Abstract
Unmanned Underwater Vehicles (UUVs), such as Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs) are versatile tools, suitable for many activities in different fields, and have seen an increase in usage, making them an area of interest in the study of robotics. The performance of any underwater vehicle in any given task is deeply affected by the precision of its localization system. The main challenge in underwater localization is the significant attenuation of any Radio Frequency (RF) signal underwater, which prevents the use of many common location methods such as the Global Positioning System (GPS). Many methods have been studied for the localization of UUVs, including the use of acoustic beacons. One of these methods is the use of a single moving beacon to obtain acoustic ranges, as opposed to a stationary single beacon, which restricts the UUV's trajectory or multiple beacons, involving more hardware, complicating missions' logistics and increasing costs. In this paper, a guidance algorithm based on the Fisher Information Matrix is proposed for an Autonomous Surface Vehicle to serve as a beacon vehicle and aid in the navigation of a UUV. The approach performances are assessed by means of simulations of the complete system under realistic conditions.

Abstract
Nowadays, one of the problems associated with Unmanned Systems is the gap between research community and end-users. In order to emend this problem, the Portuguese Navy Research Center (CINAV) conducts the REX 2016 (Robotic Exercises). This paper describes the trials that were presented in this exercise, divided in two phases. The first phase happened at the Naval Base in Lisbon, with the support of divers and RHIBs (Rigid-Hulled Inflatable Boats), and the second phase, also with divers' support, at the coast of Lisbon-Cascais. It counted with many participants and research groups, including INESC-TEC, UNINOVA, TEKEVER and UAVISION. There are several advantages of doing this exercise, including for the Portuguese Navy, but also for partners. For the Navy, because it is an opportunity of being in contact with recent market technologies and researches. On the other hand, it is an opportunity for the partners to test their systems in a real environment, which usually is a difficult action to accomplish. Therefore, the paper describes three of the most relevant experiments: underwater docking stations, UAV and USV cooperation and Tracking targets from UAVs.

Abstract
Autonomous Underwater Vehicles (AUV) are growing in importance for their many underwater applications, due to their characteristics and functionalities. Making use of a imaging sonar, it is possible to acquire the AUV's distance to existing obstacles. Then, through an implementation of a feature detection algorithm and an estimator, it is possible to interpolate the vehicle's relative position. This paper proposes a localization method for structured environments employing a mechanical scanning sonar feeding an extended Kalman filter. Some tests were then run in two different water tanks in order to verify the effectiveness of the solutions. These tests were performed in two different phases. For the first one, all the readings were taken with the vehicle steady and immobile. The second phase was executed with the vehicle in motion. The results are presented and compared against ground-truth measurements.

Abstract
Corners usually appear very distinct from the rest of the scene in a mechanical scanning imaging sonar (MSIS) image, generally characterized by sharp intensities. The detection of corners is particularly useful in human-structured environments such as tanks because the knowledge on their location provides a way to compute the vehicle position. The combination of some basic operations typically used for image segmentation have great potential to detect and localize corners in sonar images automatically. This article proposes and evaluates with experimental data a set of image segmentation algorithms for corner detection in sonar scans. The developed algorithms are evaluated with ground truth, and their performance is analyzed following a few relevant metrics for autonomous navigation.

Abstract
In this paper we evaluate the long-term deployment feasibility of a large-scale network of abandoned underwater sensors, where power is provided by autonomous underwater vehicles (AUVs) in periodic visits.

Abstract
The use of Autonomous Underwater Vehicles (AUVs) is increasingly seen as a cost-effective way to carry out underwater missions. Due to their long endurance and set of sensors onboard, AUVs may collect large amounts of data, in the order of Gbytes, which need to be transferred to shore. State of the art wireless technologies suffer either from low bitrates or limited range. Since surfacing may be unpractical, especially for deep sea operations, long-range underwater data transfer is limited to the use of low bitrate acoustic communications, precluding the timely transmission of large amounts of data. The use of data mules combined with short-range, high bitrate RF or optical communications has been proposed as a solution to overcome the problem. In this paper we describe the implementation and validation of UDMSim, a simulation platform for underwater data muling oriented systems that combines an AUV simulator and the Network Simulator 3 (ns-3). The results presented in this paper show a good match between UDMSim, a theoretical model, and the experimental results obtained by using an underwater testbed when no localization errors exist. When these errors are present, the simulator is able to reproduce the navigation of AUVs that act as data mules, adjust the throughput, and simulate the signal and connection losses that the theoretical model can not predict, but that will occur in reality. UDMSim is made available to the community to support easy and faster evaluation of data muling oriented underwater communications solutions, and enable offline replication of real world experiments.