TY - GEN
T1 - A Fuzzy Approach to Visual Servoing with A Bagging Method for Wheeled Mobile Robot
AU - Xu, Meng
AU - Shi, Haobin
AU - Jiang, Kai
AU - Wang, Lihua
AU - Li, Xuesi
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Visual servoing is a vision-based control method with a mechanism of closed-loop, which uses feedback information extracted from the camera to control the motion of a robot. In this paper, we propose a fuzzy-based visual servoing integrated with a bagging method for the wheeled mobile robot (WMR). Previous studies have shown that the value of the mixture parameter for the image Jacobian matrix affects the performance of image-based visual servoing(IBVS). However, the mixture parameter value is constant in most visual servoing methods. To address this problem, we propose a fuzzy-based method to adjust the mixture parameter during the process of visual servoing. Meanwhile, in order to reduce the effect of image noise and the computational complexity of the pseudoinverse matrix, we propose a bagging method to calculate the inverse kinematics, instead of using the Moore-Penrose pseudoinverse method. The results of simulation and real experiments demonstrate the effectiveness of the proposed IBVS method.
AB - Visual servoing is a vision-based control method with a mechanism of closed-loop, which uses feedback information extracted from the camera to control the motion of a robot. In this paper, we propose a fuzzy-based visual servoing integrated with a bagging method for the wheeled mobile robot (WMR). Previous studies have shown that the value of the mixture parameter for the image Jacobian matrix affects the performance of image-based visual servoing(IBVS). However, the mixture parameter value is constant in most visual servoing methods. To address this problem, we propose a fuzzy-based method to adjust the mixture parameter during the process of visual servoing. Meanwhile, in order to reduce the effect of image noise and the computational complexity of the pseudoinverse matrix, we propose a bagging method to calculate the inverse kinematics, instead of using the Moore-Penrose pseudoinverse method. The results of simulation and real experiments demonstrate the effectiveness of the proposed IBVS method.
KW - Bagging method
KW - Fuzzy approach
KW - Mobile wheeled robot
KW - Visual servoing
UR - http://www.scopus.com/inward/record.url?scp=85072380431&partnerID=8YFLogxK
U2 - 10.1109/ICMA.2019.8816420
DO - 10.1109/ICMA.2019.8816420
M3 - 会议稿件
AN - SCOPUS:85072380431
T3 - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
SP - 444
EP - 449
BT - Proceedings of 2019 IEEE International Conference on Mechatronics and Automation, ICMA 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Mechatronics and Automation, ICMA 2019
Y2 - 4 August 2019 through 7 August 2019
ER -