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Proceedings Paper

Embodying a cognitive model in a mobile robot
Author(s): D. Paul Benjamin; Damian Lyons; Deryle Lonsdale
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Paper Abstract

The ADAPT project is a collaboration of researchers in robotics, linguistics and artificial intelligence at three universities to create a cognitive architecture specifically designed to be embodied in a mobile robot. There are major respects in which existing cognitive architectures are inadequate for robot cognition. In particular, they lack support for true concurrency and for active perception. ADAPT addresses these deficiencies by modeling the world as a network of concurrent schemas, and modeling perception as problem solving. Schemas are represented using the RS (Robot Schemas) language, and are activated by spreading activation. RS provides a powerful language for distributed control of concurrent processes. Also, The formal semantics of RS provides the basis for the semantics of ADAPT's use of natural language. We have implemented the RS language in Soar, a mature cognitive architecture originally developed at CMU and used at a number of universities and companies. Soar's subgoaling and learning capabilities enable ADAPT to manage the complexity of its environment and to learn new schemas from experience. We describe the issues faced in developing an embodied cognitive architecture, and our implementation choices.

Paper Details

Date Published: 2 October 2006
PDF: 14 pages
Proc. SPIE 6384, Intelligent Robots and Computer Vision XXIV: Algorithms, Techniques, and Active Vision, 638407 (2 October 2006); doi: 10.1117/12.686163
Show Author Affiliations
D. Paul Benjamin, Pace Univ. (United States)
Damian Lyons, Fordham Univ. (United States)
Deryle Lonsdale, Brigham Young Univ. (United States)

Published in SPIE Proceedings Vol. 6384:
Intelligent Robots and Computer Vision XXIV: Algorithms, Techniques, and Active Vision
David P. Casasent; Ernest L. Hall; Juha Röning, Editor(s)

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