Collaborative Intelligence for Safety-Critical Industries: A Literature Review

被引:0
|
作者
Ramos, Ines F. [1 ]
Gianini, Gabriele [2 ]
Leva, Maria Chiara [3 ]
Damiani, Ernesto [1 ]
机构
[1] Univ Milan, Dept Comp Sci, I-20122 Milan, Italy
[2] Univ Milano Bicocca, Dept Informat Syst & Commun DISCo, I-20126 Milan, Italy
[3] Technol Univ Dublin, Sch Food Sci & Environm Hlth, Dublin D07 H6K8, Ireland
基金
欧盟地平线“2020”;
关键词
collaborative intelligence; AI; safety-critical industries; HUMAN-ROBOT COLLABORATION; RECOGNITION; EFFICIENT; POMDP;
D O I
10.3390/info15110728
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
While AI-driven automation can increase the performance and safety of systems, humans should not be replaced in safety-critical systems but should be integrated to collaborate and mitigate each other's limitations. The current trend in Industry 5.0 is towards human-centric collaborative paradigms, with an emphasis on collaborative intelligence (CI) or Hybrid Intelligent Systems. In this survey, we search and review recent work that employs AI methods for collaborative intelligence applications, specifically those that focus on safety and safety-critical industries. We aim to contribute to the research landscape and industry by compiling and analyzing a range of scenarios where AI can be used to achieve more efficient human-machine interactions, improved collaboration, coordination, and safety. We define a domain-focused taxonomy to categorize the diverse CI solutions, based on the type of collaborative interaction between intelligent systems and humans, the AI paradigm used and the domain of the AI problem, while highlighting safety issues. We investigate 91 articles on CI research published between 2014 and 2023, providing insights into the trends, gaps, and techniques used, to guide recommendations for future research opportunities in the fast developing collaborative intelligence field.
引用
收藏
页数:42
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