Department for Automation, Biocybernetics and Robotics





ACAT (Learning and execution of Action Categories)

Project duration: 2013 - 2016
Project area: Laboratory of Humanoid and Cognitive Robotics
Project type: Research
Project funding: EU
Project leader: Aleš Ude

Abstract

ACAT focuses on how artificial systems (robots) can understand and utilize information made for humans.

ACAT focuses on how artificial systems (robots) can understand and utilize information made for humans.

Project description

For many skills, humans have internalized and stored a lot of readily available information and our external textual or pictorial sources tacitly assume this and do not reiterate "the obvious". The goal of the ACAT project is to provide machines (robots) with this type of tacit information and to generate internal knowledge about individual task by way of creating and storing all required action information into so-called Action Categories.

To achieve this, ACAT generates a dynamic process memory by extraction and storage of action categories from large bodies of human compatible sources (text, images). Action categories are designed to include the actual action-encoding but also large amounts of context information ("background"). They are obtained by combining linguistic analysis with grounded exploration and action-simulation. To make them available to a wide variety of robots ACAT will structure and store the action categories in an action-specific knowledge base.

The ACAT system then uses action-categories to compile robot-executable plans. Execution benefits strongly from the rich context information present in the action-categories because this allows for generalization (for example replacement of objects in an action). It also permits us to specifically address ambiguity, incompleteness and uncertainty in planning. The ultimate purpose of ACAT is to equip the robot – on an ongoing basis – with abstract, functional knowledge, normally made for humans, about relations between actions and objects leading to a system which can act meaningfully.