MOIN (Minimum Location Infrastructure)

Duration: 01.09.2018 - 31.12.2020
Project Leader:
Prof. Dr.-Ing Horst Hellbrück
Staff: Sven Ole Schmidt

Background

A producer stores his semi-finished and pre-products in a hall with numerous narrow aisles in between. Inside the production hall, there are also completely enclosed rooms (sanding, welding and painting booths). From semi-finished and pre-products, the final product is manufactured in several operations. In addition to retrieving the semi-finished and precursors, the entire production process should be automatically monitored, e.g. Determine buffer times. In order to perform an automatic tracking of the production process, the position of the semi-finished and pre-products, as well as the production order, must be retrievable at any time.
With traditional methods, such as barcode or passive RFID, complete tracking is only possible to a limited extent. In addition, these methods cause considerable manual overhead (permanent simultaneous scanning of object and position) and pose a high potential for errors by forgetting a scan. The object can no longer be located in this case.
Existing positioning systems based on radio runtime measurement require a large number of reference points. Due to the hall topology described, the corresponding infrastructure for radiolocation would have to be set up in each individual aisle in this case. A location within the enclosed spaces would be limited or not possible by shielding.

Objective

The result of this project is the development of a minimalist location system. In contrast to established location systems, the required infrastructure (reference points, server and processing hardware) is reduced to a minimum. For the design and application of the location system, a simulation and planning tool is developed.

The subproject Modeling and Algorithms (Modal) of the University of Applied Sciences Lübeck develops solutions for the algorithmic part of the location system.

Project Partners

 

Solcon

Gefördert durch:                    

Förderkennzeichen: ZF4186108BZ8

files/mflo/zim_4c_klein.jpg

 

Veröffentlichungen


Refereed Conference Papers
[2019] On the Effective Length of Channel Impulse Responses in UWB Single Anchor Localization (Sven Ole Schmidt, Marco Cimdins, Horst Hellbrück), In International Conference on Localization and GNSS, 2019. [bib] [abstract]
Recently, single anchor localization evolves as a new research topic that exploits multipath propagation for calculation of tag positions. With a combination of movement information and particle filters, they provide a precision that is similar to multi-anchor systems. However, a systematic approach to the design and implementation of such systems is not yet available. The combination of theory and mathematical modeling for channel impulse responses is still an open research question that we address in this paper. Therefore, we propose a new representation of a channel impulse response targeted for single anchor localization systems. Based on this representation, we model the relationship between tag positions and channel impulse responses and evaluate the statistic properties of channel impulse responses in this application. In this paper, we introduce a new metric for the assessment of anchor positions, the effective length of CIRs. By the shortest effective length of a set of CIRs, we identify the best anchor position, since it indicates the position where requirements for the measurement of the channel impulse response are lowest.
Other Publications
[2019] Improvements to UWB Channel Impulse Response Measurements for Indoor Localization (B. Mattthews, M. Cimdins, H. Hellbrück), (T. M. Buzug et. al., ed.), 2019. [bib] [abstract]
This paper proposes two methods to improve the accuracy of UWB channel impulse response (CIR) measurements. Improving the accuracy of UWB CIR measurements results in an improvement of the overall accuracy of an indoor localization system. Two methods are analyzed, both with the idea of combining a series of CIR measurements to yield higher accuracy than a single measurement. We evaluated both methods by gathering data at different positions within a room. These methods reduced the error by an average of 7% and 4% respectively. The results indicate that utilizing these techniques will improve the accuracy of localization.
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