Human–autonomy teaming in smart logistics
Xuan QIU , Chun-Hsien CHEN , Kum Fai YUEN , Gangyan XU
Eng. Manag ››
With the rapid adoption of artificial intelligence (AI) and robotics in modern logistics, operations are transitioning from isolated automation toward interdependent human–autonomy teaming. However, existing research remains conceptually fragmented, often separating human–robot teaming (HRT) in physical execution from human–AI teaming (HAT) in decision-making processes. Drawing on an integrative multidisciplinary review, this paper develops a logistics-specific framework that connects these two forms of teaming through two operationally coupled layers: an information and decision layer and a physical execution layer. Synthesizing studies across application domains, teaming modes, and human-factor concerns, the review shows that prior work has largely focused on specific technologies, functions, or interaction settings, while giving limited attention to human role reconfiguration, decision authority, and meaningful oversight in integrated human–autonomy systems. Building on these insights, we establish a future research agenda centered on adaptive interaction, human-centered authority design, and networked resilience to support effective teaming under routine and disrupted conditions. This review thereby provides a foundation for conceptualizing and developing adaptive, accountable, and resilient smart logistics systems.
smart logistics / human–autonomy teaming / human–AI collaboration / human–robot collaboration / human factors
The Author(s) 2026
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