Image-Based Visual Servoing Control of Robot Manipulators Using Hybrid Algorithm With Feature Constraints

• Published in: IEEE access Vol. 8; pp. 223495 - 223508
• Main Authors: Ren, Xiaolin, Li, Hongwen, Li, Yuanchun
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; Bidirectional extreme learning machine; Calibration; Cameras; constraint function; Control algorithms; Control theory; Field of view; Hybrid control; Jacobian matrices; Machine learning; Manipulators; Random noise; restricted region; Robot arms; Robot control; Robot kinematics; Robots; Servocontrol; smooth variable structure filter; Smoothness; Variable structure control; Visibility; Visual control; Visual servoing; Visualization
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2020.3042207

The challenge in addressing uncalibrated visual servoing (VS) control of robot manipulators with unstructured environments is to obtain appropriate interaction matrix and keep the image features in the field of view (FOV), especially when the non-Gaussian noise disturbance exists in the VS process. In this article, a hybrid control algorithm which combines bidirectional extreme learning machine (B-ELM) with smooth variable structure filter (SVSF) is proposed to estimate interaction matrix and tackle visibility constraints. For VS, the nonlinear mapping between image features and interaction matrix is approximated using the B-ELM learning. To increase the capability of anti-interference, the SVSF is employed to re-estimate interaction matrix. A constraint function presenting feature coordinates and region boundaries is given and added to the velocity controller, which drags image features away from the restricted region and ensures the smoothness of the velocities. Since the camera and robot model parameters are not required in developing the control strategy, the servoing task can be fulfilled flexibly and simply. Simulation and experimental results on a conventional 6-degree-of-freedom manipulator verify the effectiveness of the proposed method.