Path estimation of a shopping cart using a particle filter and an environment map

Daiki Sasakura, Keigo Watanabe, Isaku Nagai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Understanding of consumer behavior contributes a store for improving the profitability. It is important to analyze and understand consumer trajectories in a store building for the purpose. Therefore analyses of purchasing history and consumer's movement are performed in the process. Purchasing histories is regularly obtained via a POS system. For acquiring the movement path, a measurement device using an optical sensor and a gyro sensor was proposed. However, the device has a problem of poor measurement accuracy because of the accumulated error in the sensors. In this study, we propose a method for improving the accuracy by using a particle filter and an environmental map. We describe the outline of the device and the path estimated by the method from the measured data with a map.

Original languageEnglish
Title of host publicationProceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society
PublisherIEEE Computer Society
Pages6152-6157
Number of pages6
ISBN (Electronic)9781509034741
DOIs
Publication statusPublished - Dec 21 2016
Event42nd Conference of the Industrial Electronics Society, IECON 2016 - Florence, Italy
Duration: Oct 24 2016Oct 27 2016

Publication series

NameIECON Proceedings (Industrial Electronics Conference)

Other

Other42nd Conference of the Industrial Electronics Society, IECON 2016
CountryItaly
CityFlorence
Period10/24/1610/27/16

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Sasakura, D., Watanabe, K., & Nagai, I. (2016). Path estimation of a shopping cart using a particle filter and an environment map. In Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society (pp. 6152-6157). [7793480] (IECON Proceedings (Industrial Electronics Conference)). IEEE Computer Society. https://doi.org/10.1109/IECON.2016.7793480