Physical Agentic AI: An Architecture for Orchestrating a Robot Crew with LLMs
Agentic AI frameworks interpret open-ended task goals and decompose them into multi-step plans. Richer information about embodiment-specific capabilities, physical preconditions, and cross-robot coordination improves grounding, but does not eliminate infeasible, mistimed, or unsafe physical actions. Physical robot crews therefore require an explicit architectural interface between semantic planning and execution, where every planned action is verified against robot capabilities, system state, and workflow constraints before actuation. This paper introduces Physical Agentic AI, a framework for skill-grounded robot agent orchestration, in which each robot exposes a typed library of executab...
| Authors | Xinyuan Liu, Eren Sadikoglu, Riana Chatterjee et al. |
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| Primary category | cs.RO |
| Published | 23 August 2026 |
| Last updated at source | 23 August 2026 |
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