22,864 research outputs found
A Survey of Positioning Systems Using Visible LED Lights
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe
An Implementation Approach and Performance Analysis of Image Sensor Based Multilateral Indoor Localization and Navigation System
Optical camera communication (OCC) exhibits considerable importance nowadays
in various indoor camera based services such as smart home and robot-based
automation. An android smart phone camera that is mounted on a mobile robot
(MR) offers a uniform communication distance when the camera remains at the
same level that can reduce the communication error rate. Indoor mobile robot
navigation (MRN) is considered to be a promising OCC application in which the
white light emitting diodes (LEDs) and an MR camera are used as transmitters
and receiver respectively. Positioning is a key issue in MRN systems in terms
of accuracy, data rate, and distance. We propose an indoor navigation and
positioning combined algorithm and further evaluate its performance. An android
application is developed to support data acquisition from multiple simultaneous
transmitter links. Experimentally, we received data from four links which are
required to ensure a higher positioning accuracy
EVEREST IST - 2002 - 00185 : D23 : final report
Deliverable pĂşblic del projecte europeu EVERESTThis deliverable constitutes the final report of the project IST-2002-001858 EVEREST. After its successful completion, the project presents this document that firstly summarizes the context, goal and the approach objective of the project. Then it presents a concise summary of the major goals and results, as well as highlights the most valuable lessons derived form the project work. A list of deliverables and publications is included in the annex.Postprint (published version
Exploiting 2D Floorplan for Building-scale Panorama RGBD Alignment
This paper presents a novel algorithm that utilizes a 2D floorplan to align
panorama RGBD scans. While effective panorama RGBD alignment techniques exist,
such a system requires extremely dense RGBD image sampling. Our approach can
significantly reduce the number of necessary scans with the aid of a floorplan
image. We formulate a novel Markov Random Field inference problem as a scan
placement over the floorplan, as opposed to the conventional scan-to-scan
alignment. The technical contributions lie in multi-modal image correspondence
cues (between scans and schematic floorplan) as well as a novel coverage
potential avoiding an inherent stacking bias. The proposed approach has been
evaluated on five challenging large indoor spaces. To the best of our
knowledge, we present the first effective system that utilizes a 2D floorplan
image for building-scale 3D pointcloud alignment. The source code and the data
will be shared with the community to further enhance indoor mapping research
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