학생 연구실 A (제 10공학관 711호)
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세미나 및 모션 캡쳐(Motion Capture) 시스템
학생 연구실 B (제 10공학관 701호)
제작 및 보행 실험 공간
Spring, 2022
Numerical Methods (Undergraduate)
[week 1] Introduction & Simple Mathematical Models.
[week 2] Programming and Software(MATLAB: Free Fall, Single Pendulum, Double Pendulum, Cart).
[week 3] Approximations, Round-Off Errors and Taylor Series.
[week 4] Bracketing Methods.
[week 5] Open Methods.
[week 6] Roots of Polynomials.
[week 7] Lagrange Polynomial Interpolation, Cubic Spline Interpolation.
[week 8] Linear Algebraic Equations(Gauss Elimination, LU Decomposition).
[week 9] Numerical Differentiation(Finite Differences using Taylor Series).
[week 10] Numerical Integration.
Numerical Solution of Ordinary Differential Equations.
[week 11] PART I: Initial Value Problems, Boundary Value Problems, Forward/Backward Euler Method.
[week 12] PART II: Linearization for Implicit Methods, Runge-Kutta Methods.
Numerical Solution of Partial Differential Equations.
[week 13] PART I: Semi-Discretization, Accuracy via Modified Equation.
[week 14] PART II: Du-Fort-Frankel Method.
[week 15] Final Exam, MATLAB Exam.
Smart Control System (Undergraduate)
[week 1] Introduction & Homogeneous Coordinates.
Optimal Control.
[week 2] Linear Algebra, Numerical Solvers. Line search, Bracket Methods, Open Methods(Newton-Raphson).
[week 3] Convex Optimization (Linear regression).
[week 4] Least Squares, Linear Quadratic Program, Gradient Descent Method.([Book] Numerical Optimization.)
[week 5] Semi-Definite Program.
Path Planning & Trajectory Planning.
[week 6] Grid Maps.
[week 7] Visibility Graphs.
[week 8] A* Planning.
[week 9] Probabilistic Roadmaps.
[week 10] Rapid Random-exploring Tree Planning.
Advanced State Estimation.
[week 11] Sensors.
[week 12] Computer Vision/Simultaneously Localization and Mapping (SLAM).
[week 13] Inertial Measurement Unit, Force/Torque Sensor, Wheatstone Bridge, Digital Filters(ex Low pass filter).
[week 14] Estimator, Extended Kalman-Filter.
[week 15] Final Exam.
Modern Robotics (Graduate)
[week 1] Introduction & Rigid Body Motion Review.
[week 2] Kinematics Review.
[week 3] Lagrangian Formulation: Forward Dynamics.
[week 4] Lagrangian Formulation: Inverse Dynamics.
[week 5] Fully-actuated, Under-actuated Systems.
[week 6] Acrobots, Cart-Poles and Quadrotors (MATLAB Assignment, Pendulum).
[week 7] Limit Cycles (Simple Models of Legged Robots).
[week 8] Stability and Planning of Legged Robots.
[week 9] Midterm Exam. (Term Project Proposal: submit to Dr. Lee and get comments)
[week 10] Trajectory planning: Modern Robotics Chapter 9.
[week 11] Trajectory planning: Modern Robotics Chapter 9.
[week 12] Grid Maps.
[week 13] Visibility Graphs.
[week 14] A* Planning.
[week 15] Rapid Random-exploring Tree Planning.
[week 16] Term Project Presentation.
Modern Robotics, Kevin M. Lynch, Frank C. Park.
Introduction to Humanoid Robotics, Shuuji Kajita.
Fall, 2021
Control Engineering (Undergraduate)
[week 1] Introduction.
Engineering Mathematics (Undergraduate)
[week 1] Introduction.
Adventure Design (Undergraduate)
[week 1] Introduction.
Spring, 2021
Numerical Methods (Undergraduate)
[week 1] Introduction & Simple Mathematical Models.
[week 2] Programming and Software(MATLAB: Free Fall, Single Pendulum, Double Pendulum, Cart).
[week 3] Approximations, Round-Off Errors and Taylor Series.
[week 4] Bracketing Methods.
[week 5] Open Methods.
[week 6] Roots of Polynomials.
[week 7] Lagrange Polynomial Interpolation, Cubic Spline Interpolation.
[week 8] Linear Algebraic Equations(Gauss Elimination, LU Decomposition).
[week 9] Numerical Differentiation(Finite Differences using Taylor Series).
[week 10] Numerical Integration.
Numerical Solution of Ordinary Differential Equations.
[week 11] PART I: Initial Value Problems, Boundary Value Problems, Forward/Backward Euler Method.
[week 12] PART II: Linearization for Implicit Methods, Runge-Kutta Methods.
Numerical Solution of Partial Differential Equations.
[week 13] PART I: Semi-Discretization, Accuracy via Modified Equation.
[week 14] PART II: Du-Fort-Frankel Method.
[week 15] Final Exam, MATLAB Exam.
Smart Control System (Undergraduate)
[week 1] Introduction & Homogeneous Coordinates.
Optimal Control.
[week 2] Linear Algebra, Numerical Solvers. Line search, Bracket Methods, Open Methods(Newton-Raphson).
[week 3] Convex Optimization (Linear regression).
[week 4] Least Squares, Linear Quadratic Program, Gradient Descent Method.([Book] Numerical Optimization.)
[week 5] Semi-Definite Program.
Path Planning & Trajectory Planning.
[week 6] Grid Maps.
[week 7] Visibility Graphs.
[week 8] A* Planning.
[week 9] Probabilistic Roadmaps.
[week 10] Rapid Random-exploring Tree Planning.
Advanced State Estimation.
[week 11] Sensors.
[week 12] Computer Vision/Simultaneously Localization and Mapping (SLAM).
[week 13] Inertial Measurement Unit, Force/Torque Sensor, Wheatstone Bridge, Digital Filters(ex Low pass filter).
[week 14] Estimator, Extended Kalman-Filter.
[week 15] Final Exam.
Modern Robotics (Graduate)
[week 1] Introduction & Rigid Body Motion Review.
[week 2] Kinematics Review.
[week 3] Lagrangian Formulation: Forward Dynamics.
[week 4] Lagrangian Formulation: Inverse Dynamics.
[week 5] Fully-actuated, Under-actuated Systems.
[week 6] Acrobots, Cart-Poles and Quadrotors (MATLAB Assignment, Pendulum).
[week 7] Limit Cycles (Simple Models of Legged Robots).
[week 8] Stability and Planning of Legged Robots.
[week 9] Midterm Exam. (Term Project Proposal: submit to Dr. Lee and get comments)
[week 10] Trajectory planning: Modern Robotics Chapter 9.
[week 11] Trajectory planning: Modern Robotics Chapter 9.
[week 12] Grid Maps.
[week 13] Visibility Graphs.
[week 14] A* Planning.
[week 15] Rapid Random-exploring Tree Planning.
[week 16] Term Project Presentation.
Modern Robotics, Kevin M. Lynch, Frank C. Park.
Introduction to Humanoid Robotics, Shuuji Kajita.
Fall, 2020
Engineering Mathematics (Undergraduate)
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