This paper deals with the problem of informative path planning for a UAV deployed for precision agriculture applications. First, we observe that the ``fear of missing out'' data lead to uniform, conservative scanning policies over the whole agricultural field. Consequently, employing a non-uniform scanning approach can mitigate the expenditure of time in areas with minimal or negligible real value, while ensuring heightened precision in information-dense regions. Turning to the available informative path planning methodologies, we discern that certain methods entail intensive computational requirements, while others necessitate training on an ideal world simulator. To address the aforementioned issues, we propose an active sensing coverage path planning approach, named OverFOMO, that regulates the speed of the UAV in accordance with both the relative quantity of the identified classes, i.e. crops and weeds, and the confidence level of such detections. To identify these instances, a robust Deep Learning segmentation model is deployed. The computational needs of the proposed algorithm are independent of the size of the agricultural field, rendering its applicability on modern UAVs quite straightforward. The proposed algorithm was evaluated with a simu-realistic pipeline, combining data from real UAV missions and the high-fidelity dynamics of AirSim simulator, showcasing its performance improvements over the established state of affairs for this type of missions. An open-source implementation of the algorithm and the evaluation pipeline is also available: \url{https://github.com/emmarapt/OverFOMO}.
Recent Advances in Transformer and Large Language Models for UAV Applications
LSEA Laboratory, Department of Electrical Engineering, University of Medea, 26000, Algeria（里塞阿实验室，电气工程系，梅迪亚大学，阿尔及利亚）；Institute of Technology, University Centre Salhi Ahmed, Naama, Algeria（技术研究所，萨利哈·阿赫迈德大学中心，纳马，阿尔及利亚）；Cybersecurity Institute, Department of Computer Science, University of Liverpool, L69 3BX, Liverpool, UK（网络安全研究所，计算机科学系，利物浦大学，英国）；LCPTS Laboratory, University of Sciences（LCPTS实验室，科学大学）；College of Computing（计算学院）；Data Science, Nanyang Technological University, Singapore.（数据科学，南洋理工大学，新加坡）
Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges
New Jersey Institute of Technology（新泽西理工学院）；Universiti Tenaga Nasional（国家能源大学）；Western Michigan University（西密歇根大学）；Tafila Technical University（塔菲拉技术大学）；University of Idaho（爱达荷大学）
UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobility
The State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所多模态人工智能系统国家重点实验室）；Macau University of Science and Technology（澳门科技大学）；School of Automation, Beijing Institute of Technology（北京理工大学自动化学院）；School of Software, Northwestern Polytechnical University（西北工业大学软件学院）；College of Mechanical and Vehicle Engineering, Hunan University（湖南大学机械与运载工程学院）；John von Neumann Faculty of Informatics, Obuda University（欧布达大学约翰·冯·诺依曼信息学院）
Vision-based Navigation of Unmanned Aerial Vehicles in Orchards: An Imitation Learning Approach
Department of Biological and Agricultural Engineering, University of California, Davis, Davis, CA, USA（生物与农业工程系，加州大学戴维斯分校）；Department of Mechanical and Aerospace Engineering, University of California, Davis, Davis, CA, USA（机械与航空航天工程系，加州大学戴维斯分校）
Design and Evaluation of an AI-Enabled Cloud-Edge Architecture for Connected Precision Agriculture Farms
Autonomous Robotics Systems Limited（自主机器人系统有限公司）；University of Hyderabad（海得拉巴大学）；ThoughtGreen Technologies Private Limited（ThoughtGreen科技私人有限公司）；Ideabytes Software India Private Limited（Ideabytes软件印度私人有限公司）；Georgia Institute of Technology（佐治亚理工学院）；Tata Consultancy Services（塔塔咨询服务公司）；EPAM India（埃培智印度分公司）；Kaveri University（卡弗里大学）；University of Malaya（马来亚大学）
Cooperative Multi-UAV Coverage Mission Planning Platform for Remote Sensing Applications
Democritus University of Thrace（色雷斯德谟克利特大学）；Information Technologies Institute, The Centre for Research & Technology, Hellas（希腊研究与技术中心信息技术研究所）；National Technical University（国立技术大学）
Self-Predictive Representation for Autonomous UAV Object-Goal Navigation
Escola Politécnica de Pernambuco, Universidade de Pernambuco（巴伊兰联邦大学皮奥伊技术学院）；School of Computer Science and Engineering, University of New South Wales（新南威尔士大学计算机科学与工程学院）；School of Mechanical and Manufacturing Engineering, University of New South Wales（新南威尔士大学机械与制造工程学院）；Escuela de Ingeniería, Universidad Central de Chile（智利中央大学工程学院）
Discrete Gaussian Process Representations for Optimising UAV-based Precision Weed Mapping
Lincoln Centre for Autonomous Systems (L-CAS), School of Engineering & Physical Sciences, University of Lincoln（林肯大学工程与物理科学学院林肯自主系统中心（L-CAS））；MAVLab, Faculty of Aerospace Engineering, TU Delft（代尔夫特理工大学航空航天学院MAV实验室）
An Aerial Manipulator for Perception-Driven Flower Targeting Toward Contactless Pollination in Vertical Farming
Department of Computer Science University College London London United Kingdom（计算机科学系伦敦大学学院伦敦英国）；Department of Artificial Intelligence University of Malaya Kuala Lumpur Malaysia（人工智能系马来大学吉隆坡马来西亚）；University College London（伦敦大学学院）；University of Malaya（马来大学）
Geofenced Unmanned Aerial Robotic Defender for Deer Detection and Deterrence (GUARD)
Dept. of Computer Science & Engineering, University of Minnesota（计算机科学与工程系，明尼苏达大学）；Dept. of Mechanical Engineering, University of Minnesota（机械工程系，明尼苏达大学）
Continuous World Coverage Path Planning for Fixed-Wing UAVs using Deep Reinforcement Learning
TUM School of Engineering and Design, Technical University of Munich（慕尼黑技术大学工程与设计学院）；Dept. of Electrical Engineering and Computer Sciences, University of California, Berkeley（加州大学伯克利分校电气工程与计算机科学系）
Building an Aerial-Ground Robotics System for Precision Farming: An Adaptable Solution
Sapienza University of Rome（罗马大学）；IT+Robotics Srl（IT+Robotics有限责任公司）；International Research Lab 2958 Georgia Tech-CNRS（佐治亚理工-法国国家科学研究中心2958国际研究实验室）；University of Freiburg（弗莱堡大学）；Toyota Research Institute（丰田研究院）；University of Bonn（波恩大学）；Robert Bosch GmbH（罗伯特·博世有限公司）；Agency for Agro-food Sector Services of the Marche Region (ASSAM)（马尔凯大区农业食品部门服务局）；ETH Zurich（苏黎世联邦理工学院）
