Title: Integrating AI, IoT, and Robotics: A Review of Frameworks, Current Trends, and the Road to Connected Robotics

Abstract

The intersection of Artificial Intelligence (AI), the Internet of Things (IoT), and Robotics has transitioned from a speculative concept to the cornerstone of contemporary real-time, intelligent, and context-sensitive systems. In this triad, AI facilitates perception and logical reasoning, IoT ensures expansive sensing capabilities and communication networks, while robotics provides physical actuation. Although substantial advancements have been made in dual integrations like AIoT and the Internet of Robotic Things (IoRT), a cohesive design framework that seamlessly unites all three disciplines remains elusive.

This survey consolidates current advancements across these fields, spotlighting the growing significance of Small Language Models (SLMs) deployed at the edge and Large Language Models (LLMs) operating in the cloud to support distributed cognition and autonomous decision-making. We introduce a modular system architecture tailored to these developments, evaluate ongoing challenges regarding interoperability and feedback control, and categorize prior research based on the depth of integration. Our analysis demonstrates that hybrid systems combining SLMs and LLMs, when supported by IoT infrastructure and robotic agents, can effectively mitigate issues related to real-time adaptation, scalability, and reliability. Ultimately, this paper presents a conceptual and technical blueprint for engineering future AI-IoT-Robotic ecosystems that are modular, transparent, and adaptive within dynamic settings, thereby establishing the foundation for the emerging era of Connected Robotics and Physical AI.

Source: arXiv Generated at: 2026-06-02 00:00:00 UTC