Intelligent Human–Robot Interaction: AI, LLMs, and Adaptive Control

Dear Colleagues,

Human–robot interaction (HRI) is entering a new era shaped by rapid advancements in artificial intelligence, foundation models, embodied intelligence, and adaptive control. Robots are no longer limited to structured environments or predefined tasks; instead, they are evolving into intelligent partners capable of understanding human instructions, inferring intentions, adapting to uncertainties, and collaborating seamlessly across diverse application domains. These capabilities are driven by breakthroughs in large language models (LLMs), vision–language models (VLMs), multi-agent coordination frameworks, and physical AI.

This Special Issue aims to gather together pioneering research that pushes beyond traditional robotics and explores the next generation of intelligent HRI across manufacturing, healthcare, smart homes, logistics, service robotics, space, construction, and other domains. We welcome contributions that advance theoretical foundations, algorithmic innovations, system integration, and the real-world deployment of intelligent human–robot interactions. 

Topics of Interest

(1) AI-Enabled Interaction and Cognitive Collaboration

• LLMs, VLMs, and multimodal foundation models for reasoning and task decomposition;
• Human intention understanding, behavior prediction, and cognitive modeling;
• Multi-agent systems for cooperative human–robot teamwork and distributed decision-making.

(2) Embodied Intelligence and Physical AI

• Compliant and adaptive control for safe physical collaboration;
• Dexterous manipulation, physical reasoning, and skill adaptation;
• Physics-informed learning, sim-to-real transfer, and world-model-based interaction.

(3) Perception and Environment Understanding

• Open-vocabulary perception and semantic scene representation;
• Tactile, force, audio, and physiological sensing for enriched interaction;
• Human state estimation, affect recognition, and ergonomic assessment.

(4) Interaction-Aware Planning and Execution

• Hybrid planning with LLM-based cognition, reasoning, and controllers;
• Uncertainty handling, risk prediction, and task execution;
• Human-in-the-loop control and mixed-initiative interaction strategies.

(5) Human-Centric Systems and Applications

• XR/VR/MR interfaces, metaverse-enabled HRI, and digital twin;
• Knowledge transfer, demonstration learning, and skill augmentation;
• Applications in manufacturing, healthcare, smart homes, logistics, construction, and field robotics.

Dr. Shufei Li
Dr. Zuoxu Wang
Dr. Sichao Liu
Guest Editors

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