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
This letter presents a novel architecture for evaluating the success of picking operations that are executed by industrial robots. It is formed by a cascade of machine learning algorithms (kNN and SVM) and uses information obtained by a 6 axis force/torque sensor and, if available, information from the built-in sensors of the robotic gripper. Beyond measuring the success or failure of the entire operation, this architecture makes it possible to detect in real-time when an object is slipping during the picking. Therefore, force and torque signatures are collected during the picking movement of the robot, which is decomposed into five different stages that allows to characterize distinct levels of success over time. Several trials were performed using an industrial robot with two different grippers for picking a long and flexible object. The experiments demonstrate the reliability of the proposed approach under different picking scenarios since, it obtained a testing performance (in terms of accuracy) up to 99.5% of successful identification of the result of the picking operations, considering an universe of 400 attempts.

Abstract
This paper describes a robot with 12 degrees of freedom for pick-and-place operations using bricks. In addition, an optimization approach is proposed, which determines the state of each joint (that establishes the pose for the robot) based on the target position while minimizing the effort of the servomotors avoiding the inverse kinematics problem, which is a hard task for a 12 DOF robot manipulator. Therefore, it is a multi-objective optimization problem that will be solved using two optimization methods: the Stretched Simulated Annealing method and the NSGA II method. The experiments conducted in a simulation environment prove that the proposed approach is able to determine a solution for the inverse kinematics problem. A real robot formed by several servomotors and a gripper is also presented in this research for validating the solutions.

Abstract