Finding and exploiting goal opportunities in real-time during plan execution

Authors:
Paul Schermerhorn;J. Benton;Matthias Scheutz;Kartik Talamadupula;Subbarao Kambhampati
Affiliations:
Cognitive Science Program Indiana University Bloomington, IN;Department of Computer Science and Engineering Arizona State University Tempe, AZ;Cognitive Science Program Indiana University Bloomington, IN;Department of Computer Science and Engineering Arizona State University Tempe, AZ;Department of Computer Science and Engineering Arizona State University Tempe, AZ
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

Autonomous robots that operate in real-world domains face multiple challenges that make planning and goal selection difficult. Not only must planning and execution occur in real time, newly acquired knowledge can invalidate previous plans, and goals and their utilities can change during plan execution. However, these events can also provide opportunities, if the architecture is designed to react appropriately.We present here an architecture that integrates the SapaReplan planner with the DIARC robot architecture, allowing the architecture to react dynamically to changes in the robot's goal structures.