Abstract
This paper presents the work performed in the implementation of an underwater simulation environment for the development of an autonomous underwater vehicle for the exploration of flooded underground tunnels. In particular, the implementation of a laser based structured light system, multibeam sonar and other robot details were addressed. The simulation was used as a relevant tool in order to study and specify the robot multiple sensors characteristics and placement in order to adequately survey a realistic environment. A detailed description of the research and development work is presented along with the analysis of obtained results and the benefits this work brings to the project. © 2017 IEEE.

Abstract
This paper aims at presenting the STRONGMAR Summer School 2016 that took place at the Base Naval de Lisboa, of the Portuguese Navy. The STRONGMAR project ideal motivates the development of maritime and marine science research and technology through the knowledge transfer between INESC TEC and promising, and prestigious, leading research European institutions. This process takes place through theoretical lectures and training, and via experimental application of the concepts discussed in order to further develop technology related to the sea environment. The practical application of the STRONGMAR project ideal takes place during events such as summer schools, winter schools, thematic workshops and scientific conferences. The STRONGMAR Summer School 2016 approaches the subject of "Introduction to Advanced Marine Technologies", providing a strong component of practical applications in underwater archaeology. It develops the study of unmanned systems applied to underwater archaeology, through the use of unmanned underwater vehicles. As a whole, this paper describes the Summer School experience, providing some results and greater insight on the topic of underwater archaeology.

Abstract
This paper describes the calibration of an underwater navigation system in enclosed scenarios. The work was performed in the context of the VAMOS project addressing the development of robotic solutions for flooded open pit mine exploration. An algorithm for calibration of extrinsic parameters for DVL and USBL systems is presented. Field experiments were performed with the ROAZ autonomous surface vehicle equipped with the underwater sensors and using precision IMU/GNSS fused data as groundtruth. The tests were performed in Douro River and in the Bejanca open pit mine, one of the VAMOS test sites, both in northern Portugal. The procedure was validated in the operational scenarios and results are presented showing the error correction and navigation quality improvement.

Abstract
The robotics community is concerned with the ability to infer and compare the results from researchers in areas such as vision perception and multi-robot cooperative behavior. To accomplish that task, this paper proposes a real-time indoor visual ground truth system capable of providing accuracy with at least more magnitude than the precision of the algorithm to be evaluated. A multi-camera architecture is proposed under the ROS (Robot Operating System) framework to estimate the 3D position of objects and the implementation and results were contextualized to the Robocup Middle Size League scenario.

Abstract
The planning of mining operations in water filled open-pit mines requires detailed bathymetry to create a mine plan and assess the involved risks. This paper presents post processing techniques for creating an improved 3D model from a survey carried out using an autonomous surface vehicle with a multibeam sonar and a GPS/INS navigation system. Inconsistencies of the created point cloud as a result of calibration errors or GPS signal loss are corrected using a continuous-time simultaneous localization and mapping (SLAM) solution. Signed distance function (SDF) based mapping is employed to fuse the measurements from multiple runs into a consistent representation and reduce sensor noise. From the signed distance function model we reconstruct a 3D surface mesh. We use this terrain model to establish a virtual reality scene for immersive data visualization of the mining operations for testing and planing during development. Results of the proposed approach are demonstrated on a dataset captured in an abandoned submerged inland mine.

Abstract
In the context of detection, location and tracking of human targets with combination of thermographic and visible cameras, this paper addresses the problem of geometric calibration of thermographic and visible spectrum cameras necessary for the stereo perception of targets in the robot frame. A method for precise geometric calibration of thermographic and visible cameras in the autonomous surface vehicle (ASV) ROAZ II is presented. The method combine the utilization of special patterns for intrinsic calibration of thermographic cameras, with the usage of a high-resolution 3D laser scanner for the extrinsic calibration, relating the cameras frames with the robot frame. Calibration process results are presented and analyzed.