Abstract
This paper describes the TURTLE project that aim to develop sub-systems with the capability of deep-sea long-term presence. Our motivation is to produce new robotic ascend and descend energy efficient technologies to be incorporated in robotic vehicles used by civil and military stakeholders for underwater operations. TURTLE contribute to the sustainable presence and operations in the sea bottom. Long term presence on sea bottom, increased awareness and operation capabilities in underwater sea and in particular on benthic deeps can only be achieved through the use of advanced technologies, leading to automation of operation, reducing operational costs and increasing efficiency of human activity.

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
The paper presents a multi-robot cooperative framework to estimate the 3D position of dynamic targets, based on bearing-only vision measurements. The uncertainty of the observation provided by each robot equipped with a bearing-only vision system is effectively addressed for cooperative triangulation purposes by weighing the contribution of each monocular bearing ray in a probabilistic manner. The envisioned framework is evaluated in an outdoor scenario with a team of heterogeneous robots composed of an Unmanned Ground and Aerial Vehicle.

Abstract
This paper presents the design of low cost, small autonomous surface vehicle for missions in the coastal waters and specifically for the challenging surf zone. The main objective of the vehicle design described in this paper is to address both the capability of operation at sea in relative challenging conditions and maintain a very low set of operational requirements (ease of deployment). This vehicle provides a first step towards being able to perform general purpose missions (such as data gathering or patrolling) and to at least in a relatively short distances to be able to be used in rescue operations (with very low handling requirements) such as carrying support to humans on the water. The USV is based on a commercially available fiber glass hull, it uses a directional waterjet powered by an electrical brushless motor for propulsion, thus without any protruding propeller reducing danger in rescue operations. Its small dimensions (1.5 m length) and weight allow versatility and ease of deployment. The vehicle design is described in this paper both from a hardware and software point of view. A characterization of the vehicle in terms of energy consumption and performance is provided both from test tank and operational scenario tests. An example application in search and rescue is also presented and discussed with the integration of this vehicle in the European ICARUS (7th framework) research project addressing the development and integration of robotic tools for large scale search and rescue operations.

Abstract
This paper addresses the development of an underwater visual navigation system for a Remotely Operated Vehicle (ROV) based on Real-Time Simultaneous Localization and Mapping method using natural landmarks. Our proposed approach was tested in an indoor tank, where field experiments were performed to obtain 3D vehicle (VIDEORAY Pro3 ROV) trajectory, and results validated using an external stereo vision " ground-truth" system.

Abstract
Autonomous mobile robots perception systems are complex multi-sensors systems. Information from different sensors, placed in different parts of the platforms, need to be related and fused into some representation of the world or robot state. For that, the knowledge of the relative pose (position and rotation) between sensors frames and the platform frame plays a critical role. The process to determine those is called extrinsic calibration. This paper addresses the development of automatic robot calibration tool for Middle Size League Robots with rotating directional cameras, such as the ISePorto team robots. The proposed solution consists on a robot navigating in a path, while acquiring visual information provided by a known target positioned in a global reference frame. This information is then combined with wheel odometry sensors, robot rotative axis encoders and gyro information within an Extend Kalman filter framework, that estimates all parameters required for the sensors angles and position determination related to the robot body frame. We evaluated our solution, by performing several trials and obtaining similar results to the previous used manual calibration procedure, but with a much less time consuming performance and also without being susceptible to human error.