Visually Guided Manipulator Based on Artificial Neural Networks

ABSTRACT

In this paper, a method is proposed to control the movements of a manipulator using image-based visual servoing, which integrates computational intelligence for object tracking. The objective is to visually servo the 6 DOF PUMA 560 using a charge-coupled device camera attached to the end-effector of the manipulator whereby image is acquired (which is called eye-in-hand camera configuration). The image features are then extracted to form the image Jacobian matrix. The proposed method is based on an artificial neural network (ANN), which is capable of approximating complex and nonlinear image motions to the manipulator motions in order to control the manipulator system. For the visual servoing problem, the gradient descent (GD) and Levenberg–Marquardt (LM) algorithms have been implemented and compared, concluding that the LM algorithm has got better performance than the GD algorithm in visually controlling the manipulator based on ANN. The LM algorithm is integrated into the ANN-based visual control for tracking the periodic moving object in the presence of noise. The simulations show that the controller is noise tolerant too.

KEYWORDS:

• Eye-in-hand
• IBVS
• Neural networks
• Robot vision
• Visual servoing
• Visual tracking

DISCLOSURE STATEMENT

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Yasaman Ghandi

Yasaman Ghandi was born in Tehran, Iran. She received the BSc degree in electronic engineering from Shahid Rajaee Teacher Training University, and the MSc degree in control engineering from Imam Khomeini International University. Her research interests include robotics, artificial intelligence, and control theory.

Corresponding author E-mail: [email protected]

Mohsen Davoudi

Mohsen Davoudi received his PhD degree in control engineering from Polytechnic University of Milan (Politecnico di Milano), Milan, Italy. Presently, he has assistant professor position at Imam Khomeini International University (IKIU), Qazvin, Iran.

E-mail: [email protected]