Abstract
This paper presents an uncalibrated visual servoing scheme for underwater vehicle manipulator systems (UVMSs) with an eye-in-hand camera under uncertainties. These uncertainties contain vision sensor parameters, UVMS kinematics and feature position information. At first, a linear separation approach is addressed to collect these uncertainties into vectors, and this approach can also be utilized in other free-floating based manipulator systems. Secondly, a novel nonlinear adaptive controller is proposed to achieve image error convergence by estimating these vectors, the gradient projection method is utilized to optimize the restoring moments. Thirdly, a high order disturbance observer is addressed to deal with time-varying disturbances, and the convergence of the image errors is proved under the Lyapunov theory. Finally, in order to illustrate the effectiveness of the proposed method, numerical simulations based on a 9 degrees of freedom (DOFs) UVMS with an eye-in-hand camera are conducted. In simulations, the UVMS is expected to track a circle trajectory on the image plane, meanwhile, time-varying disturbances are exerted on the system. The proposed scheme can achieve accurate and smooth tracking results during simulations.
Highlights
Nowadays, underwater vehicles play a pivotal role in the applications of oceanic explorations, submarine salvages and scientific expeditions [1,2]
The rest of this paper is organized, as follows: in Section 2, we introduce the kinematic of the system in underwater vehicle manipulator systems (UVMSs), the dynamic model of the UVMS is established
In the process of designing the controller, at first, we establish a new reference velocity term to optimize the restoring moment through using the gradient projection method (GPM), novel adaptive laws are established to estimate the uncertainties in uncalibrated systems by utilizing the linear separation method which we described in the last section
Summary
Underwater vehicles play a pivotal role in the applications of oceanic explorations, submarine salvages and scientific expeditions [1,2]. Camera parameters, UVMS kinematic modelling, and feature manipulator and under the assumption that kinematics of the manipulator is perfectly known In this position are always difficult to accurately achieve. We propose a novel linear separation method to collect these uncertainties into constant Kinematics vectors without this assumption for free-floating based articulated manipulators. As described in previous proofs, camera perspective projection matrix M, the manipulator kinematics parameters aee and the manipulator relative position vector ε0V,0 are all collected in azin ,az ,azd. From the proofs of above three properties, uncertainties of the systems (i.e., uncertainties in intrinsic and extrinsic parameters of the camera, the kinematics of the UVMS, the position of the target w.r.t. the inertial frame) can be collected in these three parameter vectors in (17), (20), and (24). JΩ is used to describe the relationship from the generalized velocity term ζ to zx + 12 z∆x
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