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A new active visual system for humanoid robots.

De Xu1, You Fu Li, Min Tan

  • 1Key Laboratory of Complex System and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China. sdxude@yahoo.com

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|March 20, 2008
PubMed
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This study introduces an active vision system using bionic principles for robust object positioning. The novel system, insensitive to camera properties, enables flexible visual tracking and accurate object localization.

Area of Science:

  • Robotics
  • Computer Vision
  • Biomimetics

Background:

  • Active vision systems enhance object localization and tracking capabilities.
  • Existing systems often exhibit sensitivity to camera intrinsic parameters, limiting flexibility.
  • Bionic vision principles offer a framework for developing more robust and adaptable visual systems.

Purpose of the Study:

  • To develop a novel active visual system inspired by bionic vision.
  • To achieve camera-insensitive object positioning and enhance visual tracking.
  • To investigate a generalizable model for active visual positioning with two cameras.

Main Methods:

  • Development of a mechanical platform with two degrees of freedom (pitch and yaw) for camera mounting.
  • Simultaneous adjustment of two cameras' optical axes in opposite directions to center object images.

Related Experiment Videos

  • Geometric computation of object position using active motions and camera geometry.
  • Investigation of a generalized model for active visual positioning without a 'neck' mechanism.

    • Main Results:

    • The developed active visual system effectively centers object images using bionic principles.
    • Object position is accurately determined through geometric analysis of active camera motions.
    • The generalized model demonstrates reduced sensitivity to intrinsic camera parameters.
    • Experimental validation confirms the effectiveness of the proposed active vision methods.

    Conclusions:

    • The proposed bionic active vision system provides a flexible and robust solution for object positioning.
    • The system's insensitivity to camera properties and generalized model enhance applicability in diverse scenarios.
    • This research advances active vision techniques, particularly for applications like visual tracking with dynamic focusing.