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Proceedings Paper

Intelligent behavior generator for autonomous mobile robots using planning-based AI decision making and supervisory control logic
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Paper Abstract

In earlier research the Center for Self-Organizing and Intelligent Systems (CSOIS) at Utah State University (USU) have been funded by the US Army Tank-Automotive and Armaments Command's (TACOM) Intelligent Mobility Program to develop and demonstrate enhanced mobility concepts for unmanned ground vehicles (UGVs). One among the several out growths of this work has been the development of a grammar-based approach to intelligent behavior generation for commanding autonomous robotic vehicles. In this paper we describe the use of this grammar for enabling autonomous behaviors. A supervisory task controller (STC) sequences high-level action commands (taken from the grammar) to be executed by the robot. It takes as input a set of goals and a partial (static) map of the environment and produces, from the grammar, a flexible script (or sequence) of the high-level commands that are to be executed by the robot. The sequence is derived by a planning function that uses a graph-based heuristic search (A* -algorithm). Each action command has specific exit conditions that are evaluated by the STC following each task completion or interruption (in the case of disturbances or new operator requests). Depending on the system's state at task completion or interruption (including updated environmental and robot sensor information), the STC invokes a reactive response. This can include sequencing the pending tasks or initiating a re-planning event, if necessary. Though applicable to a wide variety of autonomous robots, an application of this approach is demonstrated via simulations of ODIS, an omni-directional inspection system developed for security applications.

Paper Details

Date Published: 17 July 2002
PDF: 17 pages
Proc. SPIE 4715, Unmanned Ground Vehicle Technology IV, (17 July 2002); doi: 10.1117/12.474447
Show Author Affiliations
Hitesh K Shah, Utah State Univ. (United States)
Vikas Bahl, Utah State Univ. (United States)
Jason Martin, Utah State Univ. (United States)
Nicholas S. Flann, Utah State Univ. (United States)
Kevin L. Moore, Utah State Univ. (United States)


Published in SPIE Proceedings Vol. 4715:
Unmanned Ground Vehicle Technology IV
Grant R. Gerhart; Chuck M. Shoemaker; Douglas W. Gage, Editor(s)

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