Computer Vision without Vision: Methods and Applications of Radio and Audio Based SLAM

Research output: ThesisDoctoral Thesis (compilation)

195 Downloads (Pure)

Abstract

The central problem of this thesis is estimating receiver-sender node positions from measured receiver-sender distances or equivalent measurements. This problem arises in many applications such as microphone array calibration, radio antenna array calibration, mapping and positioning using ultra-wideband and mapping and positioning using round-trip-time measurements between mobile phones and Wi-Fi-units. Previous research has explored some of these problems, creating minimal solvers for instance, but these solutions lack real world implementation. Due to the nature of using different media, finding reliable receiver-sender distances is tough, with many of the measurements being erroneous or to a worse extent missing. Therefore in this thesis, we explore using minimal solvers to create robust solutions, that encompass small erroneous measurements and work around missing and grossly erroneous measurements.

This thesis focuses mainly on Time-of-Arrival measurements using radio technologies such as Two-way-Ranging in Ultra-Wideband and a new IEEE standard 802.11mc found on many WiFi modules. The methods investigated, also related to Computer Vision problems such as Stucture-from-Motion. As part of this thesis, a range of new commercial radio technologies are characterised in terms of ranging in real world enviroments. In doing so, we have shown how these technologies can be used as a more accurate alternative to the Global Positioning System in indoor enviroments. Further to these solutions, more methods are proposed for large scale problems when multiple users will collect the data, commonly known as Big Data. For these cases, more data is not always better, so a method is proposed to try find the relevant data to calibrate large systems.
Original languageEnglish
QualificationDoctor
Awarding Institution
  • Mathematics (Faculty of Engineering)
Supervisors/Advisors
  • Åström, Kalle, Supervisor
  • Oskarsson, Magnus, Supervisor
  • Tufvesson, Fredrik, Supervisor
  • Bernhardsson, Bo, Supervisor
Thesis sponsors
Award date2020 Oct 2
Publisher
ISBN (Print)9789178956203
ISBN (electronic) 9789178956210
Publication statusPublished - 2020 Sep 8

Bibliographical note

Defence details
Date: 2020-10-02
Time: 13:15
Place: Lecture hall MH:Gårding, Matematicum, Sölvegatan 18, Faculty of Engineering LTH, Lund University, Lund
External reviewer(s)
Name: Kuusniemi, Heidi
Title: Prof.
Affiliation: University of Vaasa, Finland.
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Subject classification (UKÄ)

  • Computer Vision and Robotics (Autonomous Systems)

Keywords

  • TOA
  • Self-Calibration
  • Localization
  • 802.11mc
  • Round-Trip Time

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