Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints. (March 2015)

• Record Type: Journal Article
• Authors: Li, Kun; Meng, Max Q.-H.
• Is Part Of: Engineering. Volume 1:Number 1(2015)
• Page Start: 079
• Page End: 084
• Publication Date: 2015-03
• Subjects: personalized robot -- habit learning -- behavioral footprints; Engineering -- Periodicals; Engineering -- China -- Periodicals; 620.005
• DOI: 10.15302/J-ENG-2015024
• Languages: English
• ISSNs: 2095-8099

Abstract

ABSTRACT: For a domestic personal robot, personalized services are as important as predesigned tasks, because the robot needs to adjust the home state based on the operator's habits. An operator's habits are composed of cues, behaviors, and rewards. This article introduces behavioral footprints to describe the operator's behaviors in a house, and applies the inverse reinforcement learning technique to extract the operator's habits, represented by a reward function. We implemented the proposed approach with a mobile robot on indoor temperature adjustment, and compared this approach with a baseline method that recorded all the cues and behaviors of the operator. The result shows that the proposed approach allows the robot to reveal the operator's habits accurately and adjust the environment state accordingly.