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Engineering    2015, Vol. 1 Issue (1) : 79 -84
Research |
Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints
Kun Li1,Max Q.-H. Meng2,()
1. California Institute of Technology, Pasadena, CA 91125, USA
2. The Chinese University of Hong Kong, Hong Kong, China

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.

Keywords personalized robot      habit learning      behavioral footprints     
Corresponding Authors: Max Q.-H. Meng   
Just Accepted Date: 31 March 2015   Issue Date: 03 July 2015
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Kun Li,Max Q.-H. Meng. Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints[J]. Engineering, 2015, 1(1): 79 -84 .
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