A Control Predictive Framework for Image-Based Visual Servoing Applications

Lazăr, Corneliu; Burlacu, Adrian

doi:10.1007/978-3-319-21290-6_19

Cited by 2 publications

(2 citation statements)

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“…In recent decades, robotic visual servoing has been fully researched and widely used in various areas, such as robotic production logistic [1], robotic service [2,3], robotic navigation and exploration [4,5]. According to the different feedback information from the camera, the visual servoing system can be divided into image-based visual servoing [6,7], position-based visual servoing [8,9], and hybrid visual servoing [10,11]. Refs.…”

Section: Introductionmentioning

confidence: 99%

“…Refs. [6,7] adopted the image-based visual servoing method, which takes the deviation between the current and desired image features as the control deviation. The robustness of different position-based visual servoing systems was discussed in [8,9], where the control deviations are the deviations of relative pose between the end-effector and the target in the Cartesian coordinate system.…”

Section: Introductionmentioning

confidence: 99%

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Constrained Image-Based Visual Servoing of Robot Manipulator with Third-Order Sliding-Mode Observer

Peng¹,

Li²,

Li³

et al. 2022

Machines

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A new image-based robot visual servo control strategy based on a third-order sliding-mode observer (TOSM) model predictive control is proposed in this study. This new control strategy solves the problem of robot visual servo control with system constraints and time-varying disturbances when the camera and model of the robot manipulator are uncertain and the joint velocity is unknown. In the proposed method, the joint velocity and system centralized uncertainties are estimated simultaneously based on a third-order sliding-mode observer, and the image-based visual servoing problem is transformed into a nonlinear optimization problem based on a model predictive control method considering both visibility constraints and actuator constraints, which minimizes the predicted trajectory cost function to generate the control signal for each cycle. Simulations were carried out to verify the effectiveness of the proposed control scheme.

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