Collaborative Merging of Radio SLAM Maps in View of Crowd-sourced Data Acquisition and Big Data

Kenneth Batstone, Magnus Oskarsson, Kalle Åstrom

Abstract

Indoor localization and navigation is a much researched and difficult problem. The best solutions, usually use expensive specialized equipment and/or prior calibration of some form. To the average person with smart or Internet-Of-Things devices, these solutions are not feasible, particularly in large scales. With hardware advancements making Ultra-Wideband devices more accurate and low powered, this unlocks the potential of having such devices in commonplace around factories and homes, enabling an alternative method of navigation. Therefore, indoor anchor calibration becomes a key problem in order to implement these devices efficiently and effectively. In this paper, we present a method to fuse radio SLAM (also known as Time-Of- Arrival self-calibration) maps together in a linear way. In doing so we are then able to collaboratively calibrate the anchor positions in 3D to native precision of the devices. Furthermore, we introduce an automatic scheme to determine which of the maps are best to use to further improve the anchor calibration and its robustness but also show which maps could be discarded. Additionally, when a map is fused in a linear way, it is a very computationally cheap process and produces a reasonable map which is required to push for crowd-sourced data acquisition.

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Paper Citation


in Harvard Style

Batstone K., Oskarsson M. and Åstrom K. (2019). Collaborative Merging of Radio SLAM Maps in View of Crowd-sourced Data Acquisition and Big Data.In Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-351-3, pages 807-813. DOI: 10.5220/0007574408070813


in Bibtex Style

@conference{icpram19,
author={Kenneth Batstone and Magnus Oskarsson and Kalle Åstrom},
title={Collaborative Merging of Radio SLAM Maps in View of Crowd-sourced Data Acquisition and Big Data},
booktitle={Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2019},
pages={807-813},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007574408070813},
isbn={978-989-758-351-3},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Collaborative Merging of Radio SLAM Maps in View of Crowd-sourced Data Acquisition and Big Data
SN - 978-989-758-351-3
AU - Batstone K.
AU - Oskarsson M.
AU - Åstrom K.
PY - 2019
SP - 807
EP - 813
DO - 10.5220/0007574408070813