Learning Perceptual Concepts by Bootstrapping from Human Queries

Understand

When robots operate in human environments, it's critical that humans can quickly teach them new concepts: object-centric properties of the environment that they care about (e.g.

• objects near, upright, etc).
• However, teaching a new perceptual concept from high-dimensional robot sensor data (e.g.
• point clouds) is demanding, requiring an unrealistic amount of human labels.