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The proliferation of multi-robot systems has significantly advanced the capabilities and applications of robotics in various fields. Efficiently managing and as-signing tasks to multiple robots remains a critical challenge, impacting overall system performance and operational efficiency. This research proposes a cloud-based task assignment strategy leveraging an improved Periodic Min-Max Weight (PMW) algorithm. By integrating cloud computing resources, we aim to enhance the collaboration and coordination among robots, optimizing task distribution and completion. The proposed model demonstrates a scalable and robust solution to the Multi-Robot Task Assignment Problem (MRTA), promising significant improvements in efficiency and adaptability.

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A Novel Task Assignment Strategy for Multi-robot System

  • 会议论文

  • 发表日期：

    2026年

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  • Md Ali Haider,
  • Raihan Kabir,
  • Shah Alam Hossain,
  • Yutaka Watanobe

摘要

The proliferation of multi-robot systems has significantly advanced the capabilities and applications of robotics in various fields. Efficiently managing and as-signing tasks to multiple robots remains a critical challenge, impacting overall system performance and operational efficiency. This research proposes a cloud-based task assignment strategy leveraging an improved Periodic Min-Max Weight (PMW) algorithm. By integrating cloud computing resources, we aim to enhance the collaboration and coordination among robots, optimizing task distribution and completion. The proposed model demonstrates a scalable and robust solution to the Multi-Robot Task Assignment Problem (MRTA), promising significant improvements in efficiency and adaptability.