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One-Degree-of-Freedom System01:24

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Related Experiment Video

Updated: Mar 13, 2026

Using Eye-tracking to Assess the Relative Importance of Visual and Vestibular Input to Subcortical Motion Processing in the Roll Plane
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Uncalibrated Visual Tracking Control for Networked Eye-in-Hand Robots by Adaptive Distributed Observer.

Haiwen Wu, Wei Chen, Jinfei Hu

    IEEE Transactions on Cybernetics
    |March 11, 2026
    PubMed
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    This study develops a distributed control scheme for robotic manipulators with uncalibrated cameras to track unknown moving targets. The method ensures precise target projection on the image plane despite camera and depth uncertainties.

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    Area of Science:

    • Robotics
    • Control Systems
    • Computer Vision

    Background:

    • Visual tracking of unknown targets by robotic manipulators presents challenges due to uncalibrated cameras and uncertain target motion.
    • Maintaining target projection on the image plane is crucial for effective robotic manipulation.

    Purpose of the Study:

    • To develop a distributed control scheme for a network of robotic manipulators to visually track an unknown moving target.
    • To ensure the target's image projection is maintained at a specified position despite uncalibrated camera parameters and uncertain depths.

    Main Methods:

    • An adaptive distributed observer estimates the target's motion.
    • An image-space observer estimates target position and velocity for each robot.
    • Adaptive laws are proposed to handle uncertain camera and robot parameters, leveraging depth-independent Jacobian properties.

    Main Results:

    • The closed-loop system stability is rigorously proven using Lyapunov stability theory.
    • Asymptotic convergence of image-space tracking errors is demonstrated.
    • Simulations with three-DOF robotic manipulators validate the scheme's effectiveness.

    Conclusions:

    • The proposed distributed control scheme effectively addresses visual tracking of unknown moving targets by networked robotic manipulators.
    • The method robustly handles uncalibrated cameras, uncertain depths, and unknown target dynamics.
    • This work contributes to advanced robotic perception and control for complex manipulation tasks.