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.

Abstract
This work presents an autonomous system for marine integrated physical-chemical and biological monitoring - the MarinEye system. It comprises a set of sensors providing diverse and relevant information for oceanic environment characterization and marine biology studies. It is constituted by a physical-chemical water properties sensor suite, a water filtration and sampling system for DNA collection, a plankton imaging system and biomass assessment acoustic system. The MarinEye system has onboard computational and logging capabilities allowing it either for autonomous operation or for integration in other marine observing systems (such as Observatories or robotic vehicles. It was designed in order to collect integrated multi-trophic monitoring data. The validation in operational environment on 3 marine observatories: RAIA, BerlengasWatch and Cascais on the coast of Portugal is also discussed.

Abstract
This paper presents a new concept for a deep sea lander system combining both sea bottom permanence characteristics with autonomous repositioning functionalities and efficient ascent/descent motion in the water column. The TURTLE hybrid lander is a particular type of autonomous underwater vehicle designed to act as sea bottom fixed observation node or in operations of transport equipment to the deep sea. The paper discusses the general concept of operation and applications and also presents the developed prototype. This system was developed under a dual use EDA (European Defense Agency) project and with national and European funds. Considered as one of the dual use (civil and military) success stories, the demonstrator was equipped to sensors allowing both seismographic data gathering and acoustic monitoring applications.

Abstract
This paper addresses the use of heterogeneous sensors for target detection and recognition in maritime environment. An Unmanned Aerial Vehicle payload was assembled using hyperspectral, infrared, electro-optical, AIS and INS information to collect synchronized sensor data with vessel ground-truth position for conducting air and sea trials. The data collected is used to develop automated robust methods for detect and recognize vessels based on their exogenous physical characteristics and their behaviour across time. Data Processing preliminary results are also presented.

Abstract
A great variety of human gesture recognition methods exist in the literature, yet there is still a lack of solutions to encompass some of the challenges imposed by real life scenarios. In this document, a gesture recognition for robotic search and rescue missions in the high seas is presented. Themethod aims to identify shipwrecked people by recognizing the hand waving gesture sign. We introduce a novelmotion descriptor, through which high recognition accuracy can be achieved even for low resolution images. The method can be simultaneously applied to rigid object characterization, hence object and gesture recognition can be performed simultaneously. The descriptor has a simple implementation and is invariant to scale and gesture speed. Tests, preformed on a maritime dataset of thermal images, proved the descriptor ability to reach a meaningful representation for very low resolution objects. Recognition rates with 96.3% of accuracy were achieved.