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From Deliberative to Routine Behaviors: a Cognitively-Inspired Action Selection Mechanism for Routine Behavior Capture

By Sonia Chernova and Ronald C. Arkin

Abstract

Long-term human-robot interaction, especially in the case of humanoid robots, requires an adaptable and varied behavior base. In this work we present a method for capturing, or learning, sequential tasks by transferring serial behavior execution from deliberative to routine control. The incorporation of this approach leads to natural development of complex and varied behaviors, with lower demands for planning, coordination and resources. We demonstrate how this process can be performed autonomously as part of the normal function of the robot, without the need for an explicit learning stage or user guidance. The complete implementation of this algorithm on the Sony QRIO humanoid robot is described

Topics: Autonomous behavior, Autonomous humanoid robot, Deliberative system, Human-robot interaction, Robotics
Publisher: Georgia Institute of Technology
Year: 2006
OAI identifier: oai:smartech.gatech.edu:1853/20537
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