2024 20th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Abu Dhabi, United Arab Emirates, 2024, pp. 339-346
Multicopter drones are becoming a key platform in several application domains, enabling precise on-the-spot sensing and/or actuation. We focus on the case where the drone must process the sensor data in order to decide, depending on the outcome, whether it needs to perform some additional action, e.g., more accurate sensing or some form of actuation. On the one hand, waiting for the computation to complete may waste time, if it turns out that no further action is needed. On the other hand, if the drone starts moving toward the next point of interest before the computation ends, it may need to return back to the previous point, if some action needs to be taken. In this paper, we propose a learning approach that enables the drone to take informed decisions about whether to wait for the result of the computation (or not), based on past experience gathered from previous missions. Through an extensive evaluation, we show that the proposed approach, when properly configured, outperforms several static policies, up to 25.8%, over a wide variety of different scenarios where the probability of some action being required at a given point of interest remains stable as well as for scenarios where this probability varies in time.
Count Every Rotation and Every Rotation Counts: Exploring Drone Dynamics via Propeller Sensing
Shenzhen International Graduate School, Tsinghua University, China（清华大学深圳国际研究生院）；The University of Hong Kong（香港大学）；Meituan Academy of Robotics Shenzhen, China（美团机器人研究院（深圳））；School of Software, Tsinghua University, China（清华大学软件学院）
Exploring Unstructured Environments using Minimal Sensing on Cooperative Nano-Drones
Computer Vision and Aerial Robotics Group at Universidad Politécnica de Madrid（马德里理工大学计算机视觉与空中机器人小组）；Centre for Automation and Robotics C.A.R. (UPM-CSIC)（自动化与机器人中心（UPM-CSIC））；Department of Mechanical Engineering, Texas A&M University（机械工程系，德克萨斯A&M大学）
EcoFlight: Finding Low-Energy Paths Through Obstacles for Autonomous Sensing Drones
Computer Science New Jersey Institute of Technology Newark, NJ, USA（计算机科学 新 jersey 理工学院 新ARK, NJ, USA）；Computer Engineering New York Institute of Technology New York, NY, USA（电子与计算机工程 新 york 理工学院 新 YORK, NY, USA）
OmniAI: A Surface-Adaptive Aerial Projection Interface for Human--Drone Interaction
Skolkovo Institute of Science and Technology（斯科尔科沃科学技术研究院）；School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳）理工学院）
Rich State Observations Empower Reinforcement Learning to Surpass PID: A Drone Ball Balancing Study
Autonomous and Interactive Mobile Systems Group (AIMS), Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University（自主与互动移动系统组（AIMS），航空与航空工程系，香港理工大学）
CubeDN: Real-time Drone Detection in 3D Space from Dual mmWave Radar Cubes
Department of Security and Crime Science, University College London（安全与犯罪科学系，伦敦大学学院）；Department of Computer Science, University College London（计算机科学系，伦敦大学学院）
mmE-Loc: Facilitating Accurate Drone Landing with Ultra-High-Frequency Localization
Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Carnegie Mellon University（卡内基梅隆大学）；Meituan Academy of Robotics Shenzhen and Meituan Inc.（美团机器人研究院（深圳）及美团公司）；School of Software and BNRist, Tsinghua University（清华大学软件学院）；Shenzhen Smart City Communication Co., Ltd.（深圳智慧城市通信有限公司）；Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；International Digital Economy Academy（国际数字经济 academy）
On Adversarial Attacks In Acoustic Drone Localization
Department of Computer Science（计算机科学系）；Technion – Israel Institute of Technology（技术ion-以色列理工学院）；School of Electrical and Computer Engineering（电气与计算机工程学院）；Ben-Gurion University of the Negev（贝内尔谢瓦大学）；Institute of Science and Technology Austria（奥地利科学与技术研究院）
Bumper Drone: Elastic Morphology Design for Aerial Physical Interaction
University of Bristol（布里斯托大学）；School of Engineering Mathematics and Technology（工程数学与技术学院）；School of Civil, Aerospace and Design Engineering（土木、航空航天与设计工程学院）；Department of Aeronautics（航空系）；Laboratory of Sustainability Robotics, EMPA（可持续机器人实验室，EMPA）
Drones Guiding Drones: Cooperative Navigation of a Less-Equipped Micro Aerial Vehicle in Cluttered Environments
Multi-robot Systems Group, Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague（多机器人系统组，控制系，电气工程系，捷克技术大学）
Ultra-High-Frequency Harmony: mmWave Radar and Event Camera Orchestrate Accurate Drone Landing
Shenzhen International Graduate School, Tsinghua University（清华大学深圳国际研究生院）；Carnegie Mellon University（卡内基梅隆大学）；Meituan Academy of Robotics Shenzhen（美团深圳机器人研究院）；School of Software, Tsinghua University（清华大学软件学院）；Pengcheng Laboratory（鹏城实验室）；RISC-V International Open Source Laboratory（RISC-V国际开源实验室）
Optimal Wildfire Escape Route Planning for Drones under Dynamic Fire and Smoke
Budapest University of Technology and Economics（布达佩斯技术与经济大学）；HUN-REN Institute for Computer Science and Control (SZTAKI)（HUN-REN计算机科学与控制研究所）；Machine Perception Research Laboratory（机器感知研究实验室）
Towards autonomous photogrammetric forest inventory using a lightweight under-canopy robotic drone
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）
