Toward Interoperable Heterogeneous Mobile-Robot Fleets: A Systematic Review of Industrial Fleet Management, Cross-Layer Orchestration, and Deployment Maturity

Industrial mobile-robot fleets are evolving from homogeneous automated guided vehicle installations toward systems that combine different platforms, capabilities, navigation stacks, and interfaces. Research on fleet management is extensive but fragmented across allocation, scheduling, routing, traffic management, charging, interoperability, and execution supervision. This systematic review asks how far the field has progressed from isolated optimization functions toward heterogeneous, interoperable, and execution-aware orchestration. Scopus, Web of Science, and IEEE Xplore were searched for peer-reviewed primary studies published from 2019 to 2026. Of 524 post-venue records, 503 full texts were assessed and 491 studies were included; predefined protocols then selected 243 Core studies and 97 high-quality exemplars for in-depth synthesis. Across the 491 studies, cross-layer integration (76.6%) and runtime coordination (60.5%) are far more common than genuine robot heterogeneity (12.2%), substantive interoperability (8.1%), or deployment maturity (8.6%); only 16 studies combine heterogeneity with interoperability, and five satisfy all five dimensions. Among the 97 exemplars, only six reach the highest orchestration category, and resilience research concentrates on collisions and deadlocks rather than robot faults, communication loss, or human interaction. The review contributes a seven-level maturity model (M0–M6) with an explicit assessment workflow, an analysis of why system-level resilience remains rare, and an evidence-derived reference architecture for heterogeneous, multi-vendor industrial fleets.