Zhirong Luan
Papers
3
Total Citations
23
H-Index
2
About
Zhirong Luan is pioneering the integration of Large Language Models (LLMs) into robotics, focusing on task planning, multi-agent coordination, and automated development. His major contributions include a multi-layer LLM framework that enhances robot task decomposition and execution, addressing the limitations of direct LLM application for complex, real-world tasks. He also proposed a hierarchical LLM architecture within a cloud-edge-end system for controlling heterogeneous robot clusters, enabling sophisticated multi-agent strategy generation and motion control. Additionally, Luan developed a collaborative LLM framework that automates robotic development, reducing the need for intensive human involvement in task allocation and teamwork. His most cited work, “Enhancing Robot Task Planning and Execution through Multi-Layer Large Language Models” (2024), has garnered 18 citations, reflecting its timely impact. Through these innovations, Luan is advancing the frontier of autonomous robotics, making strides toward more intelligent, scalable, and collaborative robotic systems that can handle intricate, multi-domain challenges.
Research Focus
Key Achievements
Top Papers
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