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B站：CLEAR_LAB

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1. What is this course about?

• Develop a solid foundation in robot modeling and control to conduct cutting edge research in robotics

Math : Linear Algebra, Optimization
Modeling: Advanced rigid body kinematics and dynamics(screw theory and spatial vectors)
Optimization: learn how to formulate robotic decision and control problem as tractable optimization problems
Control: Nonlinear control, optimal control, Model Predictive Control (Lyapunovfunc)

• Journal : TR-O, IJRR, ICRA, IROS

2. Tentative Schedule暂定时间表

1. Continuous time linear systems and Matrix Exponential
2. Advanced Kinematics and Dynamics
   2.1 Rigid body configuration and velocity
   2.2 Exponential coordinate of rigid body motion
   2.3 Kinematics of open chain
   2.4 Rigid body dynamics
   2.5 Multibody dynamics(Recursive Newton-Euler Algorithm, inverse and forward dynamics)
3. Basic Optimization
   3.1 Optimization problems and basic duality theory([数] 对偶理论; 二元论)
   3.2 Semi-definite Programming(SDP) and linear matrix inequalities
4. Nonlinear Stability and Stabilization
   4.1 Lyapunov stability theory
   4.2 Numerical construction of Lyapunov functions via semi-definite programming
   4.3 Control-Lyapunov Function for stabilization
5. Basic Robot Control
   5.1 Differential IK
   5.2 Robot Motion Control(Computed Torque Method Task-space Inverse Dynamics-TSID)
6. Optimal Control and Model Predictive Control
   6.1 Optimal control problem and dynamic programming
   6.2 Model Predictive Control for Linear Systems
   6.3 General MPC Theory(Closed-loop stability, recursive feasibility)