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Simultaneous localization and mapping (SLAM): part II

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2 Author(s)
Bailey, Tim ; Australian Centre for Field Robotics, Sydney Univ., NSW ; Durrant-Whyte, H.

This paper discusses the recursive Bayesian formulation of the simultaneous localization and mapping (SLAM) problem in which probability distributions or estimates of absolute or relative locations of landmarks and vehicle pose are obtained. The paper focuses on three key areas: computational complexity; data association; and environment representation

Published in:
Robotics & Automation Magazine, IEEE  (Volume:13 ,  Issue: 3 )

Date of Publication: Sept. 2006

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