Joseph Modayil and Benjamin Kuipers.
Autonomous Development of a Grounded Object Ontology by a Learning Robot.
Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI-07)


We describe how a physical robot can learn about objects from its own autonomous experience in the continuous world. The robot identifies statistical regularities that allow it to represent a physical object with a cluster of sensations that violate a static world model, track that cluster over time, extract percepts from that cluster, form concepts from similar percepts, and learn reliable actions that can be applied to objects. We present a formalism for representing the ontology for objects and actions, a learning algorithm, and the results of an evaluation with a physical robot.