Hengjia Xiao

Papers

1

Total Citations

2

H-Index

1

About

Hengjia Xiao is a robotics researcher whose work sits at the intersection of large language models (LLMs) and autonomous navigation. His primary research areas include human-in-the-loop AI, path planning for mobile embodied agents, and interactive robotic systems. Xiao’s most notable contribution is the development of the “LLM A*” framework, a novel approach that integrates the commonsense reasoning of LLMs with the utility-optimal A* search algorithm. This framework enables robots to perform path planning in a more intuitive, human-guided manner, allowing for real-time interaction and adaptation. While still early in its citation impact, with 2 citations since 2023, the work represents a forward-looking synthesis of symbolic planning and neural language models. Xiao’s research is particularly significant for its emphasis on human-in-the-loop interaction, addressing a critical gap in making autonomous systems more transparent and controllable. His work is poised to influence the next generation of assistive and service robots, where safe, explainable, and collaborative navigation is paramount.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
LLM A*: Human in the Loop Large Language Models Enabled A* Search for Robotics
2 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 1

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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