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Tuesday, 27 August 2013

6.832 - Underactuated Robotics - MIT Lecture Notes

Instructor(s) - Prof. Russell Tedrake

MIT Course Number - 6.832

Level - Graduate

Robots today move far too conservatively, using control systems that attempt to maintain full control authority at all times. Humans and animals move much more aggressively by routinely executing motions which involve a loss of instantaneous control authority. Controlling nonlinear systems without complete control authority requires methods that can reason about and exploit the natural dynamics of our machines. This course discusses nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on machine learning methods.

Front Title page, table of contents, and preface (PDF)
1 Fully actuated vs. underactuated systems (PDF)
I. Nonlinear dynamics and control
2 The simple pendulum (PDF)
3 The acrobot and cart-pole (PDF)
4 Manipulation
5 Walking (PDF)
6 Running
7 Flight
8 Model systems with stochasticity
II. Optimal control and motion planning
9 Dynamic programming (PDF)
10 Analytical optimal control with the Hamilton-Jacobi-Bellman sufficiency theorem (PDF)
11 Analytical optimal control with Pontryagin's minimum principle
12 Trajectory optimization (PDF)
13 Feasible motion planning
14 Global policies from local policies
15 Stochastic optimal control
16 Model-free value methods
17 Model-free policy search (PDF)
18 Actor-critic methods
IV. Applications and extensions
19 Learning case studies and course wrap-up
Appendix A. Robotics preliminaries (PDF)
B. Machine learning preliminaries
Back References (PDF)

Prof. Russell Tedrake, 6.832, Underactuated Robotics
(Massachusetts Institute of Technology: MIT OpenCouseWare), (Accessed August 27, 2013). 
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