School of Engineering and Digital Sciences
School of Engineering and Digital Sciences
School of Engineering and Digital Sciences
Робототехника саласындағы екі жылдық магистрлік бағдарлама студенттерді роботтехникасы саласында академиялық ортада, мемлекеттік саясатта және жеке бизнес салаларында табысты болуы мүмкін кәсіби инженерлер мен ғалымдар ретінде дайындауға арналған. Оқу бағдарламасы заманауи роботтехникасы жүйелерінің электр, механикалық және жасанды интеллект аспектілеріне қатысты жасалған. Түлектер жаһандық экономикада роботтандырылған жүйелерді әзірлеумен, сондай-ақ қызмет көрсету секторында робототехникасы таралуынаң пайда болуына байланысты сыни проблемаларды озық түсінуді әзірлейді. Бағдарламада ұсынылған элективті курстар: адам роботымен өзара іс-қимыл, мобильді робототехникасы, қозғалысты роботтандырылған жоспарлау, гуманоидттар, биоробот роботтехникасы және өнеркәсіптік роботтехникасы. Бағдарлама түлектері машина жасау, энергетика, химия, электроника және инновациялар секторын қоса алғанда, оның ішінде, Қазақстанның өсіп келе жатқан басым секторларында жұмыс істеу үшін дайындау ниеті бар. Бағдарлама түлектері зияткерлік жүйелердегі маңызды мәселелерді зерделеуге, Қазақстанда да сондай-ақ шетелдерде де технологиялар саласына елеулі үлес қосуға мүмкіндік беретін алдыңғы қатарлы ғылыми дағдыларға ие болады. Бағдарлама туралы қосымша ақпарат алу үшін кафедра меңгерушісі Атакан Варолмен хабарласуға болады (ahvarol@nu.edu.kz)
Total Number of Credits: 120 ECTS
Year 1: Fall Semester (Semester 1)
Year 1: Spring Semester (Semester 2)
Year 2: Fall Semester (Semester 3)
Year 2: Spring Semester (Semester 4)
Program Core Courses
This is an accelerated course in the evolution and design of imperative programming languages, and modern software development techniques. In the first part of the course, we will use the C language to review the fundamentals of programming, and progress on to the concepts of data types, encapsulation, and reusability. Algorithms and performance will also be topics of discussion. While investigating the advantages and drawbacks of C, we will motivate some of the key features of object-oriented languages, such as inheritance and polymorphism, as well as generics. We will then look at the Java language as an instance of the object-oriented paradigm, and discuss good object-oriented design principles. In the second part of the course, we will pull several of these threads together with a project.
This graduate level course combines the application of rhetorical analysis to stylistic conventions of writing in engineering, with a focus on clarity, conciseness, and coherence. Students will employ process writing to produce genre specific writing familiar to Engineers, including research reports scientific papers designed for specific audiences. This course also trains students to deliver effective and appealing professional and scientific presentations, with attention to best practices in the use of technical English and oral communication.
This course covers classical and advanced topics in robotics with particular emphasis on the dynamics and control of serial and parallel manipulators. Analysis of velocities, static forces, and kinematic singular configurations is carried out by means of differential kinematics, conventional Jacobian and screw-based Jacobian matrixes. Motion control is introduced in the joint and task space by using tracking and computed-torque techniques. Mobile and legged robotic systems with a high level of kinematic redundancy (e.g. humanoid robots, exoskeletons for tele-manipulation applications) are presented together with classical and state-of-the-art control algorithms targeted at solving the direct and inverse kinematic/dynamic problem, the spatial mapping, and the motion and path planning. Other topics covered in this course are: tendon-driven manipulators, synthesis and design of manipulators and mobile robots, biological mapping, the subsumption and other bioinspired control architectures.
The course aims to introduce the students to the state-of-the-art analytical tools and methods used for control system design. The course will start with the modeling of physical systems in the frequency and state space domains. The student will master analytical tools such as Bode plots, root locus diagrams, and phase plots. The second part of the course includes frequency domain-based control design (mainly focused on PID controllers) and then covers control system design in state space (linear quadratic regulators, servo-controllers, etc.). In the last part, students will review different advanced control algorithms such as model predictive control, adaptive control and soft computing based control.
This course aims to provide the students with a set of principles and skills that will be of paramount importance for conducting their research and disseminating the corresponding results. The course provides an overview of the scientific method and its application, project planning, working in teams, interaction with sources, and assessment of research results. Students are also taught the fundamental principles necessary for writing technical reports, scientific papers, and research proposals, and for preparing and delivering presentations: the focus of this part is on the connection between the employed research methods and the way in which the results are presented, rather than on the writing/presentation style in itself. Finally, students are exposed to a general introduction on moral reasoning, with subsequent focus on ethics in professional practice and research activity. The latter topic will focus on data management and intellectual property rights, and on the description of phenomena such as plagiarism and data fabrication.
The Hardware/Software Co-Design course introduces underlying scientific and engineering principles of embedded real-time systems for hardware data processing for computer science and robotics applications. 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. The course covers the software aspects of embedded processor architectures and elements of Linux operating systems for hardware control. Students can expect to learn how to apply off-shelf hardware components to design embedded sensor data processing systems that can be used in the Internet-of-Things, robotics and other applications. Topics covered include embedded processor architectures, concurrency principles, real-time principles (multi-tasking, process synchronization and scheduling), mechatronics design basics, sensor fusion and system state estimation (optional) algorithms, etc. Through a series of practical projects assignments using a state-of-the-art ARM based BeagleBone Black system-in-chip board and popular Robot Operating System (ROS) students will acquire skills in the design/implementation of core hardware control functionality using Linux based C/C++ programming tools and libraries.
The course aims to introduce the principles, models and applications of robot vision and perception. Some covered topics are image structure, projection, stereo vision, and the interpretation of visual motion. The practical applicability of the 2-D and 3-D vision algorithms to the robotic problems will also be discussed as case studies such as visual navigation of autonomous robots, robot hand-eye coordination and novel man-machine interfaces.
The course introduces students to the pedagogical structures and methods of teaching and learning, beginning with program structure and curricula requirements to the elucidation of learning objective and learning outcomes, the selection of student assessment methods, and the quality assurance life cycle processes.
The course requires students to select a topic, identify authoritative sources, generate an annotated bibliography, and compose a survey paper representing the current state-of-the-art in the selected topic area, and prepare a presentation based on the survey paper. The course includes a series of research presentations, presented by domain experts, to expose students to current research programs, and facilitate the thesis topic selection by students.
Students will apply educational and instructional methodologies in laboratory and practical sessions of their respective disciplines under the supervision of an experienced faculty member. They will summarize their observations and experience in a final report.
Students are led through the processes required to plan and initiate an independent research project that will make an original contribution to engineering knowledge. Students are required develop a research proposal based on literature analysis, and begin to execute the proposal.
The student will conduct independent work under the direction of a supervisor on a research problem in the student's designated area of research. The project will involve a substantial amount of work in one of the NU research laboratories. For students who aim to pursue a career in research, the thesis represents an excellent opportunity to develop the skills necessary to work within a research group. On the other hand, for students who wish to pursue their careers in industry, it constitutes an important introduction to practical research and development work.
Program Elective Courses
The Industrial Robotics course builds upon the Robot Manipulation and Mobility course offered in the first year of the master program and introduces underlining principles behind industrial robot-manipulators. The course covers the theoretical aspects of robot-manipulator kinematic and dynamic modeling and control system design. Students can expect to learn how to simulate the robots using MATLAB and dedicated robotics software and state-of-the-art industrial robot-manipulators. At the end of the course students are expected to know basic robotic technologies and be able to master modelling and advanced control aspects of robots used in industrial and research settings.
Brain-Machine Interface (BMI) systems are an emerging interdisciplinary field at the intersection of engineering, neuroscience, and medicine. It has brought promising new perspectives to human-machine interaction using brain activity. It provides users the capability to control applications such as assistive robotic technologies directly. This course is an introduction to the fundamentals of BMI technology and discusses its applications including both invasive and non-invasive BMI systems for controlling user interfaces, prosthetic arms, wheelchairs, and robotic exoskeletons. The course will also introduce other clinical applications of BMI technology for patients with locked-in syndrome and its utility in restoring movement and mobility in severely paralyzed persons. Also, other nonclinical use of BMI technology will be studied with hands-on experiments/projects for applications such as security, alertness monitoring, entertainment, gaming, and education or human augmentation.
This course aims to provide the state-of-the-art concepts relative to optimal control, in particular with application to robot motion planning. After introducing the definition and applications of the robot motion planning problem, a basic treatment of different motion planning algorithms, such as search-based planning, virtual potential fields, visibility maps and sampling-based methods, is provided. Then, the course focuses on optimal control and planning algorithms, which are based on numerical methods that can be deployed in practical robotics applications. The course covers both offline motion planning problems and online motion planning via model predictive control.