Robot Dynamics and Model-Based Control (MIT 6.8210, Lecture 1)
1:25:07Nonlinear Dynamics
1:12:48Dynamic Programming I
1:20:31Dynamic Programming II (MIT 6.8210, Lecture 4)
1:22:07Acrobots, Cart-poles, and Quadrotors I
1:21:24Dynamic Programming III (MIT 6.8210, Lecture 6)
1:19:46Lyapunov Analysis I (MIT 6.8210, Lecture 7)
1:20:44Computing Lyapunov Functions I (MIT 6.8210/6.832, Lecture 8)
1:23:56Computing Lyapunov Functions II
1:21:08Trajectory Optimization I
1:18:55Trajectory Optimization II
1:22:52Trajectory Stabilization
1:18:07Hybrid Trajectory Optimization
1:19:56Simple Models of Walking
1:09:54Planning + Control Through Contact
1:16:39Humanoid Robots
1:18:47Mixed-discrete (combinatorial) and continuous optimization
1:21:04Sampling-based (kinodynamic) motion planning
1:20:47Stochastic dynamics
1:18:38Stochastic Control
1:18:37Robust Control & Policy Search
1:17:06Output feedback
1:10:41Feedback Motion Planning (MIT 6.8210, Lecture 23)
1:18:06Imitation Learning, Foundation Models, and Course Wrap-up (MIT 6.8210, Lecture 24)
1:22:02Lyapunov Analysis I (MIT 6.8210, Lecture 7)
Toyota Professor of EECS, Aeronautics & Mechanical Engineering
This lecture introduces the foundational concepts of Lyapunov stability theory for analyzing nonlinear dynamical systems. It details the construction and properties of Lyapunov functions to determine system stability without explicitly solving differential equations.
Dynamic Programming III (MIT 6.8210, Lecture 6)
Next · Lecture 8Computing Lyapunov Functions I (MIT 6.8210/6.832, Lecture 8)