Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints

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 d...

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Main Authors: Kun Li, Max Q.-H. Meng
Format: Article
Language:English
Published: Elsevier 2015-03-01
Series:Engineering
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2095809916300480
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author Kun Li
Max Q.-H. Meng
author_facet Kun Li
Max Q.-H. Meng
author_sort Kun Li
collection DOAJ
description 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.
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spelling doaj.art-270c148c34a34ec7b59d0292294e2feb2022-12-21T20:01:10ZengElsevierEngineering2095-80992015-03-011107908410.15302/J-ENG-2015024Personalizing a Service Robot by Learning Human Habits from Behavioral FootprintsKun Li0Max Q.-H. Meng1California Institute of Technology, Pasadena, CA 91125, USAThe Chinese University of Hong Kong, Hong Kong, ChinaFor 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.http://www.sciencedirect.com/science/article/pii/S2095809916300480personalized robothabit learningbehavioral footprints
spellingShingle Kun Li
Max Q.-H. Meng
Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints
Engineering
personalized robot
habit learning
behavioral footprints
title Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints
title_full Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints
title_fullStr Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints
title_full_unstemmed Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints
title_short Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints
title_sort personalizing a service robot by learning human habits from behavioral footprints
topic personalized robot
habit learning
behavioral footprints
url http://www.sciencedirect.com/science/article/pii/S2095809916300480
work_keys_str_mv AT kunli personalizingaservicerobotbylearninghumanhabitsfrombehavioralfootprints
AT maxqhmeng personalizingaservicerobotbylearninghumanhabitsfrombehavioralfootprints