ML/RL methods are often viewed as a magical black box, and while that's not true, learned policies are nonetheless a valuable tool that can work in conjunction with the underlying physics of the robot. In this video, Agility CTO Jonathan Hurst wearing his professor hat at Oregon State University presents some recent student work on using learned policies as a control method for highly dynamic legged robots.

This presentation was recorded on Oct. 20, 2020 as part of the of University of Washington Electrical & Computer Engineering seminar series:    • UW ECE Research Colloquium, October 2...