Making Virtual Pancakes — Acquiring and Analyzing Data of Everyday Manipulation Tasks through Interactive Physics-based Simulations

Teaching robots everyday tasks like making pancakes by instructions requires interfaces that can be intuitively operated by nonexperts. By performing manipulation tasks in a virtual environment using a data glove task-related information of the demonstrated actions can directly be accessed and extracted from the simulator. We translate low-level data structures of these simulations into meaningful first-order representations, called timelines, whereby we are able to select data segments and analyze them at an abstract level. Hence, the proposed system is a powerful tool for acquiring examples of manipulation actions and for analyzing them whereby robots can be informed how to perform a task.