A New Approach for a Reconfigurable Autonomous Underwater Vehicle for Intervention

The work shows an ongoing project named RAUVI (i.e. Reconfigurable AUV for Intervention). This project aims to design and develop an Underwater Autonomous Robot, able to perceive the environment by means of acoustic and optic sensors, and equipped with a robotic arm in order to autonomously perform simple intervention tasks. A complete simulation environment, including this new concept of robot, has been developed and it is presented as preliminary result.

Guiding a Path Planning Algorithm with Topological Constraints: Application to an AUV

A Topologically Guided Path Planner for an AUV Using Homotopy Classes

Detection of Cracks and Corrosion for Automated Vessels Visual Inspection

Combination of Weak Classifiers for Metallic Corrosion Detection and Guided Crack Location

First Steps Towards a Roboticized Visual Inspection System for Vessels

Scan-Based SLAM with Trajectory Correction in Underwater Environments

This paper presents an approach to perform Simultaneous Localization and Mapping (SLAM) in underwater environments using a Mechanically Scanned Imaging Sonar (MSIS) not relying on the existence of features in the environment. The proposal has to deal with the particularities of the MSIS in order to obtain range scans while correcting the motion induced distortions. The SLAM algorithm manages the relative poses between the gathered scans, thus making it possible to correct the whole Autonomous Underwater Vehicle (AUV) trajectories involved in the loop closures. Additionally, the loop closures can be delayed if needed.

The experiments are based on real data obtained by an AUV endowed with an MSIS, a Doppler Velocity Log (DVL) and a Motion Reference Unit (MRU). Also, GPS data is available as a ground truth. The results show the quality of our approach by comparing it to GPS and to other previously existing algorithms.

A first design for CANsistant: a mechanism to prevent inconsistent omissions in CAN in the presence of multiple errors

Demonstrating the feasibility of media management in ReCANcentrate

First quantitative results of the dependability improvement achieved by ReCANcentrate