Bathymetric Particle Filter SLAM Based on Mean Trajectory Map Representation
نویسندگان
چکیده
To obtain independent navigation results for autonomous underwater vehicles (AUVs) and construct high-resolution consistent seabed maps, a particle filter-based bathymetric simultaneous localization mapping (BSLAM) method with the mean trajectory map representation is proposed. reduce computational consumption, particles only keep current estimated position of vehicle, while all historical states vehicle are stored in map. Using this set-up, weights which closed to calculated newly collected data. A hierarchical clustering procedure also discussed identify invalid loop closures. The performance proposed validated using both simulated data field from sea trails. demonstrate that 50% more accurate faster than state-of-the-art BSLAM method, it has similar accuracy but 30% compared graph-based method.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2021
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2021.3078854