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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Online-Zugang: | https://arxiv.org/abs/2410.14989 |
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| _version_ | 1866914980385783808 |
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| author | Zhu, Longtao Yang, Hongyu Song, Ge Ma, Xin Zhang, Yanxin Ji, Yulong |
| author_facet | Zhu, Longtao Yang, Hongyu Song, Ge Ma, Xin Zhang, Yanxin Ji, Yulong |
| contents | Current flight procedure design methods heavily rely on human-led design process, which is not only low auto-mation but also suffer from complex algorithm modelling and poor generalization. To address these challenges, this paper proposes an agent-driven flight procedure design method based on large language model, named Au-toFPDesigner, which utilizes multi-agent collaboration to complete procedure design. The method enables end-to-end automated design of performance-based navigation (PBN) procedures. In this process, the user input the design requirements in natural language, AutoFPDesigner models the flight procedure design by loading the design speci-fications and utilizing tool libraries complete the design. AutoFPDesigner allows users to oversee and seamlessly participate in the design process. Experimental results show that AutoFPDesigner ensures nearly 100% safety in the designed flight procedures and achieves 75% task completion rate, with good adaptability across different design tasks. AutoFPDesigner introduces a new paradigm for flight procedure design and represents a key step towards the automation of this process. Keywords: Flight Procedure Design; Large Language Model; Performance-Based Navigation (PBN); Multi Agent; |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_14989 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | AutoFPDesigner: Automated Flight Procedure Design Based on Multi-Agent Large Language Model Zhu, Longtao Yang, Hongyu Song, Ge Ma, Xin Zhang, Yanxin Ji, Yulong Artificial Intelligence Robotics Current flight procedure design methods heavily rely on human-led design process, which is not only low auto-mation but also suffer from complex algorithm modelling and poor generalization. To address these challenges, this paper proposes an agent-driven flight procedure design method based on large language model, named Au-toFPDesigner, which utilizes multi-agent collaboration to complete procedure design. The method enables end-to-end automated design of performance-based navigation (PBN) procedures. In this process, the user input the design requirements in natural language, AutoFPDesigner models the flight procedure design by loading the design speci-fications and utilizing tool libraries complete the design. AutoFPDesigner allows users to oversee and seamlessly participate in the design process. Experimental results show that AutoFPDesigner ensures nearly 100% safety in the designed flight procedures and achieves 75% task completion rate, with good adaptability across different design tasks. AutoFPDesigner introduces a new paradigm for flight procedure design and represents a key step towards the automation of this process. Keywords: Flight Procedure Design; Large Language Model; Performance-Based Navigation (PBN); Multi Agent; |
| title | AutoFPDesigner: Automated Flight Procedure Design Based on Multi-Agent Large Language Model |
| topic | Artificial Intelligence Robotics |
| url | https://arxiv.org/abs/2410.14989 |