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Searching an accurate and effective simultaneous localization and mapping (SLAM) algorithm is fundamental to autonomous underwater vehicles (AUVs) to perform robust autonomous navigation. FastSLAM is one of the most popular SLAM algorithms. In spite of its wide applications, it still suffers from two major drawbacks, inconsistency and particle degeneration. In this paper, a modified FastSLAM algorithm...
Simultaneous localization and mapping (SLAM) has become a hot topic for autonomous underwater vehicles (AUVs) used in underwater applications. The most recent approach iSAM2 has been successfully applied in large-scale environment. In order to choose a good variable ordering for the efficiency of the sparse matrix solution, iSAM2 uses a strategy called incremental variable reordering. However, applying...
SLAM has increasingly become a hot topic for vehicle applications in underwater environments, searching an accurate and effective method for loop closure detection is one of the key issues for SLAM. The benefit of closed loop is the repeated observation of features, which can update the overall vehicle trajectory and environmental map to get more precise localization and mapping. In this paper we...
In this paper, iterative classification matching (ICM), a novel practical data association method, is proposed. ICM is an iterative approach to solve the data association problem which reconsiders the established observation-feature pairing and applies the quaternion approach to yield a least squares matching vector. The map features which are not associated with any observations are updated then...
The underwater vehicles technology has been developed rapidly in recent years. In the past years, the method of Simultaneous Localization and Mapping (SLAM) has prevailed and provided a feasible way of autonomous navigation. This paper introduces an algorithm based on Inertial Measurement Units (IMU) and sonar for autonomous navigation of underwater vehicles, which is called Inertial-SLAM algorithm...
Data association is one of the most difficult problems in Simultaneous Localization and Mapping (SLAM). As for Autonomous Underwater Vehicle (AUV), reliable data association is particularly important because of complex and mutable underwater environment. In this paper two prevailing data association algorithms-Individual Compatibility Nearest Neighbor (ICNN) and Joint Compatibility Branch and Bound...
The paper describes a localization system for autonomous underwater vehicles (AUV). It uses a DVL (Doppler velocity log) sensor and AHRS (attitude and heading reference system) sensor to measure AUV's depth, attitude and velocities relative to the bottom. A mechanically scanning imaging sonar (MSIS) is employed to obtain acoustic images of objects in underwater environment. In order to estimate optimally...
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