In this course students are introduced to engineering mechanics. The first part of the course
covers statics, including equilibrium of a particle and of a rigid body in 2-D and 3-D, force and
moment resultants, internal forces and moments, trusses and frames, basics of structural
analysis. The second part of the course introduces students to dynamics, and in particular to
particle kinematics and kinetics in 2-D and 3-D, to rigid body kinematics and kinetics in 3-D,
to concepts of work-energy, impulse-momentum, force-acceleration and to translational and
rotational motion.

In this course students are introduced to general concept of system dynamics. Particularly
students will cover such concepts as linear time invariant systems, Laplace transform, lumped
parameter modeling of mechanical systems, transfer-function approach to modeling dynamic
systems, state-space approach to modeling dynamic systems, introduction to modeling of
mechanical, electrical and electromechanical systems, time-domain analyses of dynamic
systems, frequency-domain analyses of dynamic systems.

This course introduces basics of electrical and electronic circuit analysis and design. Students
learn how to perform transient and sinusoidal steady-state analysis of RL, RC, and RLC circuits,
Norton-Thevenin equivalent representation, learn operational amplifiers. Main concepts shown
in class are concretized through practical lab sessions.

In this course students study the fundamentals of Laplace transforms and Bode diagrams as they
apply to electric circuit analysis, basic operation and application of main electronic components:
diodes, bipolar junction and field-effect transistors, operational amplifiers: ideal op-amp,
inverting and non-inverting configurations, op-amp circuits focusing on filters. Main concepts
shown in class are practiced through hand-on lab sessions on electronic circuit analysis and a
course design project.

The course presents and integrates the basic concepts for both continuous-time and discretetime signals and systems. Signal and system representations are developed for both time and
frequency domains. These representations are related through the Fourier transform and its
generalizations, which are explored in detail. Filtering and filter design, modulation, and
sampling for both analog and digital systems are discussed and illustrated. Main concepts shown
BSc in Robotics and Mechatronics
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in class are concretized through labs focusing on different sensors such as accelerometers,
gyroscopes, magnetometers, capacitive touch sensors, incremental encoders, potentiometers,
microphones, etc. The sensor data will be acquired using data acquisition cards and will be
analyzed using MATLAB software.

The course covers both the fundamentals of the logic and computer system design and also the
practical aspects of the microcontroller programming. Topics include Boolean algebra,
combinational logic circuit design, sequential logic circuit design, computer design basics;
instruction set concept, peripherals of microcontrollers. The course includes structured
laboratory sessions in C and VHDL programming languages that will help students to develop
skills in applying their knowledge to solve digital system design tasks such as a simple traffic
control system, SOS signal, and logic circuits. The assignments are typically implemented on
Arduino and FPGA/ARM microcontroller boards with using of different type of sensors.

This course focuses on the fundamentals of mechanical design which lays the analytical
foundation needed for the design of machine elements. The topics include the fundamentals of
mechanical design, materials and processes, solid mechanics, stress, strain and deflections,
static and fatigue failure theories and finite elements analysis (FEA). Laboratory sessions of the
course teach students basic skills of computer-aided design (CAD) and exposes them to
different manufacturing processes with major emphasis on additive and subtractive
manufacturing technologies. SolidWorks CAD software is used to introduce 3D solid modeling,
assembling, structural analysis and motion simulation of common machine elements, such as
shafts, bearings, gears, springs, screws and fasteners. After mastering basic skills of computergenerated design students will engage in the process of 3D printing with plastic and machining
with metal. Machining methods that are explained include drilling, cutting, bending, turning,
milling, grinding, and basis of CNC machining.

This course is intended to introduce students to concepts and techniques of classical linear
system control and to briefly introduce some concepts of modern control and discrete-time. The
main goal is to enable students to analyze, design, and synthesize linear control systems by
using the root locus and frequency-domain methods based on Bode diagrams. Students will
become familiar with analytical methods and will be exposed extensively to the use of
computers for analysis and design of control systems.

This course will introduce students with the theoretical and technological foundations of
classical and modern electromechanical systems. Particular emphasis will be given to electrical
drives and machines that are employed in robotics and automation. Students will gain basic
knowledge in electromagnetics and magnetic circuit analysis to predict electromagnetic
characteristics of electric machines and permanent magnet materials. Using principles of
electromechanical energy conversion they will be able to predict forces and torques in electric
machines and to simulate them using MATLAB/Simulink software. For the lab sessions of this
class, the students will design and build their own electric drive based on brushless DC motors
and apply to it torque, velocity, and position control.

This course covers classical topics in robotics with particular emphasis on the kinematics and
dynamics of industrial manipulators. Different kinematics architectures are introduced together
with classical modeling techniques based on homogeneous transformations. Alternative
methods, such as the fixed and Euler angle conventions, quaternions and the vector-angle
representation, are explained to represent the orientation of rigid bodies. Analysis of velocities,
static forces, and kinematic singular configurations is carried out by means of differential
kinematics. The equations of motion of a manipulator are derived using Newton-Euler and
Lagrange methods. The analytical closed form solution for the inverse dynamic problem is
obtained ready to be used as the core block for model-based control techniques and for
simulation purposes.

This course brings together elements of design in mechanical, electrical/electronic and control
systems so that students will have a good idea of the range of advanced techniques available in
developing robotic/mechatronic systems including selection and control of servo and
pneumatic/hydraulic actuators, integrating industrial automation tools, thus enhancing
theoretical and practical skills acquired in previous courses through theoretical and practical
assignments.

This course introduces control and simulation techniques suitable for industrial manipulators
and mobile robots. Motion control and trajectories planning are formalized in the joint and task
space. Linear and nonlinear control schemes are applied to industrial manipulators and tested
with the support of different simulation environments, such as Matlab, VREP and Gazebo. A
state-of-the-art operative system for robotics applications (ROS) is introduced.
Modern learning techniques are presented to acquire and adapt the inverse kinematic and
dynamic model of the robot in order to implement model-based feedback control schemes in
the joint and in the Cartesian space.

The course objective is to practice industrial project work within the robotics and mechatronics
engineering field. Projects include problem definition, making time schedule, information
retrieval, work coordination, problem solving, report writing and oral presentation. Student
should demonstrate ability both to apply knowledge acquired earlier in the education and within
a project team ability to acquire and apply more knowledge.

Embedded systems control everything from space robot rovers to home electronics. Any system
that responds at the pace of relevant events has real-time requirements and constraints whether
the timescale is short like the airbag controls for an automobile or longer like the flight
scheduling system for an airline. This course introduces underlying scientific and engineering
principles behind embedded real-time systems. Students can expect to learn how to program on
an embedded architecture and apply real-time principles that are used to drive critical embedded
systems like robotics, automobiles, avionics, medical equipment, etc. Topics covered include
embedded architectures; concurrency; real-time principles (multi-tasking, scheduling,
synchronization), etc. Through a series of practical exercises with state-of-the-art system-inchip microprocessor boards students will acquire skills of embedded Linux programming using
C programming tools and libraries.

The Power Electronics course is designed to introduce switch mode power supplies and power
converters (DC/DC, rectifiers and inverters). The introduction section of the course is focused
on diode- and thyristor-based half- and full-wave rectification in two- and three-phase
configurations. The DC/DC power converters section presents the operation modes and design
considerations for the standard switching power supply topologies such as the buck, boost,
buck-boost, and flyback DC/DC converters. There is a brief introduction to resonant converter
technology. The last section of the course covers power electronics inverters. Standard inverter
topologies are introduced, and various PWM algorithms for them are presented. Power quality
issues and closed-loop control schema are presented. Multilevel converter topologies are
introduced.

In this course students will get introduced to the concept of industrial automation and
programmable logic controllers (PLC). The topics will include: introduction to automation and
plants, an overview of the Factory Automation, programmable logic controllers (PLCs), PLC
hardware components, PLC programming using Ladder logic, programming timers and
counters, PLC installation, networking, Human machine interface (HMI), industrial sensors and
actuators, and some advanced topics in industrial automation.
Two main software tools will be introduced and used in the class, to practice developing
programs for the PLCs and to work with the real PLCs in the lab. Students will learn different
PLC programming languages.

This course provides an introduction to the fundamental concepts, algorithms, methods and
tools of digital image processing. The course aims to lay a solid mathematical foundation to
further study of concepts in image and video processing, computer vision, image segmentation
and understanding. After studying the basics of image formation and human visual system, topic
such as image sampling and quantization, intensity transformations, spatial filtering, filtering in
the frequency domain, color image processing, image processing and image segmentation will
be covered. Matlab and OPENCV (using Python or C++ programming languages) will be used
extensively for projects which aim to provide practical insight into the real-world
implementation of image processing techniques.

Robotics and Mechatronics students have an opportunity to complete a credit-bearing internship
from the third year onwards. The internship provides a practical problem-solving experience as
a bridge between coursework and professional life. A student can take the internship at a
company, located either in Kazakhstan or in a foreign country, for a total number of working
hours equal to 120 or more. As an alternative, the internship can be taken either in one of the
research labs of Nazarbayev University, or at a research lab of a foreign university, for total
number of hours equal to 120 or more. In all cases, the internship will be supervised by a faculty
member of the Department of Robotics and Mechatronics.

This course introduces the students to the state-of-the-art analytical tools and methods used for
machine learning. Topics include (semi) supervised learning, Bayesian decision theory,
parametric methods, multivariate methods, dimensionality reduction, design of machine
learning experiments, introduction to clustering, nonparametric methods, decision trees, linear
discrimination and kernel based methods. The course also contains an integrated final project
that gives students hands on experience with practical machine learning algorithms and express
those algorithms as computer implementations. MATLAB and C++ and related machine
learning libraries and databases will be used extensively.

This course is about the emerging field of Human-Robot Interaction (HRI). This
multidisciplinary research area draws from Robotics, Artificial Intelligence, Human-Computer
Interaction, Interaction Design, Cognitive Psychology and other fields to enable robots to
successfully interact with humans. This course is a combination of lectures, discussions,
assignments, readings and hands-on workshops on a wide range of topics such as social signal
processing, multi-modal communication, natural language interaction, robot-assisted therapy,
human perception tools and technologies, smart environments, interaction design for robots,
and ethics. During this course, we will discuss how cognitive, social and affective issues apply to interaction design, and how to gather, analyze, and present data for interaction design. In
addition, the interaction of HRI techniques are discussed and practiced in a special term project
resulting in the implementation of a complete human-robot interaction system. This project may
be developed using a robotic platform from NU robotics labs.