An Open-source Hardware/Software Architecture and Supporting Simulation Environment to Perform Human FPV Flight Demonstrations for Unmanned Aerial Vehicle Autonomy
University at Buffalo（布法罗大学）
Haosong Xiao, Prajit Krisshnakumar, Jagadeswara P K V Pothuri, Puru Soni, Eric Butcher, Souma Chowdhury
Small multi-rotor unmanned aerial vehicles (UAVs), mainly quadcopters, are nowadays ubiquitous in research on aerial autonomy, including serving as scaled-down models for much larger aircraft such as vertical-take-off-and-lift vehicles for urban air mobility. Among the various research use cases, first-person-view RC flight experiments allow for collecting data on how human pilots fly such aircraft, which could then be used to compare, contrast, validate, or train autonomous flight agents. While this could be uniquely beneficial, especially for studying UAV operation in contextually complex and safety-critical environments such as in human-UAV shared spaces, the lack of inexpensive and open-source hardware/software platforms that offer this capability along with low-level access to the underlying control software and data remains limited. To address this gap and significantly reduce barriers to human-guided autonomy research with UAVs, this paper presents an open-source software architecture implemented with an inexpensive in-house built quadcopter platform based on the F450 Quadcopter Frame. This setup uses two cameras to provide a dual-view FPV and an open-source flight controller, Pixhawk. The underlying software architecture, developed using the Python-based Kivy library, allows logging telemetry, GPS, control inputs, and camera frame data in a synchronized manner on the ground station computer. Since costs (time) and weather constraints typically limit numbers of physical outdoor flight experiments, this paper also presents a unique AirSim/Unreal Engine based simulation environment and graphical user interface aka digital twin, that provides a Hardware In The Loop setup via the Pixhawk flight controller. We demonstrate the usability and reliability of the overall framework through a set of diverse physical FPV flight experiments and corresponding flight tests in the digital twin.
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）
Agentic UAVs: LLM-Driven Autonomy with Integrated Tool-Calling and Cognitive Reasoning
AlfaisalX: Center of Excellence of Cognitive Robotics and Autonomous Agents（阿尔法西尔研究中心：认知机器人与自主代理中心）；Alfaisal University（阿尔法西尔大学）；Prince Sultan University（普森大学）
BIM-Discrepancy-Driven Active Sensing for Risk-Aware UAV-UGV Navigation
Department of Electrical and Computer Engineering, University of California San Diego, La Jolla, CA, USA（电气与计算机工程系，加州大学圣地亚哥分校）；Department of Civil, Construction, and Environmental Engineering, San Diego State University, San Diego, CA, USA（土木、建设与环境工程系，圣地亚哥州立大学）
Machine Learning-Aided Operations and Communications of Unmanned Aerial Vehicles: A Contemporary Survey
CISTER - Research Centre in Real-Time and Embedded Computing Systems（CISTER实时与嵌入式计算系统研究中心）；The Hong Kong Polytechnic University（香港理工大学）；Commonwealth Scientific and Industrial Research Organization (CSIRO)（联邦科学与工业研究组织（CSIRO））；University of Manitoba（曼尼托巴大学）
VIRGA: Virtual-Agent-Intermediated Riemannian Geometry for Active-Sensing Air-Ground Coordination
Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University（同济大学上海自主智能无人系统科学中心）；State Key Laboratory of Autonomous Intelligent Unmanned Systems, Tongji University（同济大学自主智能无人系统全国重点实验室）；College of Electronic and Information Engineering, Tongji University（同济大学电子与信息工程学院）
Long-Duration Fully Autonomous Operation of Rotorcraft Unmanned Aerial Systems for Remote-Sensing Data Acquisition
University of Washington（华盛顿大学）；Alpen-Adria-Universität Klagenfurt（克拉根福阿尔卑斯-亚德里亚大学）；Jet Propulsion Laboratory（喷气推进实验室）；California Institute of Technology（加州理工学院）；ETH Zürich（苏黎世联邦理工学院）
BGC-Nav: Cross-Altitude Multi-UAV Collaborative Navigation via Belief-Guided Coupling
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）
Fully Onboard Low-Power Localization with Semantic Sensor Fusion on a Nano-UAV using Floor Plans
IDSIA, Universita della Svizzera italiana（IDSIA，瑞士意大利语大学）；Integrated Systems Laboratory / Center for Project-Based Learning - ETH Zürich（苏黎世联邦理工学院集成系统实验室/项目式学习中心）；Department of Electrical, Electronic and Information Engineering - University of Bologna（博洛尼亚大学电气、电子与信息工程系）
Neural 3D Object Reconstruction with Small-Scale Unmanned Aerial Vehicles
i2CAT Foundation（i2CAT基金会）；University of Klagenfurt（克雷格弗特大学）；Universitat Politècnica de Catalunya（巴塞罗那理工大学）；Faculty of Electrical Engineering and Computing（电气工程与计算学院）；University of Zagreb（扎格雷布大学）；NEC Labs Europe GmbH（NEC欧洲实验室）；ICREA
Leveraging Cloud-Fog Automation for Autonomous Collision Detection and Classification in Intelligent Unmanned Surface Vehicles
Deakin University（德克萨斯大学）；University of Birmingham（伯明翰大学）；RMIT University（皇家墨尔本理工学院）；VinUniversity（文大学）；Swinburne University of Technology（斯威本技术大学）；University of Tasmania（塔斯马尼亚大学）
Ultra-Fusion: A Resilient Tightly-Coupled Multi-Sensor Fusion SLAM Framework under Sensor Degradation and Spatiotemporal Perturbation for Intelligent Transportation Systems
Beijing Institute of Technology（北京理工大学）；Chongqing University（重庆大学）；Sichuan University（四川大学）；Northwestern Polytechnical University（西北工业大学）；Shanghai Jiao Tong University（上海交通大学）
