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Proceedings Paper

Overview of the dynamic predictive architecture for robotic assistants
Author(s): Charles E. Martin; Robert James Firby
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Paper Abstract

A robotic assistant for extra-vehicular activity in space must deal with a complex, constantly changing environment. Classical planning architectures are ineffective for such tasks, but modern reactive systems are a plausible alternative. In addition, the robot must be capable of effective real-time response to the needs of human astronauts. Writing and debugging robot programs will not be possible under actual work conditions; astronaut-assistant dialogues must, therefore, take place in natural language. Unfortunately, the generally nonrepresentationalist nature of reactive systems make generative natural language interfaces impossible. In this paper, we present an overview of the Dynamic Predictive Memory architecture for robotic assistants. This architecture is an extension of the Direct Memory Access Parsing (DMAP) model of language understanding, in which the data structures and algorithms associated with the reactive action package (RAP) execution system are represented in the uniform memory format of the system. This allows natural language reference to take place coincident with the reactive execution of plans. The result is a reactive system which human users can interact with in natural language.

Paper Details

Date Published: 1 November 1992
PDF: 7 pages
Proc. SPIE 1829, Cooperative Intelligent Robotics in Space III, (1 November 1992); doi: 10.1117/12.131693
Show Author Affiliations
Charles E. Martin, Univ. of Chicago (United States)
Robert James Firby, Univ. of Chicago (United States)


Published in SPIE Proceedings Vol. 1829:
Cooperative Intelligent Robotics in Space III
Jon D. Erickson, Editor(s)

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