simultaneous localization and mapping (UFastSLAM) using the geometric information of particles. The information are the pose of particles and their geometric relation, which are utilized in both the importance weight and the resampling steps. In the importance weight step, all particles are grouped via their weights and updated more accurately using the weight compensation scheme. In addition, ...

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Simultaneous Localization and Mapping (SLAM) is a well-known solution for mapping realizing autonomous navigation of an Autonomous Underwater Vehicle (AUV) in unknown underwater environments. However, the inaccurate time-varying observation noise will cause filtering divergence reduce accuracy localization feature estimation. In this paper, VB-AUFastSLAM based on unscented-FastSLAM (UFastSLAM) ...

Simultaneous localization and mapping (SLAM) is crucial challenging for autonomous underwater vehicle (AUV) navigation in complex uncertain ocean environments. However, inaccurate time-varying observation noise parameters may lead to filtering divergence poor accuracy. In addition, particles are easily trapped local extrema during the resampling, which state estimation. this paper, we propose a...