Underactuated Robotics

Algorithms for Walking, Running, Swimming, Flying, and Manipulation
Spring 2021

Course Description

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 introduces nonlinear dynamics and control of underactuated mechanical systems, with an emphasis on computational methods. Topics include the nonlinear dynamics of robotic manipulators, applied optimal and robust control and motion planning. Discussions include examples from biology and applications to legged locomotion, compliant manipulation, underwater robots, and flying machines.

Each semester we will devote a number of lectures to taking a "deeper dive" into some new and exciting area. This spring, we will dive into learning models from data / model-based reinforcement learning.

Course Information

Note: The course staff is working to make the very best of the online format this Spring. We will explore interactive and flipped lectures. Recordings will be provided for students that cannot attend synchronously.

Class Time and Location

  • Tuesday and Thursday
  • From 2:30 to 4:00 pm EST
  • Zoom link is available on Piazza
  • See class schedule for complete details

Office Hours

  • Dongchan Lee (TA): Monday 2-3 pm EST
  • AJ Miller (TA): Wednesday 12-1 pm EST
  • Eric Chen (TA): Friday 3-4 pm EST

Useful Links


  • Basic linear algebra and differential equations
  • Coding assignments will be in Python
  • Some backgound material can be found here
  • See the FAQs if you have any questions about prerequisites

Grading Policy

  • Assignments: 40%
  • Midterm: 30%
  • Final Project: 30%
  • No final exam