Learning to Scaffold the Development of Robotic Manipulation Skills

Understand

Learning contact-rich, robotic manipulation skills is a challenging problem due to the high-dimensionality of the state and action space as well as uncertainty from noisy sensors and inaccurate motor control.

• To combat these factors and achieve more robust manipulation, humans actively exploit contact constraints in the environment.
• By adopting a similar strategy, robots can also achieve more robust manipulation.
• In this paper, we enable a robot to autonomously modify its environment and thereby discover how to ease manipulation skill learning.