Abstract-This paper compares two well known scan matching algorithms: the MbICP and the pIC. As a result of the study, it is proposed the MSISpIC, a probabilistic scan matching algorithm for the localization of an Autonomous Underwater Vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), and the robot displacement estimated through dead-reckoning with the help of a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). The proposed method is an extension of the pIC algorithm. Its major contribution consists in: 1) using an EKF to estimate the local path traveled by the robot while grabbing the scan as well as its uncertainty and 2) proposing a method to group into a unique scan, with a convenient uncertainty model, all the data grabbed along the path described by the robot. The algorithm has been tested on an AUV guided along a 600m path within a marina environment with satisfactory results.

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Sometimes, the results provided by colour image processing systems are not accurate enough due to the physical process of image formation. One of that problems is cotour clipping, which appear when at least one of the sensor components is saturated. We propose a method to recover the chromatic information of those pixels on which colour has been clipped. The chromatic correction method is based on the fact that some chromatic characteristics are invariant to the uniform scaling of the three RGB components. In this paper we present this method and one study of the chromatic components to which it can be applied.