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Splitting neural network inference between robots and edge servers can significantly enhance real-time perception in 5G-connected autonomous systems.
This paper provides a systematic mapping of IMT-2030 key performance indicators to robotic functional blocks including sensing, perception, cognition, actuation and self-learning and proposes a high-level architectural framework integrating robotic, intelligent, and network service planes, underscoring the need for a holistic approach.
