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Related Experiment Video

Updated: Jan 13, 2026

Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
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Dynamic grasping system based on visual algorithm and robot arm collaboration in logistics production line.

Bowen He1, Bin Chen1

  • 1Mechanical and Electrical Engineering College, Hainan Vocational University of Science and Technology, Haikou, China.

Plos One
|January 9, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces the Vision-based Robotic Collaborative Dynamic Grasping System (VRCDS) for automated logistics. The VRCDS enhances grasping efficiency and accuracy using multi-robot collaboration and advanced vision algorithms, saving energy.

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Area of Science:

  • Robotics
  • Automation
  • Computer Vision

Background:

  • Automated logistics requires efficient and accurate dynamic grasping.
  • Traditional systems often face limitations in speed, accuracy, and energy consumption.

Purpose of the Study:

  • To develop and evaluate a novel dynamic grasping system for logistics automation.
  • To improve grasping accuracy, system efficiency, and energy savings.

Main Methods:

  • Integration of a multi-feature weighted Perspective-n-Point (PnP) vision algorithm.
  • Implementation of multi-robot arm collaboration.
  • Establishment of a closed-loop "perception-decision-execution-feedback" architecture.

Main Results:

  • High object recognition accuracy and robust grasping efficiency across varying conveyor speeds.
  • Precise trajectory control for dynamic grasping tasks.
  • Significant reduction in power consumption compared to conventional methods.

Conclusions:

  • The VRCDS offers an efficient, precise, and reliable solution for dynamic grasping in automated logistics.
  • The system demonstrates superior performance in accuracy, efficiency, and energy savings.