AirNav: A Large-Scale Real-World UAV Vision-and-Language Navigation Dataset with Natural and Diverse Instructions

• URL: http://arxiv.org/abs/2601.03707v1
• Date: Wed, 07 Jan 2026 08:46:09 GMT
• Title: AirNav: A Large-Scale Real-World UAV Vision-and-Language Navigation Dataset with Natural and Diverse Instructions
• Authors: Hengxing Cai, Yijie Rao, Ligang Huang, Zanyang Zhong, Jinhan Dong, Jingjun Tan, Wenhao Lu, Renxin Zhong,
• Abstract summary: We propose AirNav, a large-scale UAV VLN benchmark constructed from real urban aerial data.<n>We also introduce the AirVLN-R1, which combines Supervised Fine-Tuning and Reinforcement Fine-Tuning to enhance performance and generalization.
• Score: 6.369522034276603
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Existing Unmanned Aerial Vehicle (UAV) Vision-Language Navigation (VLN) datasets face issues such as dependence on virtual environments, lack of naturalness in instructions, and limited scale. To address these challenges, we propose AirNav, a large-scale UAV VLN benchmark constructed from real urban aerial data, rather than synthetic environments, with natural and diverse instructions. Additionally, we introduce the AirVLN-R1, which combines Supervised Fine-Tuning and Reinforcement Fine-Tuning to enhance performance and generalization. The feasibility of the model is preliminarily evaluated through real-world tests. Our dataset and code are publicly available.

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