The elements and devices of the robotics field are studied, and basic techniques are established through the basic measurement and instrumentation.

Basic knowledge is studied for mobile robots through various experiments.

This laboratory deals with the signals of the sensor such as the thermal sensors, the mechanical sensors, and the optical sensors using the instruments. The sensor interface circuits using A/D converter, D/A converter, and microprocessor is designed and experimented.

Experiments of control system theories. Analysis and design of control system using frequency domain techniques.

This courses provides an environnment where the variety of disciplines combine to solve a complex design problem. Sophistication of the project encourages collaboration and team effort among students, serious design consultation with the instructor, and other elements of a working engineering environment.

This course trains one's ability to observe in everyday life and proceeds a project to apply it.

Mechanics is the branch of physics concerned with the behavior of physical bodies when subjected to forces or displacements, and the subsequent effects of the bodies on their environment. Students learn the basic physics and mathematical background for mechanics and robotics.

The design and analysis of digital system. Logic design for digital system. Application to computer hardware design and microprocessor control.

Basic concepts about electro-magnetic field theory on which major field of current electric and electronic technologies.

Study on basic circuit theory with physics and calculus, analysis of circuit theory by frequently domain with phaser, and application to network analysis and synthesis by transfer function.

Students learn about forward and inverse kinematics of robots. Various combination of actuators and links are studied. And the forward/inverse kinematics of robot are studied.

Provided by Chinese instructors, this lecture consists of two parts. In the first half of the lecture, students engage in learning economic terminologies and basic concepts of economics through reading news articles about business and economics. The second half of the lecture focuses on improving students’ writing skills (e.g., personal statement, resume, business contracts, etc).

Continuous time systems, Fourier series, Fourier transform, Laplace transform, discrete-time system, Fourier analysis of discrete-time systems, Z-transform, discrete Fourier transform, and design of analog and digital filters.

Computer systems and architectures. Application of microprogrammable computer to digital control.

This course develops logical thinking by imagining robots and criticizing them.

Modeling, and analysis and design methods for feedback control systems both in the time domain and the frequency domain.

The objectives of this course is 1. to introduce basic and entry level theories and terminologies and 2. to familiarize the students with the concepts and techniques in design and analysis of robot manipulator and its application.

This course covers transmission of digital data, transmission media, error detection and correction, data link control. OSI reference model and its layered architecture will be discussed in detail.

This course covers the basic principles of actuators and their control methods.

The microprocessor concepts, its instruction set, assembly-language programming, privilege states, exceptions, reset, input/output and interfacing.

This course deals with various robot manipulation control methods used in industrial fields and technical issues with control theory. Based on the understanding of mechatronics system and the kinematics of manipulators, core theoretical approaches and experimental methodologies required in robotics fields are discussed and presented.

Modeling, and analysis and design methods for feedback control systems both in the time domain and the frequency domain.

This course covers measurement techniques and the principles of the electronic instrument such as the oscilloscopes, the multi-function meter, and the spectrum analyzer.

Students learn network structure, protocol, data transmission, and flow control, network maintenance and network security.

Learn about the basic principles and algorithms of machine learning techniques and methods for generating machine learning models according to real-world problems. In addition, it cultivates design ability to build with actual implementation and system.

Basic design principles of linear amplifiers, compensators, regulators, oscillators, etc., and applications of analog computer circuits interface.

This course deals with the theoretical knowledge and implementation methods of various algorithms. Students learn how to analyze the complexity of algorithms, sorting algorithms, search algorithms, dynamic programming, and learn how to navigate robots. Because the exercises and assignments in this subject use the Python language, you must have a basic knowledge of the Python language to take this course.

Students learn about how to prepare robot games.

Students learn about how to make winning strategy of robot games.

In this class, the fundamentals of embedded system hardware and firmware design will be explored. Issuse such as embedded processor selection, hardware/firmware partitioning, circuit design, circuit layout, circuit debugging, development tools, firmware architecture, firmware design, and firmware debugging will be discussed. The course will deal with various issues on RTOS including porting and developing based on RTOS Kernel. The coures will culminate with a significant final project which will extend the base microcontroller board completed earlier in the course.

This lecture studies a method to control robots by developing application on smart phones. We first practice th basic grammar of Android, and develop an application to control a robot by using given APIs. By carryig out a project, we practically implement the learned knowledge.

In this course, various intelligent methods, such as a decision tree, an artificial neural network, and learning theories, for intelligent robots are studied, and a term-project is carried out to implement the methods.

This course is to study basic theories and applications of deep learning that have been making high achievements in various fields in recent years. In addition to the basic principles of machine learning, it deals with learning principles of neural network models and models related to image, language, and voice recognition problems applied to various fields and implement them through programming. This course requires a basic background in calculus, linear algebra, probability statistics, and Python programming, and a final project assignment will be given as an important evaluation element.

This course deals with various robotic applications and technical issues. With these, core theoretical approaches and experimental methodologies required in robotics fields are discussed.

Designing and manufacturing methods of robots is presented by several case studies. Line tracer and 4DOF SCARA type robot design will be studied. For the case of SCARA robot, disassembling and assembling activities will be conducted for understanding the robot structure.

Students learn how to design speech recognition, image processing, or embeded system with DSP, microprocessor, linux, and colour CCD camera.

Students learn about the forward and inverse kinematics of robots, and how to implement the theories to the robotic systems. The basic design approach for robot system (including the various combinations of actuators and links) is studied.

Students learn about how to develop robots. Various robot development theme about actuator selection, mechanism design, control system design are studied.