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)
Abstract
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.
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