基于模仿学习的机器人演奏示教系统  

Robot Performance Teaching Demonstration System Based on Imitation Learning

作　　者：赵雨飞 靳聪[2] 刘潇雨 王洁 朱永贵[1] 李波[4] ZHAO Yufei;JIN Cong;LIU Xiaoyu;WANG Jie;ZHU Yonggui;LI Bo(School of Data Science and Media Intelligence,Communication University of China,Beijing 100000,China;School of Information and Communication Engineering,Communication University of China,Beijing 100000,China;China Philharmonic Orchestra,Beijing 100000,China;School of Electronics and Information,Northwestern Polytechnical University,Xi’an 710000,China)

机构地区：[1]中国传媒大学数据科学与智能媒体学院,北京100000 [2]中国传媒大学信息与通信工程学院,北京100000 [3]中国爱乐乐团,北京100000 [4]西北工业大学电子信息学院,西安710000

出　　处：《计算机科学》2024年第S02期981-985,共5页Computer Science

摘　　要：近年来,模仿学习被广泛应用于机器人领域,并展示出巨大的潜力。同时关注到智能系统在教育领域的应用越来越多样化,将机器人合理地应用到教学中可以提升教学效果,如果机器人可以教授一些专业技巧,如演奏乐器,可以为学生和人类老师都提供很大的便利。模仿学习特别适用于高度专业和技术性强的小提琴演奏,但在将专家演示引入动态运动原语(Dynamic Movement Primitive,DMP)的过程中,模糊性问题尤为突出,例如换弦角度的不确定性。传统的换弦角度测量方法如物理测量会有很大的误差且无法泛化,为了解决这一问题,提出了一种名为基于模糊和PCA的动态运动原语(Fuzzy Dynamic Movement Primitive for Teaching,T-FDMP)的新模型。该模型基于二型模糊模型和主成分分析(Principal Component Analysis,PCA)进行构建,使用主成分分析法(PCA)得到的特征变量(运弓角度)作为隶属度函数(琴弦角度)的输入进行学习,同时构建了一个专业级的音乐演奏行为数据库。仿生实验结果证明,所提出的T-FDMP模型能够以高精度控制机器人进行小提琴演奏,还为模仿学习在其他高度专业和技术性强的领域的应用提供了新的研究方向。In recent years,imitation learning has been widely applied in the field of robotics,demonstrating significant potential.At the same time,the application of intelligent systems in the field of education is becoming more and more diversified,and the reasonable application of robots in teaching can improve the teaching effect.If robots can instruct certain professional skills,such as playing musical instruments,it could offer significant convenience for both students and human teachers.Imitation learning is particularly suitable for highly specialized and technically demanding tasks,such as violin performance.However,the introduction of expert demonstrations into the process of dynamic movement primitives(DMP),especially regarding the ambiguity issues like uncertainties in string-changing angles,poses a prominent challenge.Traditional methods of measuring string-changing angles,such as physical measurements,exhibit substantial errors and lack generalization.To address this issue,a new model named fuzzy dynamic movement primitive for teaching(T-FDMP)is proposed.The model is constructed based on Type-2 fuzzy model and principal component analysis(PCA).It utilizes the features obtained from principal component analysis(PCA),specifically the bowing angle,as input for the membership functions(string angles)and simultaneously builds a professional-level music perfor-mance behavior database.Bionic experimental results demonstrate that our T-FDMP model can precisely control the robot for violin performance.Furthermore,it opens up new research directions for imitation learning in other highly specialized and technical domains.

关 键 词：模仿学习 机器人控制 二型模糊模型 智慧教育 动态运动原语 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]