Angelo Odetti

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

Autonomous Underwater Intervention: Experimental Results of the MARIS Project

Autonomous underwater vehicles are frequently used for survey missions and monitoring tasks, however, manipulation and intervention tasks are still largely performed with a human in the loop. Employing autonomous vehicles for these tasks has received a growing interest in the last ten years, and few pioneering projects have been funded on this topic. Among these projects, the Italian MARIS project had the goal of developing technologies and methodologies for the use of autonomous underwater vehicle manipulator systems in underwater manipulation and transportation tasks. This work presents the developed control framework, the mechatronic integration, and the projects final experimental results on floating underwater intervention.

P2-ROV a portable/polar ROV

P2-ROV is a portable polar ROV. Designed to be transported via-helicopter and easily handled by a small team of scientists it is specially addressed to work under the shelf ice of Antarctica by exploiting the holes drilled in the ice by means of a special 350 mm auger; the shape of the vehicle reminds that of a torpedo contained in a 340 mm diameter. Highly automated, P2-ROV is designed to work in hovering in order to monitor the peculiar Platelet Ice and to collect biological samples. For this purpose it will be equipped with a mechanical arm with an embedded suction pump which permits to collect larvae and fish eggs of the species that live and breed in the Platelet Ice. During these operations P2-ROV is remotely controlled, with a tether that transmits mutual information and electrical power, by operators safely standing on the Pack Ice. P2-ROV, light and manageable, is highly modular thanks to the open-frame chassis that allows for quick installation and shifting of tools, equipment and sensors. Even thrusters are interchangeable and displace-able modules. In this way the vehicle can be reconfigured at every mission according to the specific needs.

Cost-Effective Technologies to Study the Arctic Ocean Environment

The Arctic region is known to be severely affected by climate change, with evident alterations in both physical and biological processes. Monitoring the Arctic Ocean ecosystem is key to understanding the impact of natural and human-induced change on the environment. Large data sets are required to monitor the Arctic marine ecosystem and validate high-resolution satellite observations (e.g., Sentinel), which are necessary to feed climatic and biogeochemical forecasting models. However, the Global Observing System needs to complete its geographic coverage, particularly for the harsh, extreme environment of the Arctic Region. In this scenario, autonomous systems are proving to be valuable tools for increasing the resolution of existing data. To this end, a low-cost, miniaturized and flexible probe, ArLoC (Arctic Low-Cost probe), was designed, built and installed on an innovative unmanned marine vehicle, the PROTEUS (Portable RObotic TEchnology for Unmanned Surveys), during a preliminary scientific campaign in the Svalbard Archipelago within the UVASS project. This study outlines the instrumentation used and its design features, its preliminary integration on PROTEUS and its test results.

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.

A practical identification procedure for unmanned underwater vehicles — From modeling to experiments

The need of defining suitable dynamical models for Unmanned Underwater Vehicles (UUVs) is of absolute importance for the sake of a precise motion estimation (needed due the slow rate and low precision measurement usually provided by acoustic devices) and guidance & control system design, where regulation scheme and parameter setting have to be defined and evaluated on the basis of a reliable dynamical model.