Smartphone-based indoor localization systems are increasingly needed in various types of applications. This article proposes a novel WiFi and vision-integrated fingerprint (Wi-Vi fingerprint) for accurate robust localization. The method consists two steps mapping In the step, Wi-Vi fingerprints all sampling sites computed by using EXIT signs as landmarks. multiscale strategy is proposed, which includes coarse from weighted access points (WAPs)-based matching, Gaussian KNN (GW-KNN)-based...

Automatic Guided Vehicles (AGVs) are crucial for improving the operational efficiency of industrial scenes, however self-localization AGVs faces severe challenges in a dynamic environment due to large number observation noises. To address above issue, this paper presents trusted area information based method achieve efficient and accurate localization highly scene, where proportion obstacles is close 50%. First all, "coarse-noise filter-fine" framework proposed establish foundation...

3D LiDAR maps are playing a more and important role in intelligent vehicle localization. In this paper, the proposed SeqPolar localization method consists of two parts. The first part is novel node-based map representation method, termed polarized (PLM), second matching algorithm based on second-order hidden Markov model (HMM2) for Unlike existing map, which usually constructed by accumulating clouds collected at different times, generated from set nodes. Each node three elements: image,...

Diamond nanorods are one-dimensional carbon nanostructures consisting of all sp3 bonded atoms. They represent an alternative class structure to fullerene nanotubes for potential applications in nanocomposites mechanical reinforcement and thermal management, as well microelectronics. Synthetic routes creating diamond (and related structures) recent predictions their stability, mechanical, properties summarized the article.

Accurate localization is a crucial step for intelligent vehicles (IVs). And vision-based methods are promising due to its good accuracy and low cost. However, usually not robust enough the errors of matching similar road scenarios. In this paper, we proposed visual map-based method, called multi-view site (MVSM). We using two camera views (i.e., downward-view front-view) construct map. The map consists serial nodes. Each node encodes features road, 2D structure, poses vehicle. Based on...

Safety and comfortability are important indicators to evaluate the performance of driver assistant systems (ADAS) intelligent vehicle (IV) systems. Driver identification or driving characteristic learning is needed achieve function for ADAS IV The effectiveness directly affected by representation method. This paper develops a new concept fingerprint map represent characteristics. First, scenes classified using ensemble Then, feature selection method known as conditional mutual information...

Matching high definition (HD) map and real-time sensor data, which is crucial for map-based intelligent vehicle localization, usually requires robust distinct road features extracted from both ends. However, extacted data (e.g., image, LiDAR) are susceptible to various conditions, such as lighting, weather dynamic objects, etc. Moreover, although lane lines can provide continuous lateral constraints on a vehicle's position, it still challenging get sufficient longitudinal ones due the...

Matching with a semantic map can feed accurate prior information into perception and localization modules in the intelligent vehicle system. This article proposes simultaneous matching, localization, detection (SMLAD) method from LiDAR for vehicles, which integrates separated steps of maximum posteriori probability (MAP) inference problem particle filter framework. Firstly, objects, such as cubes, poles, walls, ground, are extracted query point cloud by segmentation method. Then likelihood...

Robust and reliable localization is important for intelligent vehicles, especially in GPS-blind areas, such as underground parking lots. A novel frame by building two-layer visual maps from two-camera views (i.e., front side views) proposed this paper. Among these two views, we build the dense map layer extracting handcraft features front-view to achieve accurate localization. We sparse both holistic local semantic with a Siamese Network side-view improve reliability. These types of layers...

Summary In frequency-space domain, mixed-grid finite-difference (FD) schemes are widely used and effectively improve the forward modeling accuracy,but in time FD methods use high-order general or rotated rectangular coordinate system. this article, by introducing from domain to time-space we propose a new kind of Mixed-grid 2M+ N(MG2M+N) methods, where M N respectively represent number Laplacian operators system, derive method calculate coefficients based on dispersion relationship. Then...

High-precision localization is one of the most critical components unmanned surface vehicle (USV). However, accuracy and robustness traditional GPS-based methods in complex berthing departing scenarios are still limited. This paper proposes a novel method USV based on LiDAR semantic geometric information scene, which integrates such as shoreline, ships, buildings into SLAM system to enhance perception ability USV. First, CNN-based scene using presented, make get from port accurately. And...