model predictive control

Pick anything below and it plays in the bar at the foot of the window — and keeps playing while you go on browsing the directory.

1. 1▶Lecture 15 - Optimization and Learning for Robot Control - Implementing MPC on a manipulatorOptimization and Learning for Robot Control 2025Notes
   +Watch later
2. 2▶Lecture 14 - Optimization and Learning for Robot Control - LAB Collision avoidanceOptimization and Learning for Robot Control 2025Notes
   +Watch later
3. 3▶Lecture 13 - Optimization and Learning for Robot Control - Model Predictive Control (part 2)Optimization and Learning for Robot Control 2025Notes
   +Watch later
4. 4▶Lecture 12 - Optimization and Learning for Robot Control - LAB Trajectory OptimizationOptimization and Learning for Robot Control 2025Notes
   +Watch later
5. 5▶Lecture 11 - Optimization and Learning for Robot Control - Model Predictive Control (part 1)Optimization and Learning for Robot Control 2025Notes
   +Watch later
6. 6▶Lecture 10 - Optimization and Learning for Robot Control - Trajectory Optimization: Direct MethodsOptimization and Learning for Robot Control 2025Notes
   +Watch later
7. 7▶Lecture 9 - Optimization and Leaning for Robot Control - Intro to Numerical OptimizationOptimization and Learning for Robot Control 2025Notes
   +Watch later
8. 8▶Lecture 8 - Optimization and Learning for Robot Control - Optimal control introductionOptimization and Learning for Robot Control 2025Notes
   +Watch later
9. 9▶Lecture 7 - Optimization and Learning for Robot Control - Lab session on QP-based controlOptimization and Learning for Robot Control 2025Notes
   +Watch later
10. 10▶Lecture 6 - Learning and Optimization for Robot Control - QP-based motion control (part 2)Optimization and Learning for Robot Control 2025Notes
    +Watch later
11. 11▶Lecture 11, 2024: On-line training, neural networks, and other approximation architecturesReinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later
12. 12▶Lecture 4, 2024, POMDP, Systems with Changing Parameters, Adaptive Control, Model Predictive ControlReinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later
13. 13▶Lecture 13, 2021: An overview of the entire course. Discussion. ASU.Reinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later
14. 14▶Lecture 12, 2021: Aggregation methods and approximation in value space. ASU.Reinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later
15. 15▶Lecture 11, 2021: Linear programming, policy approximation, policy gradients. ASU.Reinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later
16. 16▶Lecture 10, 2021: Approximate policy iteration, Q-learning, parallel versions. ASU.Reinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later
17. 17▶Lecture 9, 2021: Infinite horizon theory and algorithms. ASU.Reinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later
18. 18▶Lecture 8, 2021: Neural networks, off-line training. ASU.Reinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later
19. 19▶Lecture 7, 2021: Constrained forms of rollout, discrete optimization, ASU.Reinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later
20. 20▶Lecture 6, 2021: Model Predictive Control, ASU.Reinforcement Learning Course at ASU, Spring, 2021Notes
    +Watch later