Robotic Foundation Models for Industrial Control: A Comprehensive Survey and Readiness Assessment Framework

• URL: http://arxiv.org/abs/2603.06749v1
• Date: Fri, 06 Mar 2026 11:23:00 GMT
• Title: Robotic Foundation Models for Industrial Control: A Comprehensive Survey and Readiness Assessment Framework
• Abstract summary: This survey gives an overview over the RFM-landscape and analyses, driven by concrete implications.<n>We synthesise industrial deployment perspectives into eleven interdependent implications.<n>We evaluate 324 manipulation-capable RFMs via 48,276 criterion-level decisions.
• Score: 8.463273762997398
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Robotic foundation models (RFMs) are emerging as a promising route towards flexible, instruction- and demonstration-driven robot control, however, a critical investigation of their industrial applicability is still lacking. This survey gives an extensive overview over the RFM-landscape and analyses, driven by concrete implications, how industrial domains and use cases shape the requirements of RFMs, with particular focus on collaborative robot platforms, heterogeneous sensing and actuation, edge-computing constraints, and safety-critical operation. We synthesise industrial deployment perspectives into eleven interdependent implications and operationalise them into an assessment framework comprising a catalogue of 149 concrete criteria, spanning both model capabilities and ecosystem requirements. Using this framework, we evaluate 324 manipulation-capable RFMs via 48,276 criterion-level decisions obtained via a conservative LLM-assisted evaluation pipeline, validated against expert judgements. The results indicate that industrial maturity is limited and uneven: even the highest-rated models satisfy only a fraction of criteria and typically exhibit narrow implication-specific peaks rather than integrated coverage. We conclude that progress towards industry-grade RFMs depends less on isolated benchmark successes than on systematic incorporation of safety, real-time feasibility, robust perception, interaction, and cost-effective system integration into auditable deployment stacks.

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