Simultaneous localization and mapping based on particle filter for sparse environment

Abstract

This paper presents a method for solving simulation localization and mapping (SLAM) in sparse-feature environment, by adopting a concept of particle filter with multiple extended Kalman filters (EKF). Compared with common FastSLAM where each particle is a sample of one vehicle path whereas each EKF is solely a feature estimator, the proposed algorithm… (More)

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