Abstract
This paper presents an embedded hardware/software implementation for the computing system of a small scale unmanned autonomous sailing boat. The system is integrated in a single XILINX FPGA, and hosts a Microblaze soft processor surrounded with heterogeneous, custom designed, control and processing modules than handle the interface with all the sensors, actuators and communication devices of the sailing boat. These interfacing modules implement tasks that have been decentralized from the main processor, thus alleviating its computational load and providing processing time for higher level software applications. Using an FPGA to implement an integrated single-chip computing system, as an alternative to conventional processors, has proven to be a very flexible solution as it eases the migration of computation tasks between the hardware and software domains, and more importantly, allowing the rapid adaptation of the digital interfacing hardware in order to support additional peripheral devices required for an application mission. The software component of the boat's control system runs on the top of the uClinux embedded operating system and is formed by various concurrent applications developed in C with the standard Linux libraries. The remote monitoring, configuration and operation of the sailing boat is done via a WiFi link, using a graphics interactive application that runs on a conventional PC.

Abstract
This paper addresses the design and implementation of feedback controllers for the direction of autonomous robotic sailboats. In order to design such a controller, it is important to determine a model for the sailboat dynamics during turns. However, there are many uncontrollable factors that may affect the direction of the sailboat, which make it difficult to obtain an accurate model and require a lot of sensors to feed a proper controller. Instead, we assume a rather simple model relating the most important variables and concentrate on data that can easily be available with simple low-cost sensors, compensating the lack of accuracy of the model with the robustness of the controller. We describe our approach to extract the parameters of such a dynamic model using data obtained in field experiments and we show how to use this model to tune a PI controller. As a case study, we use the FASt vehicle, a 2.5 m long robotic sailing boat capable of fully autonomous navigation through a set of predefined marks. Experimental results show the performance of the designed controller. © 2010 IEEE.

Abstract
The lack of penetration of light and electromagnetic radiation beyond a few meters in the ocean makes acoustics the technique of choice for data transmission, target detection and ocean sensing in general. Acoustic transducers are typically based on piezoelectric materials due to the good response at high frequencies. Depending on the application it can be built using ceramics, polymers and composite materials. In the hydrostatic mode PZT ceramics hydrophones have low performance due to the low hydrostatic piezoelectric stress value. On the other hand, PVDF have shown relatively high hydrostatic mode response. This work presents the development of a PVDF hydrophone for deep sea applications. The hydrophone was subjected to a pressure test up to 25 MPa to evaluate the response variation under high hydrostatic pressure. The results show an increase up to 6 dB sensitivity under 15 MPa pressure.

Abstract
There are several compelling reasons for exploring the ocean, for instance, the potential for accessing valuable resources, such as energy and minerals; establishing sovereignty; and addressing environmental issues. As a result, the scientific community has increasingly focused on the use of autonomous underwater vehicles (AUVs) for ocean exploration. Recent research has demonstrated that buoyancy change modules can greatly enhance the energy efficiency of these vehicles. However, the literature is scarce regarding the dynamic models of the vertical motion of buoyancy change modules. It is therefore difficult to develop adequate depth controllers, as this is a very complex task to perform in situ. The focus of this paper is to develop simplified linear models for a buoyancy change module that was previously designed by the authors. These models are experimentally identified and used to fine-tune depth controllers. Experimental results demonstrate that the controllers perform well, achieving a virtual zero steady-state error with satisfactory dynamic characteristics.

Abstract
This paper describes a robotic system to detect and estimate the volume of sediments in underwater wall corners, in scenarios with zero visibility. All detection and positioning is based on data from a scanning sonar. The main idea is to scan the walls and the bottom of the structure to detect the corner, and then use data obtained in the direction of the corner to estimate the presence of sediment accumulation and its volume. Our approach implements an image segmentation to extract range from the surfaces of interest. The resulting data is then employed for relative localization and estimate of the sediment accumulation. The paper provides information about the methodologies developed and data from practical experiments.

Abstract