Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints

• Main Authors: Kun Li, Max Q.-H. Meng
• Format: Article
• Language: English
• Published: Elsevier 2015-03-01
• Series: Engineering
• Subjects: personalized robot; habit learning; behavioral footprints
• Online Access: http://www.sciencedirect.com/science/article/pii/S2095809916300480

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.