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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关键词
Simultaneous localization and mapping,Vehicles,Computational complexity,Computational efficiency,Delay estimation,Uncertainty,Robotics and automation,Mobile robots,Robustness,Bayesian methods