🤖 AI Summary
This study addresses the lack of a unified requirements framework in current human-AI collaboration tasks, which hinders the design and evaluation of complex cooperative systems. By systematically reviewing academic literature, industry standards, and regulatory guidelines, this work proposes the first comprehensive requirements taxonomy encompassing six high-level categories and twenty-one subcategories. The framework integrates fragmented knowledge and clarifies critical dimensions such as information provision, relationship control, and decision support. Through an iterative process of requirement extraction, classification, and expert validation, the authors derived 361 requirements from 14 sources to construct the taxonomy and further demonstrated its applicability on an independent corpus containing 448 requirements. The resulting framework received endorsement from five domain experts.
📝 Abstract
Autonomous systems are increasingly deployed in safety- and mission-critical domains where humans and robots must operate as a team to complete complex tasks. Existing requirements for Human-Robot teamwork remain fragmented across disparate sources, with no unified framework that addresses complexities of collaborative Human-Robot tasks. We address this gap by presenting a taxonomy of Human-Robot Teamwork (HRT) requirements derived from analysis of (academic and industrial) literature, standards and regulatory guidance. We extracted a construction corpus of 361 requirements from 14 cross-domain sources. Through iterative classification and refinement, we develop a two-level hierarchical taxonomy comprising 6 high-level categories and 21 low-level subcategories that distinguish information provision, relational control, decision support, safety mechanisms, performance monitoring, and foundational system capabilities. We validate the taxonomy through expert evaluation with 5 domain specialists and a utility demonstration on an independently assembled corpus of 448 requirements drawn from 19 sources spanning six HRT domains.