Abstract
Underwater imaging is being increasingly helpful for the autonomous robots to reconstruct and map the marine environments which is fundamental for searching for pipelines or wreckages in depth waters. In this context, the accuracy of the information obtained from the environment is of extremely importance. This work presents a study about the accuracy of a reconfigurable stereo vision system while determining a dense disparity estimation for underwater imaging. The idea is to explore the advantage of this kind of system for underwater autonomous vehicles (AUV) since varying parameters like the baseline and the pose of the cameras make possible to extract accurate 3D information at different distances between the AUV and the scene. Therefore, the impact of these parameters is analyzed using a metric error of the point cloud acquired by a stereoscopic system. Furthermore, results obtained directly from an underwater environment proved that a reconfigurable stereo system can have some advantages for autonomous vehicles since, in some trials, the error was reduced by 0.05m for distances between 1.125 and 2.675 m.

Abstract
In this article we describe the implementation of remote monitoring and control for multiple and independent experiments, namely, ecosystem replication experiments. First by presenting the main concepts behind the system architecture, and ultimately its design, and secondly by discussing its implementation. The system makes use of IEEE 802.15.4 Standard for Wireless Communications, a BeagleBone Black as the central coordinator for the experiments, and Arduino Mega as the monitoring and control device for each experiment. Data is stored on a PostgreSQL RDBMS, and the user interfaces with the system through a Website.

Abstract
Aquaculture processes usually take place in remote and harsh environments, and are highly dependent on uncontrollable and unpredictable variables, therefore its monitoring and supervision can be a key factor in this activity. Taking that into account, this paper proposes a solution for a Remote Supervision System for Aquaculture Platforms, that contemplates a modular, reconfigurable and expandable sensor network based on the I2C protocol, which is composed by two different types of sensor nodes. The main sensor node, which serves as the sensor network coordinator and as a gateway, and the tiny sensor nodes, that are responsible for simple data collection tasks.

Abstract
This paper presents the design and development of a new Autonomous Underwater Vehicle (AUV). SHAD, which stands for Small Hovering AUV with Differential actuation, is a torpedo shaped vehicle that was conceptually designed to navigate in challenging volumes. It brings to the scene of submarine robotics a different model and new design of AUV. The small size, the light weight and the high maneuverability of this AUV were among the most important features that can make the SHAD an option to applications where other models have difficulties. This paper details the design and the development of SHAD and presents experimental results from sensors and actuators testing as well as vehicle navigation.

Abstract
This paper presents results of the INESC TEC participation in the maritime environment (both at surface and underwater) integrated in the ICARUS team in the euRathlon 2015 robotics search and rescue competition. These relate to the marine robots from INESC TEC, surface (ROAZ USV) and underwater (MARES AUV) autonomous vehicles participation in multiple tasks such as situation assessment, underwater mapping, leak detection or victim localization. This participation was integrated in the ICARUS Team resulting of the EU funded project aimed to develop robotic tools for large scale disasters. The coordinated search and rescue missions were performed with an initial surface survey providing data for AUV mission planning and execution. A situation assessment bathymetry map, sidescan sonar imaging and location of structures, underwater leaks and victims were achieved, with the global ICARUS team (involving sea, air and land coordinated robots) participating in the final grand Challenge and achieving the second place.

Abstract
This paper presents the last developments towards vision-based target tracking by an AUV. The main concepts behind the visual relative localization are provided and the results from a statistical analysis for the relative localization algorithm are presented. The purpose of this analysis is to ensure properness of data used to feed controllers that are responsible for governing the AUV motion. A new set of controllers enabling the AUV to track a visual target is given. Experimental data from obtained from tests in tank are presented, validating both the visual relative localization and control of the AUV.