Adaptive visual servoing control for an underwater soft robot
Article publication date: 5 October 2018
Issue publication date: 6 December 2018
Soft robotics, regarded as a new research branch of robotics, has generated increasing interests in this decade and has demonstrated its outperformance in addressing safety issues when cooperating with human beings. However, there is still lack of accurate close-loop control because of the difficulty in acquiring feedback information and accurately modeling the system, especially in interactive environments. To this end, this paper aims to improve the controllability of the soft robot working in specific underwater environment. The system dynamics, which takes complicated hydrodynamics into account, is solved using Kane’s method. The dynamics-based adaptive visual servoing controller is proposed to realize accurate sensorimotor control.
This paper presents an image-based visual servoing control scheme for a cable-driven soft robot with a fixed camera observing the motions. The intrinsic and extrinsic parameters of the camera can be adapted online so that tedious camera calibration work can be eliminated. It is acknowledged that kinematics-based control can be only applied into tasks in the free space and has limitation in accelerating the motion speed of robot arms. That is, one must consider the unneglectable interaction effects generated from the environment and objectives when operating soft robots in such interactive control tasks. To extend the application of soft robots into underwater environment, the study models system dynamics considering complicated hydrodynamic effects. With the pre-knowledge of the external effects, the performance of the robot can be further improved by adding the compensation term into the controller.
The proposed controller has theoretically proved its convergence of image error, adaptive estimation error and the stability of the dynamical system based on Lyapunov’s analysis. The authors also validate the performance of the controller in positioning control task in an underwater environment. The controller shows its capacity of rapid convergence to and accurate tracking performance of a static image target in a physical experiment.
To the best of the authors’ knowledge, there is no such research before that has developed dynamics-based visual servoing controller which takes into account the environment interactions. This work can thus improve the control accuracy and enhance the applicability of soft robotics when operating in complicated environments.
Xu, F., Wang, H., Chen, W. and Wang, J. (2018), "Adaptive visual servoing control for an underwater soft robot", Assembly Automation, Vol. 38 No. 5, pp. 669-677. https://doi.org/10.1108/AA-12-2017-193
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