Andrei Sobo

Papers

Total Citations

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About

Andrei Sobo is a rising researcher at the intersection of artificial intelligence and robotics, with a primary focus on Human-Robot Interaction (HRI) and the application of Large Language Models (LLMs) to robotic systems. His most significant contribution to date is the first direct comparative study of major LLMs—ChatGPT 3.5, Gemini 1.5 Pro, and Claude 3.5 Sonnet—for generating code specifically tailored to HRI applications. This pioneering work, published in 2024 and already garnering 24 citations, systematically evaluates how these models handle the unique challenges of translating natural language commands into functional robotic behaviors. By benchmarking their performance in this niche domain, Sobo has provided the HRI community with critical insights into which LLMs are most reliable for rapid prototyping and code generation in human-robot systems. His findings help bridge the gap between conversational AI and physical robotics, offering practical guidance for developers and researchers seeking to integrate LLMs into their robotic workflows. As a young scholar, Sobo’s work signals a growing trend toward leveraging generative AI to streamline the traditionally complex process of programming interactive robots, making him a notable voice in the evolving landscape of intelligent robotics.