1,866 research outputs found

    A Survey of Positioning Systems Using Visible LED Lights

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    © 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

    Living IoT: A Flying Wireless Platform on Live Insects

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    Sensor networks with devices capable of moving could enable applications ranging from precision irrigation to environmental sensing. Using mechanical drones to move sensors, however, severely limits operation time since flight time is limited by the energy density of current battery technology. We explore an alternative, biology-based solution: integrate sensing, computing and communication functionalities onto live flying insects to create a mobile IoT platform. Such an approach takes advantage of these tiny, highly efficient biological insects which are ubiquitous in many outdoor ecosystems, to essentially provide mobility for free. Doing so however requires addressing key technical challenges of power, size, weight and self-localization in order for the insects to perform location-dependent sensing operations as they carry our IoT payload through the environment. We develop and deploy our platform on bumblebees which includes backscatter communication, low-power self-localization hardware, sensors, and a power source. We show that our platform is capable of sensing, backscattering data at 1 kbps when the insects are back at the hive, and localizing itself up to distances of 80 m from the access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang, In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201

    A practical multirobot localization system

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    We present a fast and precise vision-based software intended for multiple robot localization. The core component of the software is a novel and efficient algorithm for black and white pattern detection. The method is robust to variable lighting conditions, achieves sub-pixel precision and its computational complexity is independent of the processed image size. With off-the-shelf computational equipment and low-cost cameras, the core algorithm is able to process hundreds of images per second while tracking hundreds of objects with a millimeter precision. In addition, we present the method's mathematical model, which allows to estimate the expected localization precision, area of coverage, and processing speed from the camera's intrinsic parameters and hardware's processing capacity. The correctness of the presented model and performance of the algorithm in real-world conditions is verified in several experiments. Apart from the method description, we also make its source code public at \emph{http://purl.org/robotics/whycon}; so, it can be used as an enabling technology for various mobile robotic problems

    Self-sustaining Ultra-wideband Positioning System for Event-driven Indoor Localization

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    Smart and unobtrusive mobile sensor nodes that accurately track their own position have the potential to augment data collection with location-based functions. To attain this vision of unobtrusiveness, the sensor nodes must have a compact form factor and operate over long periods without battery recharging or replacement. This paper presents a self-sustaining and accurate ultra-wideband-based indoor location system with conservative infrastructure overhead. An event-driven sensing approach allows for balancing the limited energy harvested in indoor conditions with the power consumption of ultra-wideband transceivers. The presented tag-centralized concept, which combines heterogeneous system design with embedded processing, minimizes idle consumption without sacrificing functionality. Despite modest infrastructure requirements, high localization accuracy is achieved with error-correcting double-sided two-way ranging and embedded optimal multilateration. Experimental results demonstrate the benefits of the proposed system: the node achieves a quiescent current of 47 nA47~nA and operates at 1.2 μA1.2~\mu A while performing energy harvesting and motion detection. The energy consumption for position updates, with an accuracy of 40 cm40~cm (2D) in realistic non-line-of-sight conditions, is 10.84 mJ10.84~mJ. In an asset tracking case study within a 200 m2200~m^2 multi-room office space, the achieved accuracy level allows for identifying 36 different desk and storage locations with an accuracy of over 95 %95~{\%}. The system`s long-time self-sustainability has been analyzed over 700 days700~days in multiple indoor lighting situations

    Mapeamento 3D com sistemas LiDAR e GNSS

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    The project begun by collecting all the information connected with geodesy, map projections and Global Navigation Systems. In the same time theoretical part covers also manuals and specification of further used tools like FARO Laser an GNSS Receiver. After get to know about theoretical part the next step was to work with outdoor devices. Before do all surveys it has to be known all rules connected with health and safety. Then it has to be done leveling of the FARO Lasers holder. Afterwards on the top it was put GNSS Receiver. It was working for a few minutes to collect as much information as necessary to know the position. Next step was to start the scanning of laser and do the photos. The same was done with the second position on the campus. When the outdoor work was done all parts had been taken to a magazine for further users. After the outdoor work the time comes to desk work. Before this task it has to be known computer programs that will be used in the project. To do a post-processing it was chosen the RTKLIB program. For the map projecting the best option was CloudCompare. With help from manuals and tutorials the work on a map can go ahead. At least after all tasks the final map was ready for the further use
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