Abstract
Underwater acoustic localization is a challenging task. Most techniques rely on a network of acoustic sensors and beacons to estimate relative position, therefore localization uncertainty becomes highly dependent on the selected sensor configuration. Although several works in literature exploit optimal sensor placement to improve localization over large regions, the conditions contemplated in these are not applicable for the optimization of the acoustic sensors on constrained 3D shapes, such as the body of small underwater vehicles or structures. Additionally, most commercial systems used for localization with ultra-short baseline (USBL) configurations have compact acoustic sensors that cannot be spatially positioned independently. This work tackles the optimization of acoustic sensor placement in a limited 3D shape, in order to improve the localization accuracy for USBL applications. The implemented multi-objective memetic algorithm combines the Cramer-Rao Lower Bound (CRLB) configuration evaluation with incidence angle considerations for the sensor placement.

Abstract
Autonomous underwater vehicles (AUV) are increasing in popularity and importance for the realization of underwater explorations. Nowadays, these types of vehicles are implemented in underwater environments to accomplish tasks for military, scientific and industrial purposes. These vehicles can use imaging sonars that are effective in detecting the AUV's distance to an obstacle. The main goals of this paper were to extract meaningful information gathered by sonar, use it to map the surrounding environment, and locate the vehicle on the estimated map. To accomplish these goals, the system is composed of a constant false alarm rate (CFAR) algorithm to filter the sonar information, a feature extractor that filters the first obstacle for each sonar beam in a 360 degrees revolution, an Octomap to build the estimated map and a Particle Filter (PF) to locate the vehicle in the environment. This system was developed using a set of measurements in a rectangular tank where the AUV was in static positions and in motion.

Abstract
This paper describes a system designed to collect water samples, from the surface down to a configurable depth, and with configurable profiles of vertical velocity. The design was intended for the analysis of suspended sediments, therefore the sampling can integrate water flow for a given depth profile, or at a specific depth. The system is based on a catamaran-shaped platform, from which a towfish is lowered to collect the water samples. The use of a surface vehicle ensures a permanent link between the operator and the full system, allowing for a proper mission supervision. All components can be remotely controlled from the control station, or programmed for fully autonomous operation. Although the main intended use is for the analysis of suspended sediments in rivers, it can easily be extended to collect water samples in other water bodies.

Abstract
Ocean exploration is of major importance for several reasons, including energy and mineral resource retrieval, sovereignty, and environmental concerns. The use of autonomous underwater vehicles (AUV) has thus been receiving increased attention from the scientific community. In this context, it has been shown that the use of buoyancy change modules (BCMs) can significantly improve the energy efficiency of an AUV. However, the literature regarding the detailed design of these modules is scarce. This paper contributes to this field by describing the development of an electromechanical buoyancy change module prototype to be incorporated into an existing AUV. A detailed description of the constraints and compromises existing in the design of the device components is presented. In addition, the mechanical design of the hull based on FEM simulations is described in detail. The prototype is experimentally tested in a shallow pool where its full functionality is shown. The paper also presents preliminary experimental values of the power consumption of the device and compares them with the ones provided by existing models in the literature.

Abstract
In source localization problems, the relative geometry between sensors and source will influence the localization performance. The optimum configuration of sensors depends on the measurements used for the source location estimation, how these measurements are affected by noise, the positions of the source, and the criteria used to evaluate the localization performance. This paper addresses the problem of optimum sensor placement in a plane for the localization of an underwater vehicle moving in 3D. We consider sets of sensors that measure the distance to the vehicle and model the measurement noises with distance dependent covariances. We develop a genetic algorithm and analyze both single and multi-objective problems. In the former, we consider as the evaluation metric the arithmetic average along the vehicle trajectory of the maximum eigenvalue of the inverse of the Fisher information matrix. In the latter, we estimate the Pareto front of pairs of common criteria based on the Fisher information matrix and analyze the evolution of the sensor positioning for the different criteria. To validate the algorithm, we initially compare results with a case with a known optimal solution and constant measurement covariances, obtaining deviations from the optimal less than 0.1%. Posterior, we present results for an underwater vehicle performing a lawn-mower maneuver and a spiral descent maneuver. We also present results restricting the allowed positions for the sensors.

Abstract
In-situ calibration of marine sensors requires close-range positioning. In turn, localization relative to a given object of interest is necessary. This paper deals with the detection of a vertical cable hanging from a marine observatory implemented by means of a moored buoy. An algorithm composed of sequential image filtering, segmentation and template matching is proposed. Two approaches for generating the cable's acoustic image template are introduced. The performance of the approaches, obtained by comparison with ground-truth measurements, are illustrated over challenging cluttered acoustic images collected in a test tank. The results indicate a performance better than 74% of the best candidate to match the actual cable.