This thesis addresses the problem of wireless transmission between the operator station and the robot. There is a solution presented by way of testing the parameters of wireless modules, compare them in the environment and the draft protocol.

This thesis presents the design and construction of microcontroller based laboratory kit. Hardware part describes the wiring of microcontroller based laboratory kit. Software section describes the function of each program.

Contents of the thesis is to design and create an expansion board for the BeagleBoard computer one plate . The first and very important part was to find out all the possibilities for an extension of the computer itself . Choose the right expansion port . To study the possibility distribution of individual pins . Followed by the appropriate extension election districts that demonstrate the function of each enlargement . Test was designed PCB that contains circuits that change the voltage level of the BeagleBoard to protect a mini computer to the testing of each gusset periphery prevent damage to itself or part of the BeagleBoard . The peripherals themselves bind different parts of theoretical introduction. More specifically the extension of the LCD display is selected segment and includes two lines of 16 characters . When the possibility to add additional components were necessary to deal with the shortcomings of the output pins , this problem was solved by using an expander . He extends itself BeagleBoard by another 16 pins . On these pins are connected together on the LCD matrix keyboard . The creation of the board are two circuit temperature sensors , but have a different type of communication using I2C and one second using 1 -Wire bus . The board also contains various other bus outputs , for example, UART bus. It also contains an output pin which can be controlled PWM modulation . The remaining pins are versatile GPIO pins which can be programmed to define a function using the Linux operating system . The result is a final board of the package control programs which make it possible to verify the individual peripherals.

This project deals with the problematics of self-powered universal GSM/GPRS module which is used for sensorical applications. The first part analyzes features of mobile networks and applying energy from the environment. The second section expalins the various parts and characteristic of their associated components together with some fundamental functions of the technology for possible realization of sensoric module. The third part describes plan for system realisation and fourth parth illustrates achiaved results.

The main aim of this thesis is to design and build automatic calibration system for inertial measurement sensors. The calibration system is intended to support the development of devices with inertial measurement sensors. The great emphasis is placed on the configurability of system and for this reason all calculations are realized by Matlab system, which is well known by engineers. There is also presented design of inertial measurement unit, which is used as a~model sensor unit for calibration system development.

Cílem diplomové práce je navrhnout levný, avšak dostatečně výkonný a univerzální systém, schopný snímání a zpracování obrazu z digitální kamery. Další částí je návrh a implementace funkcí pro zpracování obrazu a komunikace s nadřazeným systémem.

This thesis deals with the design of overall concept of distributed system which is used for temperature, pressure and humidity measurement. The system is adapted to be used in instrument transformers and sensors production hall of ABB s.r.o. Brno. Firstly, the requirements for the measuring system are defined. After that market research focused on sensors and measurement modules is performed. The selected sensor is afterwards built into own measurement module for which hardware and software part is designed. The work continues with design of local and remote database of measured values. Besides, the PC software used for local and remote data storage is designed afterwards. The components of the measurement system are tested in the final part of the thesis.

This thesis project covers the development of a cross country skiing robot, with the purpose of being used as an instrument for measuring gliding properties of skis. The robot used in total 4 servomotors to control the motion of right and left arms with poles attached. A general movement pattern generator was developed to construct patterns that resemble the one of a human hand during poling. The final robot is able to generate a poling motion resulting in a forward propulsion, but further development to the design has to be made to use the robot for its intended purpose.

One problem with computers is that the operating system automatically trusts any externallyconnected peripheral. This can result in abuse when a peripheral technically can violate the security model because the peripheral is trusted. Because of that the security is an important issue to look at.The aim of our project is to see in which cases hardware peripherals can be trusted. We built amodel of the universal asynchronous transmitter/receiver (UART), a model of the main memory(RAM) and a model of a DMA controller. We analysed interaction between hardware peripherals,user processes and the main memory.One of our results is that connections with hardware peripherals are secure if the hardware is properly configured. A threat scenario could be an eavesdropper or man-in-the-middle trying to steal data or change a cryptographic key.We consider the use-cases of DMA and protecting a cryptographic key. We prove the well-behavior of the algorithm. Some error-traces resulted from incorrect modelling that was resolved by adjusting the models. Benchmarks were done for different memory sizes.The result is that a peripheral can be trusted provided a configuration is done. Our models consist of finite state machines and their corresponding SMV modules. The models represent computer hardware with DMA. We verified the SMV models using the model checkers NuSMV and nuXmv. / Målet med vårt projekt är att verifiera olika specifikationer av externa enheter som ansluts till datorn. Vi utför formell verifikation av sådan datorutrustning och virtuellt minne. Verifikation med temporal logik, LTL, utförs. Specifikt verifierar vi 4 olika use-case och 9 formler för seriell datakommunikation, DMA och virtuellt minne. Slutsatsen är att anslutning av extern hårdvara är säker om den är ordentligt konfigurerad.Vi gör jämförelser mellan olika minnesstorlekar och mätte tidsåtgången för att verifiera olika system. Vi ser att tidsåtgången för verifikation är långsammare än linjärt beroende och att relativt små system tar relativt lång tid att verifiera.

Fuzzy ARTMAP (FAM) is currently considered to be one of the premier neural network architectures in solving classification problems. One of the limitations of Fuzzy ARTMAP that has been extensively reported in the literature is the category proliferation problem. That is Fuzzy ARTMAP has the tendency of increasing its network size, as it is confronted with more and more data, especially if the data is of noisy and/or overlapping nature. To remedy this problem a number of researchers have designed modifications to the training phase of Fuzzy ARTMAP that had the beneficial effect of reducing this phenomenon. In this thesis we propose a new approach to handle the category proliferation problem in Fuzzy ARTMAP by evolving trained FAM architectures. We refer to the resulting FAM architectures as GFAM. We demonstrate through extensive experimentation that an evolved FAM (GFAM) exhibits good (sometimes optimal) generalization, small size (sometimes optimal size), and requires reasonable computational effort to produce an optimal or sub-optimal network. Furthermore, comparisons of the GFAM with other approaches, proposed in the literature, which address the FAM category proliferation problem, illustrate that the GFAM has a number of advantages (i.e. produces smaller or equal size architectures, of better or as good generalization, with reduced computational complexity). Furthermore, in this dissertation we have extended the approach used with Fuzzy ARTMAP to other ART architectures, such as Ellipsoidal ARTMAP (EAM) and Gaussian ARTMAP (GAM) that also suffer from the ART category proliferation problem. Thus, we have designed and experimented with genetically engineered EAM and GAM architectures, named GEAM and GGAM. Comparisons of GEAM and GGAM with other ART architectures that were introduced in the ART literature, addressing the category proliferation problem, illustrate similar advantages observed by GFAM (i.e, GEAM and GGAM produce smaller size ART architectures, of better or improved generalization, with reduced computational complexity). Moverover, to optimally cover the input space of a problem, we proposed a genetically engineered ART architecture that combines the category structures of two different ART networks, FAM and EAM. We named this architecture UART (Universal ART). We analyzed the order of search in UART, that is the order according to which a FAM category or an EAM category is accessed in UART. This analysis allowed us to better understand UART's functionality. Experiments were also conducted to compare UART with other ART architectures, in a similar fashion as GFAM and GEAM were compared. Similar conclusions were drawn from this comparison, as in the comparison of GFAM and GEAM with other ART architectures. Finally, we analyzed the computational complexity of the genetically engineered ART architectures and we compared it with the computational complexity of other ART architectures, introduced into the literature. This analytical comparison verified our claim that the genetically engineered ART architectures produce better generalization and smaller sizes ART structures, at reduced computational complexity, compared to other ART approaches. In review, a methodology was introduced of how to combine the answers (categories) of ART architectures, using genetic algorithms. This methodology was successfully applied to FAM, EAM and FAM and EAM ART architectures, with success, resulting in ART neural networks which outperformed other ART architectures, previously introduced into the literature, and quite often produced ART architectures that attained optimal classification results, at reduced computational complexity.