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Massive MIMO-Based localization and mapping Exploiting Phase Information of Multipath Components

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2019年第9期18卷 4254-4267页

作者： Li, Xuhong Leitinger, Erik Oskarsson, Magnus Astrom, Kalle Tufvesson, Fredrik Lund Univ Dept Elect & Informat Technol SE-22100 Lund Sweden Graz Univ Technol Signal Proc & Speech Commun Lab A-8010 Graz Austria Lund Univ Ctr Math Sci SE-22100 Lund Sweden

In this paper, we present a robust multipath-based localization and mapping framework that exploits the phases of specular multipath components (MPCs) using a massive multiple-input multiple-output (MIMO) array at the base station. Utilizing the phase information related to the propagation distances of the MPCs enables the possibility of localization with extraordinary accuracy even with limited bandwidth. The specular MPC parameters along with the parameters of the noise and the dense multipath component (DMC) are tracked using an extended Kalman filter (EKF), which enables to preserve the distance-related phase changes of the MPC complex amplitudes. The DMC comprises all non-resolvable MPCs, which occur due to finite measurement aperture. The estimation of the DMC parameters enhances the estimation quality of the specular MPCs and, therefore, also the quality of localization and mapping. The estimated MPC propagation distances are subsequently used as input to a distance-based localization and mapping algorithm. This algorithm does not need prior knowledge about the surrounding environment and base station position. The performance is demonstrated with real radio-channel measurements using an antenna array with 128 ports at the base station side and a standard cellular signal bandwidth of 40MHz. The results show that the high accuracy localization is possible even with such a low bandwidth.

关键词： Parametric channel estimation extended Kalman filter massive MIMO radio channel localization and mapping

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Continuous localization and mapping of a pan-tilt-zoom camera for wide area tracking

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MACHINE VISION AND APPLICATIONS 2016年第7期27卷 1071-1085页

作者： Lisanti, Giuseppe Masi, Iacopo Pernici, Federico Del Bimbo, Alberto Univ Florence Media Integrat & Commun Ctr Viale Morgagni 65 I-50134 Florence Italy

Pan-tilt-zoom (PTZ) cameras are well suited for object identification and recognition in far-field scenes. However, the effective use of PTZ cameras is complicated by the fact that a continuous online camera calibration is needed and the absolute pan, tilt and zoom values provided by the camera actuators cannot be used because they are not synchronized with the video stream. So, accurate calibration must be directly extracted from the visual content of the frames. Moreover, the large and abrupt scale changes, the scene background changes due to the camera operation and the need of camera motion compensation make target tracking with these cameras extremely challenging. In this paper, we present a solution that provides continuous online calibration of PTZ cameras which is robust to rapid camera motion, changes of the environment due to varying illumination or moving objects. The approach also scales beyond thousands of scene landmarks extracted with the SURF keypoint detector. The method directly derives the relationship between the position of a target in the ground plane and the corresponding scale and position in the image and allows real-time tracking of multiple targets with high and stable degree of accuracy even at far distances and any zoom level.

关键词： Rotating and zooming camera PTZ sensor localization and mapping Multiple target tracking

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Agricultural robot dataset for plant classification, localization and mapping on sugar beet fields

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INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2017年第10期36卷 1045-1052页

作者： Chebrolu, Nived Lottes, Philipp Schaefer, Alexander Winterhalter, Wera Burgard, Wolfram Stachniss, Cyrill Univ Bonn Bonn Germany Univ Freiburg Freiburg Germany

There is an increasing interest in agricultural robotics and precision farming. In such domains, relevant datasets are often hard to obtain, as dedicated fields need to be maintained and the timing of the data collection is critical. In this paper, we present a large-scale agricultural robot dataset for plant classification as well as localization and mapping that covers the relevant growth stages of plants for robotic intervention and weed control. We used a readily available agricultural field robot to record the dataset on a sugar beet farm near Bonn in Germany over a period of three months in the spring of 2016. On average, we recorded data three times per week, starting at the emergence of the plants and stopping at the state when the field was no longer accessible to the machinery without damaging the crops. The robot carried a four-channel multi-spectral camera and an RGB-D sensor to capture detailed information about the plantation. Multiple lidar and global positioning system sensors as well as wheel encoders provided measurements relevant to localization, navigation, and mapping. All sensors had been calibrated before the data acquisition campaign. In addition to the data recorded by the robot, we provide lidar data of the field recorded using a terrestrial laser scanner. We believe this dataset will help researchers to develop autonomous systems operating in agricultural field environments

关键词： Agricultural robotics precision farming plant classification sugar beet localization and mapping

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Rail Vehicle localization and mapping With LiDAR-Vision-Inertial-GNSS Fusion

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IEEE ROBOTICS AND AUTOMATION LETTERS 2022年第4期7卷 9818-9825页

作者： Wang, Yusheng Song, Weiwei Lou, Yidong Zhang, Yi Huang, Fei Tu, Zhiyong Liang, Qiangsheng Wuhan Univ GNSS Res Ctr Wuhan 430079 Peoples R China Wuhan Univ Sch Geodesy & Geomat Wuhan 430079 Peoples R China Suzhou Jingwei CO LTD Suzhou 215163 Peoples R China

In this letter, we present a global navigation satellite system (GNSS) aided LiDAR-visual-inertial scheme, RailLoMer-V, for accurate and robust rail vehicle localization and mapping. RailLoMer-V is formulated atop a factor graph and consists of two subsystems: an odometer assisted LiDAR-inertial system (OLIS) and an odometer integrated Visual-inertial system (OVIS). Both the subsystem exploits the typical geometry structure on the railroads. The plane constraints from extracted rail tracks are used to complement the rotation and vertical errors in OLIS. Besides, the line features and vanishing points are leveraged to constrain rotation drifts in OVIS. The proposed framework is extensively evaluated on datasets over 800 km, gathered for more than a year on both general-speed and high-speed railways, day and night. Taking advantage of the tightly-coupled integration of all measurements from individual sensors, our framework is accurate to long-during tasks and robust enough to grievously degenerated scenarios (railway tunnels). In addition, the real-time performance can be achieved with an onboard computer.

关键词： Train multi-sensor localization and mapping

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localization and mapping by an Improved ICP Algorithm and a Feature-based Alignment Correction Algorithm

中正岭学报

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中正岭学报 2021年第2期50卷 13-34页

作者：楊顓豪

This study presented a real-time localization and mapping algorithm that integrates an improved iterative closest point (ICP) algorithm, a feature-based alignment correction algorithm, and a local minimum avoidance mechanism. It started with an investigation of the ICP algorithm. Such a point-based algorithm guarantees a local minimum for the process matching two scans (i.e., maps). However, the local minimum often has a large difference from the desired global minimum. Such an issue is often induced by outliers. A mechanism neglecting some high-leverage outliers was incorporated in every ICP iteration to resolve this issue. Although this process produces an acceptable result, the efficiency and accuracy issues must be addressed. A line-based representation for scans is able to reduce processing time and was therefore adopted in this study. Also, an alignment correction algorithm utilizing line features was proposed to reduce the error of alignment between two matched scans. The derived line-based process produces better results than the original one. Finally, the methods to avoid local minima were described. Although it may be resolved to some degree by neglecting a part of outliers, the process may still converge to a local minimum occasionally. Accordingly, a mechanism for avoiding local minima was integrated into the process to further cope with this issue. The feasibility of the presented algorithm was verified through various experiments.

关键词： localization and mapping ICP feature-based alignment correction scan matching

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Towards autonomous localization and mapping of AUVs: a survey

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INTERNATIONAL JOURNAL OF INTELLIGENT UNMANNED SYSTEMS 2013年第2期1卷 97-120页

作者： Chen, Ling Wang, Sen McDonald-Maier, Klaus Hu, Huosheng Univ Essex Sch Comp Sci & Elect Engn Colchester Essex England

Purpose - The main purpose of this paper is to investigate two key elements of localization and mapping of Autonomous Underwater Vehicle (AUV), i.e. to overview various sensors and algorithms used for underwater localization and mapping, and to make suggestions for future research. Design/methodology/approach - The authors first review various sensors and algorithms used for AUVs in the terms of basic working principle, characters, their advantages and disadvantages. The statistical analysis is carried out by studying 35 AUV platforms according to the application circumstances of sensors and algorithms. Findings - As real-world applications have different requirements and specifications, it is necessary to select the most appropriate one by balancing various factors such as accuracy, cost, size, etc. Although highly accurate localization and mapping in an underwater environment is very difficult, more and more accurate and robust navigation solutions will be achieved with the development of both sensors and algorithms. Research limitations/implications - This paper provides an overview of the state of art underwater localisation and mapping algorithms and systems. No experiments are conducted for verification. Practical implications - The paper will give readers a clear guideline to find suitable underwater localisation and mapping algorithms and systems for their practical applications in hand. Social implications - There is a wide range of audiences who will benefit from reading this comprehensive survey of autonomous localisation and mapping of UAVs. Originality/value - The paper will provide useful information and suggestions to research students, engineers and scientists who work in the field of autonomous underwater vehicles.

关键词： Autonomous Underwater Vehicle localization and mapping Sensors Algorithms SLAM Underwater technology

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A System Framework for localization and mapping Using High Resolution Cameras of Mobile Devices 17

A System Framework for Localization and Mapping Using High R...

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IEEE/CVF International Conference on Computer Vision (ICCV)

作者： Liu, Lifeng Li, Jian Futurewei Technol Inc 111 Speen St Framingham MA 01776 USA

ISBN: (纸本)9781728150239

We propose a hierarchical framework for processing high-resolution images on mobile devices for visual SLAM. It is based on the insights from analysis of new progress in primary features' detection, object detection and pose estimation. A rectification/unwarping operation is applied in regions of interest (ROIs) to improve the object/parts classification/detection performance;the object-part spatial relationships are created and contribute in map building, object detection, and localization;and a geometric constraints based pose refinement is followed to further improve the localization accuracy. Our design facilitates the more accurate pose estimating and localization using mobile devices for SLAM, and Augmented Reality/Mixed Reality applications.

关键词： Camera calibration Image unwarping localization and mapping Pose refinement

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Network Assistance to localization and mapping for Outdoor Augmented Reality in Cellular Network 3

Network Assistance to Localization and Mapping for Outdoor A...

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3rd International Conference on Platform Technology and Service (PlatCon)

作者： Bang, Junseong Lee, Dongchun Lee, Hunjoo Son, Wookho ETRI Content Platform Res Dept 218m Gajeong Ro Daejeon 34129 South Korea

ISBN: (纸本)9781467386852

A mobile device performs localization and mapping processes for an augmented reality (AR) application. In an outdoor environment, the mobile device requires more computing power to compute a camera's location and pose in real-time, to construct a 3D point cloud, and to render virtual images. However, the resources (e.g., processor, memory) of the mobile device are limited. With advances in cloud computing and 4G wireless network technologies that provide a 100 Mbits/s transmission rate with guaranteeing the latency of 40 ms, network assistances can be considered to avoid complex computations at the mobile device. In this paper, network assisted methods to the localization and mapping processes are introduced in a cellular network environment.

关键词： augmented reality outdoor network assistance localization and mapping cellular network

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Vision-Based Simultaneous localization and mapping on Lunar Rover 3

Vision-Based Simultaneous Localization and Mapping on Lunar ...

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3rd IEEE International Conference on Image, Vision and Computing (ICIVC)

作者： An, Pei Liu, Yanchao Zhang, Wei Jin, Zhaojun Univ Chinese Acad Sci 19 A Yuquan Rd Beijing 100049 Peoples R China Chinese Acad Sci Technol & Engn Ctr Space Utilizat Key Lab Space Utilizat 9 Deng Zhuang South Rd Beijing 100094 Peoples R China Chinese Acad Sci Inst Elect 19 North 4th Ring Rd West Beijing 100190 Peoples R China

ISBN: (纸本)9781538649916

With the development of lunar exploration technology, vision-based localization and navigation technology has become a research focus in the field of lunar rover. This paper proposes an image-based method for localization and mapping with a lunar rover. The motion of the camera represents the movement of the lunar rover. Based on the images acquired by the camera, the relative pose of the camera and 3D landmarks are obtained using the multi-view geometry and the bundle adjustment optimization methods. The prior knowledge of the lunar rover movement is not required. In addition, this paper also proposes a grid-based feature extraction method to solve the problem of uneven feature extraction and mis-matching. The algorithm in this paper has been tested in real time in a large image dataset. Finally, the error analysis of the estimated pose obtained from the experiment and the real trajectory proves the excellent performance of the algorithm.

关键词： localization and mapping lunar exploration feature extraction pose estimation lunar rover

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Underwater localization and Environment mapping Using Wireless Robots

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WIRELESS PERSONAL COMMUNICATIONS 2013年第3期70卷 1147-1170页

作者： Wang, Sen Chen, Ling Hu, Huosheng Xue, Zhibin Pan, Wei Univ Essex Sch Comp Sci & Elect Engn Colchester CO4 3SQ Essex England Qinghai Univ Coll Chem Engn Xining Peoples R China Xiamen Univ Coll Informat Sci & Technol Xiamen Peoples R China

localization and mapping are the fundamental ability for underwater robots to carry out exploration and searching tasks autonomously. This paper presents a novel approach to localization and mapping of a school of wirelessly connected underwater robotic fish (URF). It is based on both Cooperative localization Particle Filter (CLPF) scheme and Occupancy Grid mapping Algorithm (OGMA). Using the probabilistic framework, the proposed CLPF has the major advantage that no prior knowledge about the kinematic model of URF is required to achieve accurate 3D localization. It works well when the number of mobile beacons is less than four, which is the minimum number for some traditional localization algorithms. The localization result of CLPF is fed into OGMA to build the environment map. The performance of the proposed algorithms is evaluated through extensive simulation experiments, and results verify the feasibility and effectiveness of the proposed strategy.

关键词： Wireless robots Robotic fish Particle filter localization and mapping Wireless sensor networks

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