Editorial: Synergizing large language models and computational intelligence for advanced robotic systems
Abstract
The convergence of foundation models, including Large Language Models (LLMs), Vision Language Action (VLA) models, with robotics and computational intelligence represents one of the most significant developments in modern AI research. Traditional robotic systems, while capable in structured environments, have long struggled with the safety, intuitive interaction, and adaptive reasoning required for real-world deployment. By integrating the natural language understanding and contextual reasoning capabilities of LLMs into robotic frameworks, researchers are now unlocking new possibilities spanning voice-driven manipulation, autonomous navigation, and human-robot interaction. This Research Topic brings together five original research articles that explore the growing role 23 of LLMs in robotic and intelligent systems. The contributions cover a broad range of applications, 24 including supermarket assistance robots, bimanual teleoperation, home-care navigation, educational 25 robots, and automated machine learning, but share a common focus: using the language and reasoning 26 capabilities of LLMs to bridge the gap between human intention and robot action. These works offer new 27 methodologies, system architectures, and empirical findings that advance our understanding of how LLMs 28 and computational intelligence can be effectively used in advanced robotic systems. achieving the lowest error rates, and language found to be a more significant source of variation than…
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