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Research on multirobot pursuit task allocation algorithm based on emotional cooperation factor.

Baofu Fang1, Lu Chen1, Hao Wang1

  • 1School of Computer and Information, Hefei University of Technology, Hefei 230009, China.

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|August 26, 2014
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Summary
This summary is machine-generated.

This study introduces an emotional cooperation factor for self-interested robots, enhancing multirobot task allocation. The proposed algorithm optimizes pursuit team formation and task completion, improving efficiency.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Multi-Agent Systems

Background:

  • Multirobot task allocation is a significant challenge in robotics.
  • Existing methods often struggle with self-interested agents and cooperative willingness.
  • A novel approach is needed to improve coordination in complex multirobot scenarios.

Purpose of the Study:

  • To introduce a new emotional model for self-interested robots in task allocation.
  • To develop a multirobot pursuit task allocation algorithm based on an emotional cooperation factor.
  • To enhance cooperative willingness and optimize task completion in multirobot systems.

Main Methods:

  • An emotional cooperation factor was introduced and updated based on emotional attenuation and external stimuli.
  • A multirobot pursuit task allocation algorithm was proposed, integrating the emotional cooperation factor.
  • A two-step auction algorithm was used for recruiting team leaders and collaborators to form pursuit teams.

Main Results:

  • The proposed algorithm demonstrated improved optimization of total pursuit time.
  • The algorithm showed enhanced total team revenue compared to existing methods.
  • Experimental results validated the effectiveness of the emotional cooperation factor in multirobot task allocation.

Conclusions:

  • The emotional cooperation factor provides a novel way to measure cooperative willingness in self-interested robots.
  • The developed algorithm effectively optimizes multirobot pursuit task allocation.
  • This approach offers a promising direction for improving coordination and performance in multirobot systems.