TY - GEN
T1 - DMP and GMR based teaching by demonstration for a KUKA LBR robot
AU - Hewitt, Alexander
AU - Yang, Chenguang
AU - Li, Yong
AU - Cui, Rongxin
N1 - Publisher Copyright:
© 2017 Chinese Automation and Computing Society in the UK - CACSUK.
PY - 2017/10/23
Y1 - 2017/10/23
N2 - This paper investigates the problem of Teaching by Demonstration (TbD) on a KUKA lightweight robot (LBR). Motions are recorded by a human operator, and then the data is used to model a nonlinear system, i.e., the dynamic motor primitive (DMP). In order to learn from multiple demonstrations, Gaussian Mixture Models (GMM) are employed rather than using conventional Gaussian process for the evaluation of the non-linear term of the DMP. Then the Gaussian mixture regression (GMR) algorithm is applied to generate a synthesized trajectory with smaller position errors in 3D space. The proposed approach is tested and demonstrated by performing two tasks with KUKA iiwa robot.
AB - This paper investigates the problem of Teaching by Demonstration (TbD) on a KUKA lightweight robot (LBR). Motions are recorded by a human operator, and then the data is used to model a nonlinear system, i.e., the dynamic motor primitive (DMP). In order to learn from multiple demonstrations, Gaussian Mixture Models (GMM) are employed rather than using conventional Gaussian process for the evaluation of the non-linear term of the DMP. Then the Gaussian mixture regression (GMR) algorithm is applied to generate a synthesized trajectory with smaller position errors in 3D space. The proposed approach is tested and demonstrated by performing two tasks with KUKA iiwa robot.
KW - Dynamic motor primitive
KW - Gaussian mixture model
KW - Gaussian mixture regression
KW - KUKA
KW - Teaching by demonstration
UR - http://www.scopus.com/inward/record.url?scp=85040021221&partnerID=8YFLogxK
U2 - 10.23919/IConAC.2017.8081982
DO - 10.23919/IConAC.2017.8081982
M3 - 会议稿件
AN - SCOPUS:85040021221
T3 - ICAC 2017 - 2017 23rd IEEE International Conference on Automation and Computing: Addressing Global Challenges through Automation and Computing
BT - ICAC 2017 - 2017 23rd IEEE International Conference on Automation and Computing
A2 - Zhang, Jie
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd IEEE International Conference on Automation and Computing, ICAC 2017
Y2 - 7 September 2017 through 8 September 2017
ER -