. The results demonstrate that the proposed method is more effective in extracting transient components from noisy signals.

Approach of simultaneous localization and mapping based on local maps for robot

An extended Kalman filter approach of simultaneous localization and mapping(SLAM) was proposed based on local maps. A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.

基于Google Maps的甘肃旅游景点Web GIS构建

基于Google Maps API,利用开源Flash框架Flex、PHP及开源数据库MySQL,构建基于Web的地方景点Web GIS展示系统,以电子地图方式灵活地实现了景点分类查询、景点查询展示、行车路线查询等功能。介绍了系统设计思路、主要功能及其实现方法。

基于Flex与Google Maps的地方特产Web GIS构建

基于Google Maps API,利用开源Flash框架Flex、PHP及开源数据库MySQL,构建基于Web的地方特产Web GIS展示系统,以电子地图方式灵活地实现了特产分类查询、特产查询展示、行车路线查询等功能。介绍了系统设计思路,主要功能及其实现方法。

Comparison of Digital Maps: Recognition and Quantitative Measure of Changes

A new methodology of comparing digital raster maps was proposed which allows not only detecting changes in the maps, but also obtaining quantitative measures of the importance of selected differences. Procedure of object interpretation of satellite images and forming of OMT (Object Map of Territory) is described. A list of allowable differences between two OMTs is defined. Two steps technique of quantitative measuring is proposed. At the first stage functions are constructed for calculating local measures of differences in the amount, areas and locations of objects on the map, as well as relations between the objects. In the second stage local measures are used to calculate the integral measure in order to get generalized assessment of difference between maps. The methods for constructing functions which calculate local and integral measures of differences are described. Examples of comparing and measuring the differences between OMTs are provided. Obtained results by utilizing this technique can be used to analyze trends, forecast of development and might be helpful for choosing most efficient scenarios for sustainable spatial planning and land management.

Local connectivity of the Julia set for geometrically finite rational maps

It is proved that each (eventually) periodic connected component of the Julia set of a geometrically finite rational map is locally connected.

Local deformation and processing maps of Ti-24Al-17Nb-0.5Mo alloy

The processing maps were used to identify the optimal forging parameters of Ti-24A1- 17Nb-0.5Mo alloy by evaluating the flow data according to the DMM model. The actual local strain rate and strain distribution in the samples were obtained by finite element calculations. The local microstructures of the deformed samples were related to the local deformation parameters and correlated with the processing maps at 0.3, 0.4, 0.5 and 0.6 of logarithmic strain. Flow regimes predicted by DMM analysis were then correlated with the local microstructural observations. Five domains of efficient coefficient could be distinguished. Unstable regions were microstructurally related to shear band formation within the （~2~B2 phase deformation field, and to flow localiza- tion at grain boundaries of B2 phase in the near B2 phase deformation field. Stable flow regimes were shown to be associated with dynamic globularization of the plate- like a2 in the a2＋B2 phase deformation zone, and with dynamic recrystallization of B2 in the near B2 phase deformation zone.

Hand-feel soil texture observations to evaluate the accuracy of digital soil maps for local prediction of soil particle size distribution:A case study in Central France

Digital maps of soil properties are now widely available.End-users now can access several digital soil mapping(DSM)products of soil properties,produced using different models,calibration/training data,and covariates at various spatial scales from global to local.Therefore,there is an urgent need to provide easy-to-understand tools to communicate map uncertainty and help end-users assess the reliability of DSM products for use at local scales.In this study,we used a large amount of hand-feel soil texture(HFST)data to assess the performance of various published DSM products on the prediction of soil particle size distribution in Central France.We tested four DSM products for soil texture prediction developed at various scales(global,continental,national,and regional)by comparing their predictions with approximately 3200 HFST observations realized on a 1:50000 soil survey conducted after release of these DSM products.We used both visual comparisons and quantitative indicators to match the DSM predictions and HFST observations.The comparison between the low-cost HFST observations and DSM predictions clearly showed the applicability of various DSM products,with the prediction accuracy increasing from global to regional predictions.This simple evaluation can determine which products can be used at the local scale and if more accurate DSM products are required.

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.

SOME BEST APPROXIMATION RESULTS IN LOCALLY CONVEX SPACES

In this note we obtain generalization of well known results of carbone and Conti,Sehgal and Singh and Tanimoto concerning the existence of best approximation and simultaneous best approximation of continuous Junctions from the set up of a normed space to the case of a Hausdorff locally convex space.

基于Local-map的Mesh光网络简单p圈构造法

圈构造算法是Mesh光网络中p圈法设计的前提。根据简单p圈的特点,针对圈构造算法问题,提出将原来圈上边变为跨接边的圈扩展算法。该圈扩展算法构造的圈具有保护性能优良,并且包含所有原来的圈上的点。在圈扩展算法和Local-map概念的基础上提出了基于Local-map的p圈启发式算法,该算法在Local-map中运行圈扩展算法,这样既能提高p圈的保护性能,又能使p圈位于局域范围内,保证快速恢复。对比分析Local-map和DFS两种找圈算法的实验结果,该方案构造的圈恢复速度快,容量利用率高,比较适合网状光网络中的p圈设计。

多传感器融合的SLAM算法在林业智能化的应用与改进

同步定位与建图(SLAM)算法可实现机器人在未知环境下的定位,并对周围环境构建增量式地图,是机器人实现自主导航的基础。针对单一传感器(全球导航卫星系统(GNSS)、激光、相机等)的SLAM算法在林区环境存在定位精度低、构建的地图一致性较差的问题,提出了多传感器融合的SLAM算法在林业智能化的应用与改进。首先,联合使用激光雷达、单目相机、惯导对林区环境构建三维点云地图的同时对林业机器人进行实时定位;其次,提出以时间为约束的RS-T回环帧搜索法,进行候选回环帧搜索。结果表明:针对M2DGR数据集,RS-LVI-SAM算法与当前经典的SLAM算法对比,RS-LVI-SAM算法生成轨迹的均方根误差与标准差分别为0.09和0.04 m,定位精度最高;在林区场景中,RS-LVI-SAM算法建立的林区点云地图中侧柏的胸径与真实胸径的均方根误差与绝对平均误差分别为1.27、1.16 cm,建图效果最佳;生成的轨迹与真实轨迹的均方根误差与绝对平均误差分别为0.46、0.34 m,定位精度最高。因此,RS-LVI-SAM算法可以实现林区环境下的精准定位与林区点云地图构建,为机器人林区作业提供了技术支撑。

GNSS与SINS融合下的露天煤矿无人驾驶矿用卡车视觉惯性导航方法

无人驾驶矿用卡车在露天煤矿内工作时,依靠单一的捷联惯性导航系统(SINS)实现车辆惯性导航,长期推算导航过程中会发生信息累积,导致导航轨迹绝对位置误差较大。因此提出全球导航卫星系统(GNSS)与SINS融合的露天煤矿无人驾驶矿用卡车视觉惯性导航方法。获取露天煤矿场景动态视觉图像,依托于同时定位与地图构建(SLAM)算法建立车辆行驶动态环境地图,并运用基于3D距离误差的判断方法,筛选出动态特征点,标注出地图内动态区域,以此来定位无人驾驶矿用卡车实时位置。将GNSS和SINS融合起来,构建一种组合型视觉惯性导航模型,并引入卡尔曼滤波方程优化模型参数。最后,在循环神经网络的辅助下修正导航结果,生成高精度无人驾驶矿用卡车导航结果。实验结果表明,该方法形成的导航轨迹绝对位置误差不超过3 m,证明了其优越的导航性能。

Quantale系统的空间化和Q-Locale化

引入Quantale系统的概念,给出了Quantale系统的连续映射和同胚映射的定义,证明了同胚映射的逆仍为同胚映射.探讨Quantale系统的空间化和Q-Locale化,并在Quantale系统范畴和量子空间范畴之间建立伴随.证明了Quantale系统关于Quantale的Q-Locale是Quantale系统,Quantale系统的Q-Locale化是Q-Locale.建立了Quantale系统范畴和Q-Loc范畴之间的伴随.

Folded localized excitations in the (2+1)-dimensional modified dispersive water-wave system

By using a mapping approach and a linear variable separation approach, a new family of solitary wave solutions with arbitrary functions for the （2＋1）-dimensional modified dispersive water-wave system （MDWW） is derived. Based on the derived solutions and using some multi-valued functions, we obtain some novel folded localized excitations of the system.

Implementation and Evaluation of Local Dynamic Map in Safety Driving Systems

Cooperative safety driving systems using vehicle-to-vehicle and vehicle-to infrastructure communication are developed. Sensor data of vehicles and infrastructures are communicated in the cooperative safety driving system. LDM (Local Dynamic Map) is standardized by ETSI (European Telecommunications Standards Institute) to manage the vehicle sensor data and the map data. Implementations of LDM are reported on documents of ETSI, but there are no numerical results. The implementations of LDM are deployed the database management system. We think that the response time of the database becomes higher as the number of vehicles grows. In this paper, we have implemented and evaluated the LDM with the collision detection application.

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.

Mobile robot localization algorithm based on multi-sensor information fusion

In order to effectively reduce the uncertainty error of mobile robot localization with a single sensor and improve the accuracy and robustness of robot localization and mapping,a mobile robot localization algorithm based on multi-sensor information fusion(MSIF)was proposed.In this paper,simultaneous localization and mapping(SLAM)was realized on the basis of laser Rao-Blackwellized particle filter(RBPF)-SLAM algorithm and graph-based optimization theory was used to constrain and optimize the pose estimation results of Monte Carlo localization.The feature point extraction and quadrilateral closed loop matching algorithm based on oriented FAST and rotated BRIEF(ORB)were improved aiming at the problems of generous calculation and low tracking accuracy in visual information processing by means of the three-dimensional(3D)point feature in binocular visual reconstruction environment.Factor graph model was used for the information fusion under the maximum posterior probability criterion for laser RBPF-SLAM localization and binocular visual localization.The results of simulation and experiment indicate that localization accuracy of the above-mentioned method is higher than that of traditional RBPF-SLAM algorithm and general improved algorithms,and the effectiveness and usefulness of the proposed method are verified.

The Sequence-covering Compact Images of Paracompact Locally Compact Spaces

This paper gives internal characterizations of some sequence covering compact images and compact covering compact images of paracompact locally compact spaces, which improve some results on compact images of locally compact metric spaces.