Map generation using a smartphone’s built in localisation and mapping algorithms
(2023) In Master's Theses in Mathematical Sciences FMAM05 20222Mathematics (Faculty of Engineering)
- Abstract
- Localisation and mapping algorithms for smartphones have in recent years seen a renewed interest due to their technological advancements. Using these systems to generate an indoor blueprint where none is available or incomplete is useful in tracking applications. This report examines the possibilities of adapting ARcore as a tool for map generation of unknown areas. Several tests of indoor environments were performed in office and university environments, recording pose track and environment data. This study finds it feasible to perform a combined pose tracking and indoor mapping, capturing the overall shape of a surveyed area with some distortions and drift in the resulting map.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9111187
- author
- Harvig, Emil LU
- supervisor
- organization
- alternative title
- Kartläggning av inomhusmiljöer med hjälp av en mobiltelefons inbyggda system för lokalisering och kartläggning
- course
- FMAM05 20222
- year
- 2023
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Point Cloud, SLAM, vSLAM, Pose, Occupancy Grid Map, OGM, ARcore
- publication/series
- Master's Theses in Mathematical Sciences
- report number
- LUTFMA-3495-2023
- ISSN
- 1404-6342
- other publication id
- 2023:E4
- language
- English
- id
- 9111187
- date added to LUP
- 2023-05-10 16:19:54
- date last changed
- 2023-05-10 16:19:54
@misc{9111187, abstract = {{Localisation and mapping algorithms for smartphones have in recent years seen a renewed interest due to their technological advancements. Using these systems to generate an indoor blueprint where none is available or incomplete is useful in tracking applications. This report examines the possibilities of adapting ARcore as a tool for map generation of unknown areas. Several tests of indoor environments were performed in office and university environments, recording pose track and environment data. This study finds it feasible to perform a combined pose tracking and indoor mapping, capturing the overall shape of a surveyed area with some distortions and drift in the resulting map.}}, author = {{Harvig, Emil}}, issn = {{1404-6342}}, language = {{eng}}, note = {{Student Paper}}, series = {{Master's Theses in Mathematical Sciences}}, title = {{Map generation using a smartphone’s built in localisation and mapping algorithms}}, year = {{2023}}, }