{"title":"A comprehensive review and bibliometric analysis on collaborative robotics for industry: safety emerging as a core focus.","authors":"Aida Haghighi, Morteza Cheraghi, Jérôme Pocachard, Valérie Botta-Genoulaz, Sabrina Jocelyn, Hamidreza Pourzarei","doi":"10.3389/frobt.2025.1605682","DOIUrl":null,"url":null,"abstract":"<p><p>Research organizations and academics often seek to map the development of scientific fields, identify research gaps, and guide the direction of future research. In cobot-related research, the scientific literature consulted does not propose any comprehensive research agenda. Moreover, cobots, industrial robots inherently designed to collaborate with humans, bring with them emerging issues. To solve them, interdisciplinary research is often essential (e.g., combination of engineering, ergonomics and biomechanics expertise to handle safety challenges). This paper proposes an exhaustive study that employs a scoping review and bibliometric analysis to provide a structured macro perspective on the developments, key topics, and trends in cobot research for industry. A total of 2,195 scientific publications were gained from the Web of Science database, and a thorough selection process narrowed them down to 532 papers for comprehensive analysis. Descriptive statistics were employed to analyze bibliometric measures, highlighting publication trends, leading journals, the most productive institutions, engaged countries, influential authors, and prominent research topics. Co-authorship and bibliographic couplings were also examined. Through a co-occurrence analysis of terms, the content and research objectives of the papers were systematically reviewed and lead to a univocal categorization framework. That categorization can support organizations or researchers in different cobotics (collaborative robotics) fields by understanding research developments and trends, identifying collaboration opportunities, selecting suitable publication venues, advancing the theoretical and experimental understanding of automatic collaborative systems, and identifying research directions and predicting the evolution of publication quantity in cobotics.</p>","PeriodicalId":47597,"journal":{"name":"Frontiers in Robotics and AI","volume":"12 ","pages":"1605682"},"PeriodicalIF":3.0000,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12464494/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Robotics and AI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/frobt.2025.1605682","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Research organizations and academics often seek to map the development of scientific fields, identify research gaps, and guide the direction of future research. In cobot-related research, the scientific literature consulted does not propose any comprehensive research agenda. Moreover, cobots, industrial robots inherently designed to collaborate with humans, bring with them emerging issues. To solve them, interdisciplinary research is often essential (e.g., combination of engineering, ergonomics and biomechanics expertise to handle safety challenges). This paper proposes an exhaustive study that employs a scoping review and bibliometric analysis to provide a structured macro perspective on the developments, key topics, and trends in cobot research for industry. A total of 2,195 scientific publications were gained from the Web of Science database, and a thorough selection process narrowed them down to 532 papers for comprehensive analysis. Descriptive statistics were employed to analyze bibliometric measures, highlighting publication trends, leading journals, the most productive institutions, engaged countries, influential authors, and prominent research topics. Co-authorship and bibliographic couplings were also examined. Through a co-occurrence analysis of terms, the content and research objectives of the papers were systematically reviewed and lead to a univocal categorization framework. That categorization can support organizations or researchers in different cobotics (collaborative robotics) fields by understanding research developments and trends, identifying collaboration opportunities, selecting suitable publication venues, advancing the theoretical and experimental understanding of automatic collaborative systems, and identifying research directions and predicting the evolution of publication quantity in cobotics.
研究机构和学者经常试图描绘科学领域的发展,确定研究差距,并指导未来研究的方向。在与协作机器人相关的研究中,所查阅的科学文献并没有提出任何全面的研究议程。此外,协作机器人(cobot),即生来就设计用于与人类合作的工业机器人,也带来了新出现的问题。为了解决这些问题,跨学科的研究往往是必不可少的(例如,结合工程、人体工程学和生物力学专业知识来应对安全挑战)。本文提出了一项详尽的研究,采用范围审查和文献计量分析,为工业协作机器人研究的发展、关键主题和趋势提供了一个结构化的宏观视角。从Web of Science数据库中总共获得了2195篇科学出版物,经过彻底的筛选过程,将其缩小到532篇进行综合分析。描述性统计用于分析文献计量指标,突出了出版趋势、主要期刊、最具生产力的机构、参与的国家、有影响力的作者和突出的研究主题。共同作者和书目耦合也进行了检查。通过对术语的共现分析,系统地回顾了论文的内容和研究目标,并得出了一个明确的分类框架。该分类可以帮助不同协作机器人领域的组织或研究人员了解研究发展和趋势,识别合作机会,选择合适的出版场所,推进对自动协作系统的理论和实验理解,以及确定研究方向和预测协作机器人出版数量的演变。
期刊介绍:
Frontiers in Robotics and AI publishes rigorously peer-reviewed research covering all theory and applications of robotics, technology, and artificial intelligence, from biomedical to space robotics.