Fly0: Persistent Metric Anchoring for Zero-Shot Aerial Vision-Language Navigation
National Key Laboratory of Big Data and Decision（大数据与决策国家重点实验室）；National University of Defense Technology（国防科技大学）；State Key Laboratory of Digital Intelligent Modeling and Simulation（数字智能建模与仿真国家重点实验室）；Information Support Force Engineering University（信息支援力量工程大学）
Zhenxing Xu, Yihong Lu, Weidong Bao, Zhengqiu Zhu, Jingxuan Zhou, Zhichuang Wang, Ji Wang, Lihua Liu, Wei He
Current Visual-Language Navigation (VLN) methodologies face a trade-off between semantic understanding and control precision. While Multimodal Large Language Models (MLLMs) offer superior reasoning, deploying them as low-level controllers leads to high latency, trajectory oscillations, and poor generalization due to weak geometric grounding. To address these limitations, we propose Fly0, a framework that decouples semantic reasoning from geometric planning. The proposed method operates through a three-stage pipeline: (1) an MLLM-driven module for grounding natural language instructions into 2D pixel coordinates; (2) a geometric projection module that utilizes depth data to localize targets in 3D space; and (3) a geometric planner that generates collision-free trajectories. This mechanism enables robust navigation even when visual contact is lost. By eliminating the need for continuous inference, Fly0 reduces computational overhead and improves system stability. Extensive experiments in simulation and real-world environments demonstrate that Fly0 outperforms state-of-the-art baselines, improving the Success Rate by over 20\% and reducing Navigation Error (NE) by approximately 50\% in unstructured environments. Our code is available at https://github.com/xuzhenxing1/Fly0.
School of Automation Science and Engineering, South China University of Technology（华南理工大学自动化科学与工程学院）；State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences（中国科学院沈阳自动化研究所机器人重点实验室）；State Key Laboratory of Robotics and System, School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳）机械工程与自动化学院机器人与系统重点实验室）
AirHunt: Bridging VLM Semantics and Continuous Planning for Efficient Aerial Object Navigation
Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Department of Mechanical and Energy Engineering, Southern University of Science and Technology（南方科技大学机械与能源工程系）；Department of Computer Science and Engineering, Southern University of Science and Technology（南方科技大学计算机科学与工程系）；Department of Physics, Southern University of Science and Technology（南方科技大学物理系）
ViSA-Enhanced Aerial VLN: A Visual-Spatial Reasoning Enhanced Framework for Aerial Vision-Language Navigation
Tianmushan Laboratory, Beihang University（北航之梦实验室，北京航空航天大学）；Hangzhou International Innovation Institute, Beihang University（杭州国际创新研究院，北京航空航天大学）；Foshan Graduate School of Innovation, Northeastern University（佛山创新研究生学院，东北大学）；School of Aeronautic Science and Engineering, Beihang University（航空科学与工程学院，北京航空航天大学）；Faculty of Robot Science and Engineering, Northeastern University（机器人科学与工程学院，东北大学）
Vision-Language Navigation for Aerial Robots: Towards the Era of Large Language Models
Defense Innovation Institute, Chinese Academy of Military Sciences（军事科学院国防创新研究院）；Intelligent Game and Decision Laboratory（智能博弈与决策实验室）；Aerospace Information Research Institute, Chinese Academy of Sciences（中国科学院空天信息创新研究院）
Dual-Anchoring: Addressing State Drift in Vision-Language Navigation
National Key Laboratory of Human-Machine Hybrid Augmented Intelligence（人机混合增强智能国家重点实验室）；National Engineering Research Center for Visual Information and Applications（视觉信息与应用国家工程研究中心）；Institute of Artificial Intelligence and Robotics（人工智能与机器人研究院）；Xi’an Jiaotong University（西安交通大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；School of Artificial Intelligence, University of Chinese Academy of Sciences（中国科学院大学人工智能学院）；Johns Hopkins University（约翰霍普金斯大学）；Joy Future Academy, JD（京东探索研究院）
ImagineUAV: Aerial Vision-Language Navigation via World-Action Modeling and Kinodynamic Planning
Pengcheng Laboratory（鹏城实验室）；School of Computer Science and Cyber Engineering（计算机科学与网络工程学院）；Guangzhou University（广州大学）；Southern University of Science and Technology（南方科技大学）
ViVa-SAFELAND: a New Freeware for Safe Validation of Vision-based Navigation in Aerial Vehicles
Center for Research in Mathematics CIMAT（数学研究中心（CIMAT））；Centro de Investigación y de Estudios Avanzados del IPN, CINVESTAV-IPN（墨西哥理工学院高级研究中心（CINVESTAV-IPN））
Deep Learning-based Robust Autonomous Navigation of Aerial Robots in Dense Forests
Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute FGI, The National Land Survey of Finland（遥感与摄影测量系，芬兰地理空间研究 institute FGI，芬兰国家土地测绘局）
OnFly: Onboard Zero-Shot Aerial Vision-Language Navigation toward Safety and Efficiency
School of Artificial Intelligence, Sun Yat-Sen University（中山大学人工智能学院）；Southern University of Science and Technology（南方科技大学）；The Hong Kong University of Science and Technology（香港科技大学）
Openfly: A comprehensive platform for aerial vision-language navigation
Shanghai AI Laboratory（上海人工智能实验室）；Northwestern Polytechnical University（西北工业大学）；Beihang University（北航）；Shanghai Jiao Tong University（上海交通大学）；The University of Hong Kong（香港大学）；Zhejiang University（浙江大学）；University of Science and Technology of China（中国科学技术大学）；East China University of Science and Technology（东华大学）；Fudan University（复旦大学）；Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；TeleAI
Mapless Navigation of a Hybrid Aerial Underwater Vehicle with Deep Reinforcement Learning Through Environmental Generalization
Universidad Tecnológica del Uruguay (UTEC)（乌拉圭技术大学）；Centro de Ciências Computacionais (C3) of Universidade Federal do Rio Grande (FURG)（里奥格兰德联邦大学计算科学中心）；Universidade Federal de Santa Maria (UFSM)（圣玛丽亚联邦大学）
Spiking Neural Network Actor-Critic Proximal Policy Optimization Control for Autonomous UAV Navigation Through Constrained Openings in Civil Infrastructure and Buildings
Alma Mater Europaea University（欧洲阿尔马马特大学）；AGH University of Krakow（克拉科夫AGH科技大学）
HTNav: A Hybrid Navigation Framework with Tiered Structure for Urban Aerial Vision-and-Language Navigation
Nanjing University of Aeronautics and Astronautics（南京航空航天大学）；Key Laboratory of Brain-Machine Intelligence Technology, Ministry of Education（教育部脑机智能技术重点实验室）
Depth-CUPRL: Depth-Imaged Contrastive Unsupervised Prioritized Representations in Reinforcement Learning for Mapless Navigation of Unmanned Aerial Vehicles
Universidade Federal do Rio Grande - FURG（里奥格兰德联邦大学（FURG））；Universidade Federal de Santa Maria - UFSM（圣玛丽亚联邦大学（UFSM））；Technological University of Uruguay（乌拉圭技术大学）
School of Electrical Engineering and Computer Science, The University of Queensland（昆士兰大学电气工程与计算机科学学院）；CSIRO Robotics, Data61（联邦科学与工业研究组织机器人学与Data61研究院）
