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This is a Experimental Study study.

September 20, 2025

Code-BT: A Code-Driven Approach to Behavior Tree Generation for Robot Tasks Planning with Large Language Models

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Code-BT improves task planning in robotics by automating behavior tree generation, suggesting increased efficiency and adaptability.

Code-BT enhances task planning by automating behavior tree generation, streamlining complex robotic tasks.
Improvements in the performance of large language models for behavior tree generation range from 16.67% to 29.17%.
This approach retrieves control flow information to efficiently construct behavior trees based on task instructions and APIs.
Automation of behavior tree generation offers scalability and adaptability for diverse and long-term task requirements.

Zhang et al. (2025) studied this question.

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