Minimum hardware SfM/SLAM for sparse data point mapping of retail stores
(2016) In Master's Theses in Mathematical Sciences FMA820 20161Mathematics (Faculty of Engineering)
- Abstract
- This report aims to compare methods that can be used to efficiently and accurately map digital price labels position in 3D space using a mobile robotic platform equipped with camera vision in a retail environment. The robotic platform built during the project uses four wide angle cameras to cover the full circular view in the horizontal plane. Installation of external systems for e.g. navigation can be very costly and time demanding. The accuracy, repeatability and time consumption have been evaluated for a set of methods and combinations thereof with and without external hardware. The result of the tests shows a proof-of-concept with good results but also emphasizes the need for a robust system. The mapping is done with high accuracy even... (More)
- This report aims to compare methods that can be used to efficiently and accurately map digital price labels position in 3D space using a mobile robotic platform equipped with camera vision in a retail environment. The robotic platform built during the project uses four wide angle cameras to cover the full circular view in the horizontal plane. Installation of external systems for e.g. navigation can be very costly and time demanding. The accuracy, repeatability and time consumption have been evaluated for a set of methods and combinations thereof with and without external hardware. The result of the tests shows a proof-of-concept with good results but also emphasizes the need for a robust system. The mapping is done with high accuracy even when the external hardware for navigation is completely removed. As a part of the project a novel line following algorithm has been developed which shows results far better than any published results found and yet capable of running in real time utilizing limited hardware. (Less)
- Popular Abstract (Swedish)
- Vi har konstruerat en liten robot på hjul som kan köra runt i matbutiker och kartlägga positionen av prislappar. Roboten använder sig av kameror för att triangulera fram en 3D position för prislapparna som den har sett från flera vinklar. Roboten skapar automatiskt en karta över sin omgivning genom att optimera sin egen och omgivningens position för att minimera skillnaden mellan den matematiskt förväntade bilden och den bild som kamerorna
faktiskt har sett. En nytänkande algoritm för linjeföljning med kamera har också utvecklats och publicerats i en akademisk journal.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8890475
- author
- Falk, Daniel LU
- supervisor
-
- Håkan Ardö LU
- organization
- alternative title
- En utvärdering av SfM/SLAM för kartläggning av lågdensitets punktmoln i detaljhandel
- course
- FMA820 20161
- year
- 2016
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- structure from motion, simultaneous localization and mapping, generalized imaging device, camera pose estimation, sparse data, point clouds, path planning, artificial intelligence, intelligent agent, line following, navigation, computer vision, cognitive science, stroke width transform
- publication/series
- Master's Theses in Mathematical Sciences
- report number
- LUTFMA-3303-2016
- ISSN
- 1404-6342
- other publication id
- 2016:E43
- language
- English
- id
- 8890475
- date added to LUP
- 2016-11-16 10:53:04
- date last changed
- 2016-11-16 10:53:04
@misc{8890475, abstract = {{This report aims to compare methods that can be used to efficiently and accurately map digital price labels position in 3D space using a mobile robotic platform equipped with camera vision in a retail environment. The robotic platform built during the project uses four wide angle cameras to cover the full circular view in the horizontal plane. Installation of external systems for e.g. navigation can be very costly and time demanding. The accuracy, repeatability and time consumption have been evaluated for a set of methods and combinations thereof with and without external hardware. The result of the tests shows a proof-of-concept with good results but also emphasizes the need for a robust system. The mapping is done with high accuracy even when the external hardware for navigation is completely removed. As a part of the project a novel line following algorithm has been developed which shows results far better than any published results found and yet capable of running in real time utilizing limited hardware.}}, author = {{Falk, Daniel}}, issn = {{1404-6342}}, language = {{eng}}, note = {{Student Paper}}, series = {{Master's Theses in Mathematical Sciences}}, title = {{Minimum hardware SfM/SLAM for sparse data point mapping of retail stores}}, year = {{2016}}, }