Abstract：In order to improve the human-machine interaction performance of a home service robot and to deal with the drawback of neglecting user emotion during service recognition, a user emotion based autonomous service cognition method and a personalized service selection strategy for robot are presented. Firstly, an emotion-space-time ontology model is built based on the ontology technology of intelligent space and the information of user emotion and space-time, to eliminate the heterogeneity of information in intelligent space. Secondly, the emotion-space-time rule base is encoded and then used to train BP (backpropagation) neural network reasoner. The real-time updated information in intelligent space and the trained neural network are matched to automatically generate the robot services. The autonomous cognition of user emotion based robot service tasks is realized. Finally, the user emotion is taken as a reward feedback signal to dynamically adjust the user preference of each subclass service, and the personalized service selection is achieved. The simulation result shows that a robot based on the proposed method can autonomously achieve the user emotion based service recognition and provide a personalized service according to the variation of user preference. The proposed method effectively improves the intelligence and flexibility of the home service robot and enhances user experience.
 Feng S Y, Whitman E, Xinjilefu X, et al. Optimization based full body control for the atlas robot[C]//IEEE-RAS International Conference on Humanoid Robots. Piscataway, USA:IEEE, 2014:120-127.
 Kuindersma S, Deits R, Fallon M, et al. Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot[J]. Autonomous Robots, 2016, 40(3):429-455.
 Idris I, Salam M S H. Emotion detection with hybrid voice quality and prosodic features using neural network[C]//4th World Congress on Information and Communication Technologies. Piscataway, USA:IEEE, 2014:205-210.
 Diop M, Ong L Y, Lim T S, et al. A computer vision-aided motion sensing algorithm for mobile robot's indoor navigation[C]//IEEE International Workshop on Advanced Motion Control. Piscataway, USA:IEEE, 2016:400-405.
 褚伟杰,张荣,张伟,等.面向健康感知的情境建模方法研究[J].中国科技论文,2016,11(2):208-213.Chu W J, Zhang R, Zhang W, et al. A health monitoring context model of senior living[J]. China Sciencepaper, 2016, 11(2):208-213.
 秦伟俊.基于本体的智能空间情境信息模型研究[D].北京:清华大学,2005.Qin J W. Ontology-based context model smart space[D]. Beijing:Tsinghua University, 2005.
 Lim Y M. Detecting and modelling stress levels in e-learning environment users[D]. Leicester, UK:De Montfort University, 2017.
 Tivatansakul S, Ohkura M. Emotion recognition using ECG signals with local pattern description methods[J]. International Journal of Affective Engineering, 2016, 15(2):51-61.
 张腾宇,张静莎,单新颖,等.一种基于用户情绪及意图识别的机器人人机交互方法,中国:CN105082150 A[P].2015-11-25.Zhang T Y, Zhang J S, Shan X Y, et al. A robot human-computer interaction method based on user's emotion and intention recognition, China:CN105082150A[P]. 2015-11-25.
 Nasoz F, Lisetti C L. MAUI avatars:Mirroring the user's sensed emotions via expressive multi-ethnic facial avatars[J]. Journal of Visual Languages & Computing, 2006, 17(5):430-444.
 韩晶,解仑,刘欣,等.基于Gross认知重评的机器人认知情感交互模型[J].东南大学学报:自然科学版,2015,45(2):270-274.Han J, Xie L, Liu X, et al. Cognitive emotion interaction model of robot based on Gross cognitive reappraisal[J]. Journal of Southeast University:Natural Science Edition, 2015, 45(2):270-274.
 路飞,田国会,李擎.智能空间环境下基于本体的机器人服务自主认知及规划[J].机器人,2017,39(4):423-430.Lu F, Tian G H, Li Q. Autonomous cognition and planning of robot service based on ontology in intelligent space environment[J]. Robot, 2017, 39(4):423-430.
 周志华.机器学习[M].北京:清华大学出版社,2016.Zhou Z H. Machine learning[M]. Beijing:Tsinghua University Press, 2016.
 Pan J Z, Stoilos G, Stamou G, et al. f-SWRL:A fuzzy extension of SWRL[M]//Lecture Notes in Computer Science, vol.4090. Berlin, Germany:Springer, 2006:28-46.
 Lesiuk T. The effect of preferred music listening on stress levels of air traffic controllers[J]. Arts in Psychotherapy, 2008, 35(1):1-10.
 路飞,田国会,刘国良,等.智能空间下基于WIFI指纹定位与粒子滤波的服务机器人复合全局定位系统设计[J].机器人,2016,38(2):178-184.Lu F, Tian G H, Liu G L, et al. A composed global localization system for service robot in intelligent space based on particle filter algorithm and WIFI fingerprint localization[J]. Robot, 2016, 38(2):178-184.