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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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Research and Implementation of Robot Vision Scanning Tracking Algorithm Based on Deep Learning.

Haifeng Guo1, Wenyi Li1, Na Zhou1

  • 1College of Electrical and Information Engineering, Liaoning Institute of Science and Technology, Benxi, Liaoning 117004, China.

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This study introduces a deep learning robot vision tracking algorithm combining TLD and GOTURN methods. The enhanced GOTURN-LD shows improved accuracy and robustness, especially under changing illumination and occlusion.

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Area of Science:

  • Robotics
  • Computer Vision
  • Machine Learning

Background:

  • Deep learning-based robot vision tracking is challenging.
  • Existing algorithms have limitations in real-time performance and accuracy.

Purpose of the Study:

  • To propose a novel deep learning-based target tracking algorithm.
  • To evaluate its performance against classical methods.

Main Methods:

  • Combined traditional TLD algorithm with GOTURN algorithm.
  • Utilized offline training data and online learner updates.
  • Evaluated performance under varying illumination and occlusion.

Main Results:

  • TLD algorithm showed poor performance on accuracy curves.
  • GOTURN-LD demonstrated significantly improved performance with changing illumination.
  • TLD algorithm exhibited strong robustness against occlusion.
  • GOTURN-LD was more stable and outperformed GOTURN overall.

Conclusions:

  • The proposed deep learning approach enhances robot vision tracking.
  • GOTURN-LD offers a promising solution for real-time tracking with improved accuracy and robustness.