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)
1:22:02Imitation Learning, Foundation Models, and Course Wrap-up (MIT 6.8210, Lecture 24)
This lecture provides an introduction to imitation learning paradigms and delves into the architectural and application principles of large foundation models, concluding with a comprehensive course wrap-up.