articleIEEE Robotics & Automation MagazineAug 23, 2006Closed access

Simultaneous localization and mapping (SLAM): part II

TBT. BaileyHDHugh Durrant‐Whyte

University of Sydney · Australian Centre for Robotic Vision · +1 more institution

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Abstract

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.

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2,516
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Topics & keywords

Topics
Keywords
  • Simultaneous localization and mapping
  • Data association
  • Representation (politics)
  • Artificial intelligence
  • Key (lock)
  • Computer science
  • Bayesian probability
  • Computer vision
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