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


From: 2020-10-02 13:15 to 16:00
Contact: kalle [at] maths [dot] lth [dot] se
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Kenneth Batstone försvarar sin avhandling "Computer Vision without Vision - Methods and Applications of Radio and Audio Based SLAM" Fredagen den 2 oktober 2020, kl 13:15 på zoom och i lokal MH:Gårding

Kenneth Batstone defends his thesis "Computer Vision without Vision - Methods and Applications of Radio and Audio Based SLAM"

Friday 2 October 2020, at 13:15 on zoom
and for a restricted audience

(Contact kalle [at] maths [dot] lth [dot] se if you would like to participate in MH:Gårding)

Fakultetsopponent/Faculty opponent:
Professor Heidi Kuusniemi, University of Vaasa, Finland

Ledamöter i betygsnämnden/Examination Board:
Ledamot 1: Docent Gustaf Hendeby, Linköpings universitet, Linköping
Ledamot 2: Docent Isaac Skog, Linköpings universitet, Linköping
Ledamot 3: Professor Hedvig Kjellström, KTH, Stockholm
Suppleant 1: Docent Pontus Giselsson, Lunds Tekniska högskola LTH, Lunds universitet, Lund
Suppleant 2: Docent Sara Maad Sasane, Lunds Tekniska högskola LTH, Lunds universitet, Lund

Ordförande att leda disputationen/Chairman: Docent Mikael Nilsson, Lunds Tekniska högskola LTH, Lunds universitet, Lund


The central problem of this thesis is estimating receiver­-sender node positions from measured receiver­-sender distances. This problem arrises 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 Wi­Fi-­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 receiver­sender distances is tough, with many of the measurements being erroneous or to a worse extend missing. Therefore in this thesis, we explore using minimal solvers to create robust solutions, that encompass small erroneous measurements and works 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. Although the methods investigated, also related to Computer Vision problems such as Structure for Motion.
As part of this thesis, a range of new commercial radio technologies are characterised in terms of ranging in real world environments. In doing so, we have shown how these technologies can be used as a more accurate alternative to the Global Positioning System in indoor environments. 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.

Med vänliga hälsningar,

Kalle Åström, Magnus Oskarsson, supervisors, Matematikcentrum
Bo Bernhardsson, supervisor, Reglerteknik
Fredrik Tufvesson, supervisor, Elektro och Informationsteknik