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Proceedings Paper

Task analysis of autonomous on-road driving
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Paper Abstract

The Real-time Control System (RCS) Methodology has evolved over a number of years as a technique to capture task knowledge and organize it into a framework conducive to implementation in computer control systems. The fundamental premise of this methodology is that the present state of the task activities sets the context that identifies the requirements for all of the support processing. In particular, the task context at any time determines what is to be sensed in the world, what world model states are to be evaluated, which situations are to be analyzed, what plans should be invoked, and which behavior generation knowledge is to be accessed. This methodology concentrates on the task behaviors explored through scenario examples to define a task decomposition tree that clearly represents the branching of tasks into layers of simpler and simpler subtask activities. There is a named branching condition/situation identified for every fork of this task tree. These become the input conditions of the if-then rules of the knowledge set that define how the task is to respond to input state changes. Detailed analysis of each branching condition/situation is used to identify antecedent world states and these, in turn, are further analyzed to identify all of the entities, objects, and attributes that have to be sensed to determine if any of these world states exist. This paper explores the use of this 4D/RCS methodology in some detail for the particular task of autonomous on-road driving, which work was funded under the Defense Advanced Research Project Agency (DARPA) Mobile Autonomous Robot Software (MARS) effort (Doug Gage, Program Manager).

Paper Details

Date Published: 29 December 2004
PDF: 12 pages
Proc. SPIE 5609, Mobile Robots XVII, (29 December 2004); doi: 10.1117/12.580233
Show Author Affiliations
Anthony J. Barbera, National Institute of Standards and Technology (United States)
John A. Horst, National Institute of Standards and Technology (United States)
Craig I. Schlenoff, National Institute of Standards and Technology (United States)
David W. Aha, Naval Research Lab. (United States)

Published in SPIE Proceedings Vol. 5609:
Mobile Robots XVII
Douglas W. Gage, Editor(s)

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