TPML: Task Planning for Multi-UAV System with Large Language Models

被引:1
|
作者
Cui, Jinqiang [1 ]
Liu, Guocai [1 ]
Wang, Hui [1 ]
Yu, Yue [1 ,2 ]
Yang, Jiankun [1 ]
机构
[1] Peng Cheng Lab, Shenzhen, Peoples R China
[2] Natl Univ Def Technol, Changsha, Peoples R China
来源
2024 IEEE 18TH INTERNATIONAL CONFERENCE ON CONTROL & AUTOMATION, ICCA 2024 | 2024年
关键词
D O I
10.1109/ICCA62789.2024.10591846
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Efficient task planning is pivotal for multi-UAV systems navigating dynamic environments. Traditional task planning methods face challenges in adapting to the constantly changing scenarios. The emergence of large language models (LLMs) offers promising solutions to bridge this gap. Our proposal, TPML, leverages LLMs as a command interface to comprehend operators' intentions and translate them into executable codes. Harnessing the creative capabilities of generative models, TPML can command multiple UAVs in both synchronous and asynchronous patterns with a single natural-language input. Experimental results are initially validated in a tailored simulation environment before transitioning to practical implementations. Successful demonstrations of both synchronous and asynchronous missions in real-world scenarios underscore the efficacy of TPML.
引用
收藏
页码:886 / 891
页数:6
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