Andrea Ranieri

Underwater Intervention Robotics: An Outline of the Italian National Project MARIS

The Italian national project MARIS (Marine Robotics for InterventionS) pursues the strategic objective of studying, developing and integrating technologies and methodologies enabling the development of autonomous underwater robotic systems employable for intervention activities, which are becoming progressively more typical for the underwater offshore industry, for search-and-rescue operations, and for underwater scientific missions. Within such an ambitious objective, the project consortium also intends to demonstrate the achievable operational capabilities at a proof-of-concept level, by integrating the results with prototype experimental

Evaluation and comparison of navigation guidance and control systems for 2D surface path-following☆

Abstract Robotics nowadays is a mature discipline. For its widespread employment in real civilian scenarios, in close contacts with humans, additional efforts are needed to establish standards and common procedures to evaluate and assess robot performance. A methodology for performance evaluation is here proposed and some indices are formalized for the evaluation of robot behaviors against different criteria. The indices are tested on a number of experiments with unmanned marine vehicles, from different field campaigns and in different scenarios.

Machine learning methods for acoustic-based automatic Posidonia meadows detection by means of unmanned marine vehicles

This work describes the exploitation of a Remotely Operated Vehicle (ROV), equipped with a multi-parametric sensors package (acoustic and video), for the exploration and characterisation of sea-bottoms covered with Posidonia oceanica seagrass, which represents a valuable indicator of the environmental health. The data collection is achieved by the employment of a single beam echosounder and a down-looking underwater camera. An acoustic data procedural analysis based on machine learning methods was developed to automatically detect the Posidonia presence, so that in future works it will be possible to operate also in low-visibility conditions, using only the acoustic sensors. Data acquisition was carried out over different seafloor types in coastal area near Biograd Na Moru (Croatia) and the preliminary results are reported in the paper.