Dynamic Movement Primitives Based Robot Skills Learning  

作　　者：Ling-Huan Kong Wei He Wen-Shi Chen Hui Zhang Yao-Nan Wang 

机构地区：[1]School of Intelligence Science and Technology,University of Science and Technology Beijing,Beijing 100083,China [2]Institute of Artificial Intelligence,University of Science and Technology Beijing,Beijing 100083,China [3]School of Robotics and the National Engineering Laboratory of Robot Visual Perception and Control Technology,Hunan University,Changsha 410082,China

出　　处：《Machine Intelligence Research》2023年第3期396-407,共12页机器智能研究（英文版）

基　　金：National Natural Science Foundation of China(Nos.62225304,92148204 and 62061160371);National Key Research and Development Program of China(Nos.2021ZD0114503 and 2019YFB1703600);Beijing Top Discipline for Artificial Intelligence Science and Engineering,University of Science and Technology Beijing,and the Beijing Natural Science Foundation(No.JQ20026).

摘　　要：In this article,a robot skills learning framework is developed,which considers both motion modeling and execution.In order to enable the robot to learn skills from demonstrations,a learning method called dynamic movement primitives(DMPs)is introduced to model motion.A staged teaching strategy is integrated into DMPs frameworks to enhance the generality such that the complicated tasks can be also performed for multi-joint manipulators.The DMP connection method is used to make an accurate and smooth transition in position and velocity space to connect complex motion sequences.In addition,motions are categorized into different goals and durations.It is worth mentioning that an adaptive neural networks(NNs)control method is proposed to achieve highly accurate trajectory tracking and to ensure the performance of action execution,which is beneficial to the improvement of reliability of the skills learning system.The experiment test on the Baxter robot verifies the effectiveness of the proposed method.

关 键 词：Dynamic movement primitives(DMPs) trajectory tracking control robot learning from demonstrations neural networks(NNs) adaptive control 

分 类 号：TP242[自动化与计算机技术—检测技术与自动化装置]