A good robot joke about task strategies

Ben: How many robots does it take to screw in a light bulb?
John: No clue.
Ben: Three! One to hold the bulb, and two to turn the ladder!
John: Whatever.

Any robot reasoning or learning approach that doesn't try to improve task strategies will only perfect the execution of bad ways of doing things.

Making Robots Smarter

Chris Atkeson

Robotics Institute, Carnegie Mellon University
Updated March 15, 2019

A recent NSF proposal.

A research plan of what I expect to find working with the Keva kit "Contraptions".

A new NSF proposal focusing on the vision and language part of this project.

Robot Reasoning: Using Abstraction To Find Better Task Strategies

I see work on reasoning with abstractions about task strategies as the most important work we can be doing right now in robotics. Some thoughts on abstraction and thinking about task strategies, and some slides.

Temporal decomposition and abstraction

Akihiko Yamaguchi has led work on how to decompose and abstract complex learning problems. (for example, "Differential dynamic programming for graph-structured dynamical systems: Generalization of pouring behavior with different skills", A. Yamaguchi and C.G. Atkeson, Humanoids 2016). More work in this vein.

Finding better task strategies

Here are some older case studies:

Swing leg retraction helps biped walking stability, M. Wisse, C. G. Atkeson, and D. K. Kloimwieder, 5th IEEE-RAS International Conference on Humanoid Robots, 295-300, Humanoids 2005.

"Open Loop Stable Control Strategies for Robot Juggling", Schaal, S. and C. G. Atkeson, In: IEEE International Conference on Robotics and Automation, Vol.3, pp.913-918, Atlanta, Georgia, 1993.
A look at humans doing the task: "One-handed Juggling: Dynamical Approaches to a Rhythmic Movement Task", Schaal, S., D. Sternad and C. G. Atkeson, Journal of Motor Behavior, 28(2):165-183, 1996.


Cognitive Capture