Master
University of Ljubljana FACULTY OF ELECTRICAL ENGINEERING

This course covers introduction to artificial intelligent systems: artificial perception, artificial intelligence, soft computing, machine learning, autonomous agents, and ambient intelligence, intelligent problem solving: problem decomposition and reduction, graph representation of problems, and graph search - exhaustive and heuristic search algorithms., expert systems: expert system components and human interfaces, procedural and declarative knowledge, and reasoning process, knowledge representation: production rules, fuzzy production rules, and representation based on the Petri nets and inference: forward and backward chaining, fuzzy inference, and probabilistic inference.

In Autonomus mobile systems, students will learn about autonomous mobile systems and definition of the agent concept, categorization of such systems regarding their properties such as: autonomy, mobility, different agent performance, systems structures, driving mechanism, goals, sensing and interactions with environment and areas of applicability, agents architecture and some examples of construction, multi-agent systems (MAS) as a subfield of artificial intelligence, introduction of principles for complex systems construction using agents as basic entities and possible areas of applications, classification based on different properties and capabilities and properties and disadvantages of such system usage.

The course includes the following topics: spectrums, ranges, electrical dimensions, technologies, plan of attack, RF systems: WLAN, GSM, GPS, Sensors, RF Biomedical systems, research equipmnet (NMR), common RF modules, short introduction to theory basics: waves, lines, abstract models, S and X parameters, imedance and admitance matrices, ABCD matrix, Smith chart, tunning, modelling, CAD tools, RF simulations and RF measurements.

Course covers the aims of computer vision, the origins of computer vision, and related fields and computer vision trends and application domains.

In this course the following topics will be introduced: design of new products, innovation process, product development cycle, technology market development phases, new product design approaches, cost analyses, electrical, mechanical, thermal and product design requirements, amortization period and safe disposal the device, economic aspects of the construction and operation of electronic devices, basics of reliability theory of electronic systems, probability distribution functions, environmental influences, Arhhenious plot, part stress analysis prediction, reliability databases, redundancy basics and fault tolerant design.

The course concentrates on humans and their needs for light. With the help of selected chapters it shows the effects of light on humans and how we can use these effects in connection with lighting and modern light sources to improve our lives. Today lighting should not only enable our vision but should also stimulate our entire organism. Beside that lighting should be energy-efficient and have minimal negative impacts on our environment.

System analysis classification, algorithm division, signal analysis (excitation and disturbance signals), the area of use. Least squares method, regression method, bias and consistency of estimates. Dynamical model parameter estimation, model parameterisation, extended least squares method, instrumental variables method, recursive versions of least squares, the adaptation for time varying systems – weighted least squares and exponential forgetting, the influence of unknown steady states, numerical problems. Identification of non-parametric models.

The objective of the course Biomechanics is to familiarize students with fundamental laws of mechanics and to present how these can be applied to understanding and analyzing the living systems. In the perspectives of transferring solutions from the nature the knowledge on biomechanics is fundamental in development of robotic systems, artificial organs, biomaterials, rehabilitation products, simulation models, and intelligent devices for exercise in rehabilitation and sport.

Definition of human-robot interaction problem; Human factors: perception, motor skills, social aspect of interaction, safety; Haptic robots: kinematics, dynamics, collision detection, collision force rendering, control and stability analysis; Teleoperation systems: architectures, force and position scaling, control, virtual fixtures, micro/nano manipulation; Soft robots based on variable impedance actuators; Medical robotics: surgical robotics, robot-supported diagnostics, micro-robots in the human body, nanorobors at the cell level; Rehabilitation and assistive robotics: motor rehabilitation, exoskeletons, robotic prosthetics.