Abstract
Real-time image processing is a computational intensive task with applications in various engineering fields. In several image processing applications, a significant amount of computing power is committed to image enhancement operations, basic segmentation and identification of regions of interest for further analysis. Such type of front-end processing can be done efficiently by custom data-flow processors closely coupled to an image sensor This paper proposes a visual design environment to support the high-level design of custom data-flow processors for real-time image analysis applications. The tool is embedded in Matlab/Simulink, and the system modeling is done using a library of blocks that implement common low-level image processing operations. Functional validation is performed efficiently by the simulation engine of Simulink in a frame by frame basis, using the functions provided by the image processing toolbox in Matlab. The automatic generation of a synthesizable RTL model guarantees a logic implementation of the system that complies to the high-level model validated, under constraints imposed by the user and the target reconfigurable device.

Abstract
This paper presents a project based teaching experience in an advanced digital systems design course with emphasis on design methodologies and laboratory assignments. Projects are the core of the practised teaching methodology and are structured in a pedagogical format according to the course programme. The use of the FPGA technology as the most suitable implementation technology for digital design teaching purposes is discussed. The course structure, oriented to the development of real working digital systems, challenges the students and increases their motivation. This way, the learning process is improved and the classes are more productive. A laboratory development infrastructure based on a FPGA device, used to implement a real-time video processing system, is presented. Examples of laboratory projects implemented with this infrastructure in a recent course edition are also presented. © 2008 IEEE.

Abstract
This paper presents the computing infrastructure used in an autonomous unmanned small-scale sailboat. The system is based on a FPGA and includes custom designed interfaces for the various sensors and actuators used in the sailboat. The central processing unit is a 32-bit 50 MHz RISC microprocessor implemented as a soft IP core in the FPGA. The computing system runs uClinux, a simplified version of the popular Linux operating system. The usage of a reconfigurable platform enables a quick reconfiguration of the logic circuit implemented in the FPGA, facilitating the development stage and allowing a dynamic switch among different implementations, according to the navigation requirements and environmental conditions.

Abstract
This paper presents a custom processor designed to execute a time consuming function in a CFD application. The selected function implements the method TDMA (Tri-Diagonal Matrix Algorithm) for solving a tri-diagonal system of equations. The custom processor was implemented in a commercial PCI prototyping board based on Virtex4LX FPGAs and uses a dedicated memory cache system, address generators and a deep pipelined floating-point datapath. Running at 100MHz and assuming the input data already in the cache memories, the system reaches a throughput greater than 1.4GFLOPS.

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.