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<p>Multi-Human Multi-Robot (MH-MR) teams composed of heterogeneous human and robotic agents are rapidly expanding across various sectors, including environmental disaster management, space exploration, search and rescue missions, healthcare, and manufacturing applications. While the integration of heterogeneous agents, humans and robots, introduces significant technical and operational challenges, an even greater complexity arises when evaluating their effectiveness and performance. As productivity of MH-MR teams remains a relatively unexplored field, existing assessment models and frameworks are limited and often fragmented. This article provides a focused analysis of productivity metrics, with primary reference to manufacturing contexts, critically evaluating these indicators in terms of their adaptability and limitations for MH-MR teams. Based on this, the paper proposes revised and novel indicators capable of reflecting the dynamics and coordination challenges typical of MH-MR teams. These findings aim to guide future research towards more comprehensive and effective assessment strategies. Examples from an explanatory assembly case study are presented to illustrate the practical application of these novel KPIs in real-world contexts.</p>

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Productivity assessment in multi-human multi-robot manufacturing teams: insights and proposal for novel KPIs

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月29日

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  • Aurora Sofia Di Matteo,
  • Matteo Capponi,
  • Luca Mastrogiacomo,
  • Fiorenzo Franceschini

摘要

Multi-Human Multi-Robot (MH-MR) teams composed of heterogeneous human and robotic agents are rapidly expanding across various sectors, including environmental disaster management, space exploration, search and rescue missions, healthcare, and manufacturing applications. While the integration of heterogeneous agents, humans and robots, introduces significant technical and operational challenges, an even greater complexity arises when evaluating their effectiveness and performance. As productivity of MH-MR teams remains a relatively unexplored field, existing assessment models and frameworks are limited and often fragmented. This article provides a focused analysis of productivity metrics, with primary reference to manufacturing contexts, critically evaluating these indicators in terms of their adaptability and limitations for MH-MR teams. Based on this, the paper proposes revised and novel indicators capable of reflecting the dynamics and coordination challenges typical of MH-MR teams. These findings aim to guide future research towards more comprehensive and effective assessment strategies. Examples from an explanatory assembly case study are presented to illustrate the practical application of these novel KPIs in real-world contexts.