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Related Experiment Video

Updated: Jan 15, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
05:47

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Performance analysis of robotic arm visual servo system based on BFS-canny image edge detection algorithm.

Yuling Yan1,2, Siti Salasiah Mokri3

  • 1Faculty of Engineering and Built Environment (FKAB), Universiti Kebangsaan Malaysia (UKM), Bangi Selangor, 43600, Malaysia.

Scientific Reports
|October 9, 2025
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Summary
This summary is machine-generated.

This study introduces an advanced image edge detection algorithm for robotic arm visual servoing, significantly improving real-time performance and stability. The new method enhances robotic arm intelligence and perception in complex environments.

Keywords:
Feature extractionHigh speed imageImage edge detection algorithmMechanical armPerformance analysisVisual serving system

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Area of Science:

  • Robotics
  • Computer Vision
  • Image Processing

Background:

  • Visual servoing enhances robotic arm intelligence using visual feedback.
  • Current image processing in visual servoing faces real-time performance and stability challenges.

Purpose of the Study:

  • To develop an efficient image edge detection algorithm for robotic arm visual servoing.
  • To improve the real-time performance, stability, and reliability of robotic arm systems.

Main Methods:

  • Combined Breadth-First Search, Canny, and Harris algorithms with parallel processing.
  • Developed a novel image edge detection algorithm.
  • Established a robotic arm visual servo system incorporating the algorithm.

Main Results:

  • The proposed algorithm demonstrated superior performance over existing methods with increasing data volume.
  • Achieved accuracy, recall, and F1 scores exceeding 95%, 86%, and 90%, respectively.
  • Reached 110FPS computational efficiency for 4096*2160 images and maintained an average running time of at least 30.28ms.

Conclusions:

  • The developed algorithm effectively enhances robotic arm visual servo system performance and reliability.
  • The method improves dynamic tracking performance and enables perception in complex environments.
  • The research contributes to advancing intelligent robotic arm applications.