Uncalibrated Visual Servoing Using More Precise Model

Fu, Qingshan; Zhang, Zhisheng; Shi, Jinfei

doi:10.1109/ramech.2008.4681521

Cited by 7 publications

(3 citation statements)

References 8 publications

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“…To improve the computational efficiency, some methods do not directly approximate the Hessian matrix, only the residual term. Fu et al (2008) used a secant method to approximate the residual term and used the Levenberg–Marquardt algorithm (LMA) to ensure global convergence. Kim and Lee (2006) used the full Newton’s method and the secant method to approximate the residual.…”

Section: Related Workmentioning

confidence: 99%

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Virtual exoskeleton-driven uncalibrated visual servoing control for mobile robotic manipulators based on human–robot–robot cooperation

Zeng

Song

et al. 2018

Transactions of the Institute of Measurement and Control

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This paper presents an uncalibrated visual servoing control system based on the human–robot–robot cooperation (HRRC). In case of malfunctions of the joint sensors of a robotic manipulator, the proposed system enables the mobile robot to continue operating the manipulator to complete the task that requires careful handling. With the aid of a virtual exoskeleton, an operator may use a human–computer interaction (HCI) device to guide the malfunctioning manipulator. During the guiding process, the virtual exoskeleton serves as a connector between the HCI device and the manipulator. However, when using the HCI device to guide the virtual exoskeleton, there could be a risk of a large-residual problem at any time caused by non-uniform guiding. To solve this problem, a residual switching algorithm (RSA) has been proposed that can identify whether the residual should be calculated based on the motion characteristics of the artificial guiding, reducing the computational cost and ensuring the tracking stability. To enhance the virtual exoskeleton’s ability to drive the manipulator, a multi-joint fuzzy driving controller has been proposed, which can drive the corresponding joint of the manipulator in accordance with an offset vector between the virtual exoskeleton and the manipulator. Lastly, the guiding experiments have verified that, compared with the contrast algorithm, the proposed RSA has a better tracking performance. A peg-in-hole assembly experiment has shown that the proposed control system can assist the operator to control efficiently the robotic manipulator with malfunctioning joint sensors.

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Section: Related Workmentioning

confidence: 99%

“…Fu et al (2008) suggested using a trust-region method to adjust the damping parameter μ k self-adaptively, that is, μ k is adjusted according to the actual reduction of the objective function and the predicted reduction of the quadratic model.…”

Section: Approachmentioning

confidence: 99%

Virtual exoskeleton-driven uncalibrated visual servoing control for mobile robotic manipulators based on human–robot–robot cooperation

Zeng

Song

et al. 2018

Transactions of the Institute of Measurement and Control

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show abstract

“…To do away with this dependence, one could optimize for the parameters in the image Jacobian whilst the error in the image plane is being minimized. This is done for instance, using Gauss-Newton to minimize the squared image error and non-linear least squares optimization for the image Jacobian [7]; using weighted recursive least squares, not to obtain the true parameters, but instead an approximation that still guarantees asymptotic stability of the control law in the sense of Lyapunov [8], [9]; using k-nearest neighbor regression to store previously estimated local models or previous movements, and estimating the Jacobian using local least squares [10], or building a secant model using population of the previous iterates [11]. To provide robustness to outliers in the computation of the Jacobian, [12] proposes the use of an M-estimator.…”

Section: Introductionmentioning

confidence: 99%

Uncalibrated Visual Servo for Unmanned Aerial Manipulation

Santamaria-Navarro

Grosch

Lippiello

et al. 2017

IEEE/ASME Trans. Mechatron.

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This paper addresses the problem of autonomous servoing an unmanned redundant aerial manipulator using computer vision. The over-actuation of the system is exploited by means of a hierarchical control law which allows to prioritize several tasks during flight. We propose a safety related primary task to avoid possible collisions. As a secondary task we present an uncalibrated image-based visual servo strategy to drive the arm end-effector to a desired position and orientation using a camera attached to it. In contrast to previous visual-servo approaches, a known value of camera focal length is not strictly required. To further improve flight behavior we hierarchically add one task to reduce dynamic effects by vertically aligning the arm center of gravity to the multirotor gravitational vector, and another one that keeps the arm close to a desired configuration of high manipulability and avoiding arm joint limits. The performance of the hierarchical control law, with and without activation of each of the tasks, is shown in simulations and in real experiments confirming the viability of such prioritized control scheme for aerial manipulation

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Artificial Neural Network Based Control Strategy Research and Simulation on Robot Uncalibrated Visual Servoing System

Dong

Jia

2013

Intelligent Science and Intelligent Data Engineering

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Uncalibrated Visual Servoing Using More Precise Model

Cited by 7 publications

References 8 publications

Virtual exoskeleton-driven uncalibrated visual servoing control for mobile robotic manipulators based on human–robot–robot cooperation

Virtual exoskeleton-driven uncalibrated visual servoing control for mobile robotic manipulators based on human–robot–robot cooperation

Uncalibrated Visual Servo for Unmanned Aerial Manipulation

Artificial Neural Network Based Control Strategy Research and Simulation on Robot Uncalibrated Visual Servoing System

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