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.

Abstract
In this article we discuss the use of LBL acoustic networks for operations with multiple AUVs. Differently from standard LBL configurations, we propose to use the One-Way-Travel-Time of acoustic signals to compute the ranges between all the devices. Moreover, we derive the suitable algorithms for both the navigation of multiple vehicles, but also their external tracking. Experimental results are provided that support the evidence that our approach is successful in operations for multiple vehicles.

Abstract
Here we propose a simplified model for the path planning of an Autonomous Underwater Vehicle (AUV) in an horizontal plane when ocean currents are considered. The model includes kinematic equations and a simple dynamic equation. Our problem of interest is a minimum time problem with state constraints where the control appears linearly. This problem is solved numerically using the direct method. We extract various tests from the Maximum Principle that are then used to validate the numerical solution. In contrast to many other literature we apply the Maximum Principle as defined in [9].

Abstract
Nowadays, the technological and scientific research related to underwater perception is focused in developing more cost-effective tools to support activities related with the inspection, search and rescue of wreckages and site exploration: devices with higher autonomy, endurance and capabilities. Currently, specific tasks are already carried out by remotely-operated vehicles (ROV) and autonomous underwater vehicles (AUV) that can be equipped with multiple sensors, including optical cameras which are extremely valuable for perceiving marine environments; however, the current perceptual capability of these vehicles is still limited. In this context, the paper presents a novel mosaicking method that composes the sea-floor from a set of visual observations. This method is called RObust and Large-scale MOSaicking (ROLAMOS) and it enables an efficient frame-to-frame motion estimation with outliers removal and consistence checking, a robust registration of monocular images and, finally, a mosaic management methodology that makes it possible to map large visual areas with a high resolution. The experiments conducted with realistic images have proven that the ROLAMOS is suitable for mapping large-scale sea-floor scenarios because the visual information is registered by managing the computational resources that are available onboard, which makes it appropriate for applications that do not have specialized computers. Further, this is a major advantage for automatic mosaic creation based on robotic applications, that require the location of objects or even structures with high detail and precision.

Abstract
This paper addresses a three-dimensional (3D) reconstruction of a flooded open pit mine with an autonomous surface vehicle (ASV) and unmanned aerial vehicle (UAV). The ROAZ USV and the Otus UAV were used to provide the underwater bathymetric map and aerial 3D reconstruction based from image data. This work was performed wihtin the context of the European researcj project VAMOS with the objective of developing robotic tools for efficient underwater mining

Abstract
This paper presents the autononomous aerial vehicle OTUS and its application to search and rescue scenarios, namely the participation on the EuRathlon 2015 competition. The OTUS robot was developed at INESC TEC/ ISEP for research in cooperative aerial robotics and applications in complex and dynamic environments. The system was validated in this challenging scenario and was able to win the Grand Challenge scenario in cooperation with a land and marine robotics partner teams.