6D SLAM with approximate data association
Autor(en): | Nüchter, A. Lingemann, K. Hertzberg, J. Surmann, H. |
Stichwörter: | Algorithms; Degrees of freedom (mechanics); Mobile robots; Problem solving; Three dimensional; Trees (mathematics), Box decomposition trees; Iterative Closest Points (ICP); kd-trees; Simultaneous localization and mapping (SLAM), Robotics | Erscheinungsdatum: | 2005 | Journal: | 2005 International Conference on Advanced Robotics, ICAR '05, Proceedings | Volumen: | 2005 | Startseite: | 242 | Seitenende: | 249 | Zusammenfassung: | This paper provides a new solution to the simultaneous localization and mapping (SLAM) problem with six degrees of freedom. A fast variant of the Iterative Closest Points (ICP) algorithm registers 3D scans taken by a mobile robot into a common coordinate system and thus provides relocalization. Hereby, data association is reduced to the problem of searching for closest points. Approximation algorithms for this searching, namely, approximate kd-trees and box decomposition trees, are presented and evaluated in this paper. A solution to 6D SLAM that considers all free parameters in the robot pose is built based on 3D scan matching. © 2005 IEEE. |
Beschreibung: | Conference of 12th International Conference on Advanced Robotics, 2005. ICAR '05 ; Conference Date: 18 July 2005 Through 20 July 2005; Conference Code:67859 |
ISBN: | 9780780391772 | DOI: | 10.1109/ICAR.2005.1507419 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-33749047027&doi=10.1109%2fICAR.2005.1507419&partnerID=40&md5=d06b1772c3ad7aeac3efdda45497fa6e |
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