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Multi-Arm Global Cooperative Coal Gangue Sorting Method Based on Improved Hungarian Algorithm.

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Summary
This summary is machine-generated.

This study introduces a novel cooperative sorting method for coal and gangue using multiple robotic arms. The approach enhances sorting efficiency by enabling global cooperation and dynamic task allocation, improving overall performance.

Keywords:
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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Materials Science

Background:

  • Existing multi-manipulator gangue sorting methods with fixed workspaces suffer from limited cooperation and low sorting rates.
  • Current multi-task allocation strategies fail to optimize the performance of robotic sorting systems.

Purpose of the Study:

  • To propose and validate a novel multi-manipulator cooperative sorting method for enhanced coal and gangue separation.
  • To improve sorting efficiency and system benefits through global cooperation and dynamic task allocation.

Main Methods:

  • Developed a benefit function integrating sorting time and quality, informed by gangue flow and manipulator states.
  • Employed a Proportional-Integral-Derivative (PID) control-based trajectory planning algorithm for dynamic target tracking.
  • Enhanced the Hungarian algorithm for improved task allocation, prioritizing solutions through a standardized benefits matrix.
  • Implemented cooperative analysis and processing of solutions to eliminate conflicts and ensure task execution.

Main Results:

  • The proposed cooperative sorting method demonstrated a 10% and 20% increase in sorting efficiency compared to fixed space dynamic and designated space fixed points methods, respectively.
  • Experimental validation on a multi-arm coal and gangue sorting platform confirmed the method's effectiveness across varying belt speeds.
  • The system successfully guaranteed overall benefits and achieved cooperative control of multi-manipulator operations.

Conclusions:

  • The developed multi-manipulator cooperative sorting method significantly improves coal and gangue sorting efficiency.
  • This approach enables effective cooperative control of robotic arms across the entire workspace, overcoming limitations of fixed-space systems.
  • The method offers a robust solution for enhancing automated sorting processes in mining and material handling applications.