Personalizing a Service Robot by Learning Human Habits from Behavioral Footprints

作     者：Kun Li Max Q.-H.Meng 

作者机构：California Institute of Technology The Chinese University of Hong Kong 

出 版 物：《Engineering》 (工程（英文）)

年 卷 期：2015年第1卷第1期

页      面：79-84页

核心收录：

学科分类：04[教育学] 0808[工学-电气工程] 08[工学] 0810[工学-信息与通信工程] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0401[教育学-教育学] 0817[工学-化学工程与技术] 080202[工学-机械电子工程] 0807[工学-动力工程及工程热物理] 0804[工学-仪器科学与技术] 0805[工学-材料科学与工程（可授工学、理学学位）] 0703[理学-化学] 0802[工学-机械工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 040110[教育学-教育技术学（可授教育学、理学学位）] 

基　　金：supported in part by Hong Kong RGC GRC (CUHK14205914 and CUHK415512) 

主　　题：personalized robot habit learning behavioralfootprints 

摘      要：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.