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This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and...
This paper presents a sonar-based localization approach for an autonomous underwater vehicle, valid both in structured and unstructured environments. The presented system is based on a particle filter approach to represent the vehicle state. It uses a mechanical scanning imaging sonar, as the main sensor to have information about the environment. In this paper we present the chosen approach, highlighting...
The objective of this paper is to compare the performance of the proposed measurement assisted partial resampling (MAPR) particle filter against the performance of the extended Kalman filter (EKF) within the context of a dynamic 6 DoF hydrodynamic system. In order to compare the respective performances of the above two filters in resolving a navigation solution, the filters are given a trajectory...
This paper proposes a novel technique to estimate slips and velocities of an unmanned skid-steered vehicle. An optical flow-based visual sensor looking down the terrain surface is employed to recover the motion of the vehicle by tracking features selected from the terrain surface. The special orientation of the on-board camera is to assure high accuracy of the motion estimation. To cope with the noise...
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