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A framework for vision based bearing only 3D SLAM
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. (CVAP/CAS/CSC)ORCID iD: 0000-0002-1170-7162
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-2965-2953
KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. (CAS/CVAP/CSC)ORCID iD: 0000-0002-7796-1438
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.ORCID iD: 0000-0003-0579-3372
2006 (English)In: Proceedings of the 2006 IEEE International Conference on Robotics and Automation, Orlando, Florida - May 2006: Vols 1-10, IEEE , 2006, 1944-1950 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a framework for 3D vision based bearing only SLAM using a single camera, an interesting setup for many real applications due to its low cost. The focus in is on the management of the features to achieve real-time performance in extraction, matching and loop detection. For matching image features to map landmarks a modified, rotationally variant SIFT descriptor is used in combination with a Harris-Laplace detector. To reduce the complexity in the map estimation while maintaining matching performance only a few, high quality, image features are used for map landmarks. The rest of the features are used for matching. The framework has been combined with an EKF implementation for SLAM. Experiments performed in indoor environments are presented. These experiments demonstrate the validity and effectiveness of the approach. In particular they show how the robot is able to successfully match current image features to the map when revisiting an area.

Place, publisher, year, edition, pages
IEEE , 2006. 1944-1950 p.
Series
IEEE International Conference on Robotics and Automation, ISSN 1050-4729
Keyword [en]
Cameras, Computer vision, Costs, Detectors, Indoor environments, Mobile robots, Robot sensing systems, Robustness, Sensor systems, Simultaneous localization and mapping
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-38226DOI: 10.1109/ROBOT.2006.1641990ISI: 000240886904023Scopus ID: 2-s2.0-33845636578ISBN: 0-7803-9505-0 (print)OAI: oai:DiVA.org:kth-38226DiVA: diva2:436289
Conference
IEEE International Conference on Robotics and Automation (ICRA) Location: Orlando, FL Date: MAY 15-19, 2006
Note
© 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20111124Available from: 2011-11-24 Created: 2011-08-23 Last updated: 2012-01-24Bibliographically approved

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