DemoStream: Batched Task-and-Motion-Plan Optimization for Automated Learning from Demonstration

Learning from demonstration is an effective strategy for endowing robots with manipulation capabilities but requires training on datasets comprised of massive amounts of demonstrations. Existing demonstration collection approaches either require constant human involvement, for example, via teleoperation or are specialized for a single task.

From the abstract. Our summary is in progress.