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Multi-robot cooperative autonomous exploration via task allocation in terrestrial environments.

Xiangda Yan1, Zhe Zeng2, Keyan He1

  • 1Laboratory of Unmanned Combat Systems, National University of Defense Technology, Changsha, China.

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Summary
This summary is machine-generated.

This study presents a cooperative autonomous exploration strategy for multi-robot systems. It introduces a self-healing method to ensure exploration continuity despite robot failures, enhancing system resilience.

Keywords:
Mean-Shiftcooperative autonomous explorationfrontiermulti-robotpath planningtask allocation

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Distributed Systems

Background:

  • Cooperative autonomous exploration using multi-robot systems offers efficiency gains over single robots for covering large areas.
  • Effective coordination is crucial for successful multi-robot cooperative autonomous exploration.
  • Mobile robots face operational challenges, including potential failures in harsh environments.

Purpose of the Study:

  • To design a robust multi-robot cooperative autonomous exploration strategy.
  • To develop a self-healing mechanism for autonomous exploration systems to recover from robot failures.

Main Methods:

  • A novel cooperative autonomous exploration strategy is designed for multi-robot systems.
  • A self-healing method is proposed to address robot failures during exploration tasks.

Main Results:

  • The proposed strategy facilitates efficient exploration of unknown environments by multiple robots.
  • The self-healing approach enhances the system's ability to recover from individual robot failures, ensuring task completion.

Conclusions:

  • The designed strategy and self-healing method improve the reliability and efficiency of multi-robot cooperative autonomous exploration.
  • This work contributes to the advancement of resilient autonomous systems for complex environmental exploration.