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Underactuated Robotics

 03-Feb-2015
  •  22 Lessons
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536 Students
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. Topics include nonlinear dynamics of passive robots (walkers, swimmers, flyers), motion planning, partial feedback linearization, energy-shaping control, analytical optimal control, reinforcement learning/approximate optimal control, and the influence of mechanical design on control. Discussions include examples from biology and applications to legged locomotion, compliant manipulation, underwater robots, and flying machines. Acknowledgements Professor Tedrake would like to thank John Roberts for his help with the course and videotaping the lectures.

Syllabus

1st lesson

Lesson 1

  • Introduction
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2nd lesson

Lesson 2

  • The Simple Pendulum
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3rd lesson

Lesson 3

  • Optimal Control of the Double Integrator
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4th lesson

Lesson 4

  • Numerical Optimal Control (Dynamic Programming)
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5th lesson

Lesson 5

  • Acrobot and Cart-pole
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6th lesson

Lesson 6

  • Swing-up Control of Acrobot and Cart-pole Systems
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7th lesson

Lesson 7

  • Dynamic Programming (DP) and Policy Search
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8th lesson

Lesson 8

  • Trajectory Optimization
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9th lesson

Lesson 9

  • Trajectory Stabilization and Iterative Linear Quadratic Regulator
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10th lesson

Lesson 10

  • Walking
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11th lesson

Lesson 11

  • Running
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12th lesson

Lesson 12

  • Feasible Motion Planning
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13th lesson

Lesson 13

  • Global Policies from Local Policies
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14th lesson

Lesson 14

  • Introducing Stochastic Optimal Control
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15th lesson

Lesson 15

  • Stochastic Gradient Descent
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16th lesson

Lesson 16

  • Temporal Difference Learning
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17th lesson

Lesson 17

  • Temporal Difference Learning with Function Approximation
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18th lesson

Lesson 18

  • Policy Improvement
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19th lesson

Lesson 19

  • Actor-critic Methods
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20th lesson

Lesson 20

  • Case Studies in Computational Underactuated Control
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21st lesson

Exams

  • Exams
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22nd lesson

Projects

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I thoroughly enjoyed this course and hope to expand on my gained knowledge about building websites. The course was well presented, easy to follow and engaging. The interactive examples make the course material easier to grasp. I definitely recommend this course to anyone who wishes to learn about HTML or CSS.

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