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Image based visual servoing with kinematic singularity avoidance for mobile manipulator.

Jesus Hernandez-Barragan1, Carlos Villaseñor1, Carlos Lopez-Franco1

  • 1University Center for Exact Sciences and Engineering, Universidad de Guadalajara, Guadalajara, Jalisco, Mexico.

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Summary
This summary is machine-generated.

This study implements visual servoing for redundant mobile manipulators using image-based visual servoing (IBVS). Damped least squares and task prioritization effectively reduce singularities and improve robot control.

Keywords:
ManipulabilityMobile manipulatorRedundant robotVisual servoing

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Area of Science:

  • Robotics
  • Computer Vision
  • Control Systems

Background:

  • Visual servoing (VS) enables robots to use camera feedback for precise control.
  • Redundant mobile manipulators offer enhanced dexterity but pose control challenges.
  • Eye-in-hand configurations require complex Jacobian matrix computations.

Purpose of the Study:

  • To implement a robust visual servoing strategy for redundant mobile manipulators.
  • To address kinematic singularities common in eye-in-hand configurations.
  • To enhance robot pose control accuracy and manipulability.

Main Methods:

  • Utilized the image-based visual servoing (IBVS) scheme.
  • Employed damped least squares (DLS) to invert the Jacobian matrix, mitigating singularities.
  • Implemented a task prioritization scheme for primary IBVS and secondary manipulability maximization.
  • Incorporated gravity compensation based on image space error.

Main Results:

  • Successfully demonstrated the effectiveness of the proposed visual servoing algorithm.
  • Reduced kinematic singularities and smoothed discontinuities in robot motion.
  • Validated the approach through simulations and experiments on a Kuka YouBot.

Conclusions:

  • The proposed visual servoing method enhances control for redundant mobile manipulators.
  • DLS and task prioritization are effective in overcoming singularity issues.
  • The integrated approach ensures robust and accurate robot manipulation in eye-in-hand systems.