Graduate School Curriculum
- Designed based on industry demand surveys, consisting of core competencies, basic skills enhancement, advanced courses, research projects, and field projects (3 major fields: MI: Machine Intelligence, MC: Robot Behavior and Control, SI: System Integration).
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Doctoral program (36 credits): Minimum major requirements (21 credits = 3 credits for basic skills enhancement + 12 credits for advanced courses + 6 credits for research or field projects) + Major electives (15 credits) + Doctoral dissertation.
- Must acquire 36 or more credits, 9 credits per semester (Additional credits: 3 additional credits can be taken only for 2 semesters desired by the student out of 4 semesters of class period)
- Major subject requirements: 21 credits (minimum requirement for major). Basic skills enhancement: 3 credits, advanced courses: 12 credits (at least 3 credits from each of the three fields), research or field projects: 6 credits. In total, 21 credits are required.
- For robotics majors, students must first complete one course (3 credits) in the field of artificial intelligence to enhance their basic skills. Then, they must choose one of the three specific fields of MI, MC, or SI as their area of concentration, and take at least 2 advanced courses in that field and at least 1 course in each of the other two fields to satisfy the requirement of 12 credits for advanced courses.
- Intelligence Robot Projects 1 and 2 are required courses to be taken in order to apply practical education.
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Integrated Master's and Doctoral Program (51 credits): Minimum major requirements (30 credits = 3 credits for core competencies + 3 credits for basic skills enhancement + 18 credits for advanced courses + 6 credits for research or field projects) + Major electives (21 credits) + Doctoral dissertation.
- To obtain 51 or more credits, 9 credits per semester (Additional credits: 3 additional credits can be taken only for one semester desired by the student out of 8 semesters of class period)
- A minimum of 30 credits (required for major) must be taken, including 3 credits for core competency, 3 credits for basic education, 18 credits for advanced courses (at least 3 credits for each of the three majors), 6 credits for research and field projects, for a total of 30 required credits.
- As a robotics major, 3 credits for core competency and 3 credits for basic education must be completed first, followed by selecting one of the three major fields (MI: Machine Intelligence, MC: Robot Motion and Control, SI: System Integration) and taking at least 2 advanced courses in that field and at least 1 course in each of the other fields, for a total of 18 required credits.
- It is mandatory to take Intelligent Robot Project 1 and 2 for practical education.
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Master's Degree Program (24 credits): Minimum Major Requirements (15 credits = Core Competencies 3 credits + Advanced 9 credits + Research or Field Project 3 credits) + Major Electives (9 credits) + Master's Thesis
- Acquire 24 or more credits, 9 credits per semester
- Core Competencies of 3 credits, Advanced courses of 9 credits (3 credits in each of the three areas), and Research or Field Project of 3 credits are required.
- In order to equip students majoring in robotics with fundamental skills in mathematics, programming, and simulation, one core required course (3 credits) must be taken initially. Then, in the three areas of MI: Machine Intelligence, MC: Robot Motion and Control, and SI: System Integration, at least one advanced course in each area must be taken. To strengthen practical skills, completion of one of the two Intelligent Robot Projects, Project 1 or 2, is mandatory and should be completed for 3 credits.
[Intelligent Robotics Roadmap]
| Sections | Courses | ||
|---|---|---|---|
|
Core (3) |
Robot Mathematics and Simulations(3) |
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Corner Stone (3) |
Machine Learning(3) |
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Advanced Electives (9) |
MI: Machine Learning(3) vision, learning |
MC: Robotics: Operation and Control (3) RL, control, kinematics & dynamics |
SI: System Integration(3) HW, Smart Factory Logistics, Soft robot |
|
Theory of Computer Vision Theory(3) Computer Vision(3)/Robot Vision Introduction to SLAM(3) Advanced Reinforcement Learning(3) Pattern Recognition(3) Advanced Artificial Intelligence(3) Theories of Artificial Intelligence(3) Theory of Image Processing(3) Deep Neural Networks(3) Data-driven Robot Control(3) Parametric/Nonparametric Bayesian(3) Estimation and Decision Theory(3) principles of deep learning(3) |
Intelligent Robotics(3) Control Systems(3) Advanced Dynamics(3) Introduction to Human Machine Interaction(3) Non-Linear Control(3) Electric Vehicles: Dynamics and Control(3) Robotics(3) soft Robotics(3) IntelligentVehicle ControlSystem(3) Aerial Robotics(3)
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Rehabilitation Engineering Systems(3) Pioneering in Robotics(3) Introduction to Smart Factory(3) Advanced in Digital Twin and Advanced Treatment(3) Smart Product Design & Manufacturing(3) multiphysics mechanics & computational analysis(3) Rehabiliation Engineering(3) Prognostics and Health Management(3) Measurement Science(3) Advanced in Smart Manufacturing and Advanced Treatment(3) Design for Reliability(3) Mechanics of Elastoplasticity(3) Special Topics in Future Mobility Engineering(3) |
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Research and Field projects* (3) |
Intelligent Robotics Master's Thesis Research (3) Intelligent Robotics Doctoral Thesis Research 1 (3), Intelligent Robotics Doctoral Thesis Research 2 (3) Intelligent Robotics Project 1 (3), Intelligent Robotics Project 2 (3) Advanced Robot Technology Seminar 1(1), Advanced Robot Technology Seminar 2(1) Advanced Technolog Seminar (1, Mechanical Engineering C/L), Advanced Technolog Seminar (1, Mechanical Engineering C/L), Special Lectures on Robot Systems(1, Mechanical EngineeringC/L), Independent Research for University and Industry Collaboration in Smart FactoryⅠ(3, Industrial engineering C/L) Independent Research for University and Industry Collaboration in Smart FactoryⅡ (3, Industrial engineering C/L) |
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- The graduation requirements for the graduate school follow the university's regulation and the criteria for completing the curriculum. Completion of prerequisite courses, including research ethics, reserach safety management, and thesis writing is mandatory (online)
Research project: Ex) Conducting individual or group research projects funded by reserach foundatins.
Field Project: Ex) Performing an industry consortium project (participating research institute or company)
[Intelligent Robotics Curriculum]
| Order No. | Course Number | Course Name | Credit Hours | Section | Contents |
|---|---|---|---|---|---|
| 1 | ROB5014 | Robot Mathematics and Simulations | 3 | Core | robot math programming, probabilty, optimization, robot simulation using ROS, Isaac Sim, GPU, Cuda, AWS, Kinematics |
| 2 | ECE5984 | Foundations of Machine Learning | 3 | Corner Stone | classification. prediction, clustering |
| 3 | AIM5020 | Theory of Computer Vision | 3 | Advanced Elective | deep learning, CNN, segmentation, detection |
| 4 | ECE4249 | Computer Vision | 3 | Advanced Elective | Stereo, image processing, optical flow, tracking, recognition |
| 5 | ROB5002 | Introduction to SLAM | 3 | Advanced Elective | motion and tracking, graph SLAM, EKF SLAM, particle filter SLAM, VSLAM |
| 6 | AIM5010 | Advanced Reinforcement Learning | 3 | Advanced Elective | reinforcement learning |
| 7 | ECE5302 | Pattern Recognition | 3 | Advanced Elective | statistical pattern recognition, supervised learning, linear classification function, unsupervised learning, neural network pattern recognition |
| 8 | ECE5611 | Advanced Artificial Intelligence | 3 | Advanced Elective | logic and knowledge representation, inference, machine learning, data mining |
| 9 | AIM5001 | Theories of Artificial Intelligence | 3 | Advanced Elective | AI fundamentals, serach, logic, planning, knowledge representation methods |
| 10 | AIM5006 | Theory of Image Processing | 3 | Advanced Elective | digital image, quantization, 2D signal processing, 2D transformation, frequency analysis, filtering, color space transformation, color processing |
| 11 | AIM5004 | Deep Neural Networks | 3 | Advanced Elective | multilayer perceptron, CNN, RNN, transformer, generative model |
| 12 | EME5929 | Intelligent Robotics | 3 | Advanced Elective | robot kinematics, robot dynamics, robot control |
| 13 | EME5943 | Control Systems | 3 | Advanced Elective | linear systems, linear control, non-linear stabilty |
| 14 | EME5172 | Advanced Dynamics | 3 | Advanced Elective | 3D rigid body dynamics, energy dynamics |
| 15 | EME5940 | Introduction to Human Machine Interaction | 3 | Advanced Elective | human-machine interaction, robot safety, collision recognition |
| 16 | EME5703 | Non-Linear Control | 3 | Advanced Elective | nonlinear stability, perturbation, feedback linearrization, sliding mode control |
| 17 | EME5946 | Electric Vehicles: Dynamics and Control | 3 | Advanced Elective | EV trends, EV dynamics, hybrid vehicle modeling, key component modeling |
| 18 | ECE4237 | Robotics | 3 | Advanced Elective | matrix operations, kinematics, dynamic control, mobile robots, locomotion, perception and localization |
| 19 | ROB5004 | Rehabilitation Engineering | 3 | Advanced Elective | rehabilitation theory, force control, upper limb wearable robots, lower limb werable robots |
| 20 | EME5932 | Pioneering in Robotics | 3 | Advanced Electives | soft actuator, soft sensor, bio-inspired robot |
| 21 | ESM4050 | Introduction to Smart Factory | 3 | Advanced Electives | production systems, quality control, scheduling, process simulation, introduction to industrial AI |
| 22 | ESM5220 | Advanced in Digital Twin and Advanced Treatment | 3 | Advanced Electives | overview of digital twin, design and experiment of digital twin |
| 23 | ESM5219 | Smart Product Design & Manufacturing | 3 | Advanced Electives | smart design, optimization, process overview, smart factory, strategic planning |
| 24 | IFT5008 | Multiphysics Mechanics & Computational Analysis | 3 | Advanced Electives | electromagnetic, mechinal and thermal design theory, electric vehicle motor design, battery design, physics-inspired infromation processing neural networks |
| 25 | ESM5015 | Seminar on Reliability Engineering | 3 | Advanced Electives | reliability statistics, failure modes, life cycle conditions, process control, failure case analysis and root cause identification |
| 26 | ESM5212 | Prognostics and Health Management | 3 | Advanced Electives | maintainability management, reliability, availability, data collection, feature extraction, data-driven methodologies |
| 27 | ECE5976 | Measurement Science | 3 | Advanced Electives | measurement model design, error measurement and uncertainty, measurement theory |
| 28 | ROB5101 | Intelligent Robotics Master's Thesis Research 1 | 3 | Research and field projects | Research Study |
| 29 | ROB5102 | Intelligent Robotics Master's Thesis Research 2 | 3 | Research and field projects | Research Study |
| 30 | ROB6101 | Intelligent Robotics Doctoral Thesis Research 1 | 3 | Research and field projects | Research Study |
| 31 | ROB6102 | Intelligent Robotics Doctoral Thesis Research 2 | 3 | Research and field projects | Research Study |
| 32 | ROB5012 | Intelligent Robotics Project 1 | 3 | Research and field projects | Field Project |
| 33 | ROB5013 | Intelligent Robotics Project 2 | 3 | Research and field projects | Field Project |
| 34 | ROB5010 | Advanced Robot Technology Seminar 1 | 1 | Research and field projects | Invited technology seminar with distinguished guests from industry and academia |
| 35 | ROB5011 | Advanced Robot Technology Seminar 2 | 1 | Research and field projects | Invited technology seminar with distinguished guests from industry and academia |
| 36 | EME5902 | Entrepreneurship Project | 1 | Research and field projects | Invited technology seminar with distinguished guests from industry and academia |
| 37 | EME5903 | Advanced Technolog Seminar | 1 | Research and field projects | Invited technology seminar with distinguished guests from industry and academia |
| 38 | EME5904 | Advanced Technolog Seminar | 1 | Research and field projects | Invited technology seminar with distinguished guests from industry and academia |
| 39 | ESM5221 | Advanced in Smart Manufacturing and Advanced Treatment | 3 | Advanced Electives | Basic theory, application and practice, product design and development, PLM, advanced processing technology |
| 40 | ROB5005 | soft Robotics | 3 | Advanced Electives | Research, driving, sensing, control, system integration and industrial applications of recent developments in the field of soft robotics |
| 41 | ROB5006 | IntelligentVehicleControlSystem | 3 | Advanced Electives | Advanced cruise control, engine and electric motor control, anti-lock brake, traction control, active suspension, vehicle stability control |
| 42 | ROB5007 | Data-driven Robot Control | 3 | Advanced Electives | Robot control using data-based robot recognition, based on mathematical theory |
| 43 | ROB5008 | Parametric/Nonparametric Bayesian | 3 | Advanced Electives | Non-subsidiary Bayesian modeling for reasoning, data analysis, pattern recognition, and complex environmental recognition, dealing with inference techniques from a mathematical perspective |
| 44 | ROB5009 | Estimation and Decision Theory | 3 | Advanced Electives | Inference and decision making for robot position estimation, environmental awareness and control |
| 45 | ROB7001 | principles of deep learning | 3 | Advanced Electives | Structure, theory and application, generative model foundation, multimodal learning foundation |
| 46 | ESM4113 | Design for Reliability | 3 | Advanced Electives | Learn reliability concepts and principles, risk assessment, mitigation and management strategies |
| 47 | ROB5015 | Aerial Robotics | 3 | Advanced Electives | Learning and Operation Principles of Fixed Wing and Rotary Wing Flight Principles and Application Method |
| 48 | ESM4110 | Independent Research for University and Industry Collaboration in Smart FactoryⅠ | 3 | Individual research subjects | Participation in the industry-academic research project in the smart factory field Conducts and announces the convergence research related to solution development on the operation, design, and software |
| 49 | ESM5200 | Independent Research for University and Industry Collaboration in Smart FactoryⅡ | 3 | Individual research subjects | Participation in the industry-academic research project in the smart factory field Conducts and announces the convergence research related to solution development on the operation, design, and software |
| 50 | ESM5952 | Special Topics in Future Mobility Engineering | 3 | Advanced Electives | Design, modeling, control, sensing, AI-based intelligence technology learning of future mobile objects |
| 51 | EME5938 | Mechanics of Elastoplasticity | 3 | Advanced Electives | Understanding the anisotropicyield function, plastic potential, curing theory, and annejisosan under elastomeric deformation from the perspective of thermodynamic entropy and free energy |