6.8210 Spring 2024 Lecture 17: Mixed-discrete (combinatorial) and continuous optimization

6.8210 Spring 2024 Lecture 24: Imitation learning / Foundation models / Course wrap-up

6.8210 Spring 2024 Lecture 23: Feedback motion planning

6.8210 Spring 2024 Lecture 22: Output feedback

6.8210 Spring 2024 Lecture 21: Robust Control & Policy Search

6.8210 Spring 2024 Lecture 20: Stochastic Control

6.8210 Spring 2024 Lecture 19: Stochastic dynamics

6.8210 Spring 2024 Lecture 18: Sampling-based (kinodynamic) motion planning

6.8210 Spring 2024 Lecture 17: Mixed-discrete (combinatorial) and continuous optimization

6.8210 Spring 2024 Lecture 16: Humanoid Robots

6.8210 Spring 2024 Lecture 15: Planning + Control Through Contact

6.8210 Spring 2024 Lecture 14: Hybrid Trajectory Optimization

6.8210 Spring 2024 Lecture 12: Trajectory Stabilization

6.8210 Spring 2024 Lecture 11: Trajectory Optimization II

6.8210 Spring 2024 Lecture 10: Trajectory Optimization I

6.8210 Spring 2024 Lecture 9: Computing Lyapunov Functions II

6.8210 Spring 2024 Lecture 8: Computing Lyapunov Functions I

6.8210 Spring 2024 Lecture 7: Lyapunov Analysis I

6.8210 Spring 2024 Lecture 4: Dynamic Programming II

6.8210 Spring 2024 Lecture 6: Dynamic Programming III

6.8210 Spring 2024 Lecture 1: Robot dynamics and model-based control

6.4210 Fall 2023 Lecture 23: Soft Manipulation and Tactile Sensing

6.4210 Fall 2023 Lecture 21: Multibody Parameter Estimation

6.4210 Fall 2023 Lecture 20: Reinforcement Learning Pt. 2

6.4210 Fall 2023 Lecture 19: Reinforcement Learning Pt. 1