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A Stochastically Stable Solution to the Problem of Robocentric Mapping
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: 0000-0002-1170-7162
2009 (English)In: ICRA: 2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION, 2009, 1540-1547 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper provides a novel solution for robo-centric mapping using an autonomous mobile robot. The robot dynamic model is the standard unicycle model and the robot is assumed to measure both the range and relative bearing to the landmarks. The algorithm introduced in this paper relies on a coordinate transformation and an extended Kalman filter like algorithm. The coordinate transformation considered in this paper has not been previously considered for robocentric mapping applications. Moreover, we provide a rigorous stochastic stability analysis of the filter employed and we examine the conditions under which the mean-square estimation error converges to a steady-state value.

Place, publisher, year, edition, pages
2009. 1540-1547 p.
Series
IEEE International Conference on Robotics and Automation-ICRA, ISSN 1050-4729
Keyword [en]
SIMULTANEOUS LOCALIZATION, SLAM, CONSISTENCY
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-29913DOI: 10.1109/ROBOT.2009.5152424ISI: 000276080400249Scopus ID: 2-s2.0-70350383467ISBN: 978-1-4244-2788-8 (print)OAI: oai:DiVA.org:kth-29913DiVA: diva2:398585
Note
QC 20110218Available from: 2011-02-18 Created: 2011-02-17 Last updated: 2011-12-20Bibliographically approved

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