The capabilities of autonomous flight with unmanned aerial vehicles (UAVs) have significantly increased in recent times. However, basic problems such as fast and robust geo-localization in GPS-denied environments still remain unsolved. Existing research has primarily concentrated on improving the accuracy of localization at the cost of long and varying computation time in various situations, which often necessitates the use of powerful ground station machines. In order to make image-based geo-localization online and pragmatic for lightweight embedded systems on UAVs, we propose a framework that is reliable in changing scenes, flexible about computing resource allocation and adaptable to common camera placements. The framework is comprised of two stages: offline database preparation and online inference. At the first stage, color images and depth maps are rendered as seen from potential vehicle poses quantized over the satellite and topography maps of anticipated flying areas. A database is then populated with the global and local descriptors of the rendered images. At the second stage, for each captured real-world query image, top global matches are retrieved from the database and the vehicle pose is further refined via local descriptor matching. We present field experiments of image-based localization on two different UAV platforms to validate our results.
Deloitte LLP（德勤有限责任公司）；Royal Holloway University of London（伦敦大学皇家霍洛威学院）
The anticipated widespread use of unmanned aerial vehicles (UAVs) raises significant safety and security concerns, including trespassing in restricted areas, colliding with other UAVs, and disrupting high-traffic airspaces. To mitigate these risks, geofences have been proposed as one line of defence, which limit UAVs from flying into the perimeters of other UAVs and restricted locations. In this paper, we address the concern that existing geometric geofencing algorithms lack accuracy during the calculation of complex geofences, particularly in dynamic urban environments. We propose a new algor…
Institute for Infocomm Research (IR), A*STAR（新加坡科技研究局资讯通信研究院）；Nanyang Technological University (NTU)（南洋理工大学）；University of Illinois at Urbana-Champaign (UIUC)（伊利诺伊大学厄巴纳-香槟分校）；Singapore University of Technology and Design (SUTD)（新加坡科技设计大学）
Advances in Unmanned Aerial Vehicle (UAV) opens venues for application such as tunnel inspection. Owing to its versatility to fly inside the tunnels, it can quickly identify defects and potential problems related to safety. However, long tunnels, especially with repetitive or uniform structures pose a significant problem for UAV navigation. Furthermore, post-processing visual data from the camera mounted on the UAV is required to generate useful information for the inspection task. In this work, we design a UAV with a single rotating camera to accomplish the task. Compared to other platforms, …
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）
AG-MPBS: a Mobility-Aware Prediction and Behavior-Based Scheduling Framework for Air-Ground Unmanned Systems
School of Software Northwestern Polytechnical University Xi'an, China（软件学院西北工业大学西安中国）；Energy Development Research Institute China Southern Power Grid Guangzhou, China（能源发展研究院中国南方电网广州中国）；School of Computer Science Northwestern Polytechnical University Xi'an, China（计算机学院西北工业大学西安中国）
Research, Technology and Innovation Network (RTIN), The American College of Greece（美国希腊学院研究、技术与创新网络（RTIN））；Aalborg University（奥尔堡大学）
In this work, we study the trade-off between the reliability and the investment cost of an unmanned aerial system (UAS) consisting of a set of unmanned aerial vehicles (UAVs) carrying radio access nodes, called portable access points (PAPs)), deployed to serve a set of ground nodes (GNs). Using the proposed algorithm, a given geographical region is equivalently represented as a set of circular regions, where each circle represents the coverage region of a PAP. Then, the steady-state availability of the UAS is analytically derived by modelling it as a continuous time birth-death Markov decision…
This paper presents a data-driven optimal control policy for a micro flapping wing unmanned aerial vehicle. First, a set of optimal trajectories are computed off-line based on a geometric formulation of dynamics that captures the nonlinear coupling between the large angle flapping motion and the quasi-steady aerodynamics. Then, it is transformed into a feedback control system according to the framework of imitation learning. In particular, an additional constraint is incorporated through the learning process to enhance the stability properties of the resulting controlled dynamics. Compared wit…
In recent years, increased wildfires have caused irreversible damage to forest resources worldwide, threatening wildlives and human living conditions. The lack of accurate frontline information in real-time can pose great risks to firefighters. Though a plethora of machine learning algorithms have been developed to detect wildfires using aerial images and videos captured by drones, there is a lack of methods corresponding to drone deployment. We propose a wildfire rapid response system that optimizes the number and relative positions of drones to achieve full coverage of the whole wildfire are…
North Carolina Agricultural and Technical State University（北卡罗来纳农业技术州立大学）；Georgia Tech Research Institute（佐治亚理工研究院）
The North Carolina Agriculture and Technical State University (NC A&T) in collaboration with Georgia Tech Research Institute (GTRI) has developed methodologies for creating simulation-based technology tools that are capable of inferring the perceptions and behavioral states of autonomous systems. These methodologies have the potential to provide the Test and Evaluation (T&E) community at the Department of Defense (DoD) with a greater insight into the internal processes of these systems. The methodologies use only external observations and do not require complete knowledge of the internal proce…
Cross-Session 3D LiDAR and Camera Fusion for Robust Localization of Unmanned Aerial Vehicles in GPS-Denied Environments
School of Electrical and Data Engineering, University of Technology Sydney（悉尼大学电气与数据工程学院）；Institute of Aerospace Engineering and Technology, Duy Tan University（杜益大学航空航天工程与技术学院）；College of Engineering and Computer Science, VinUniversity（Vin大学工程与计算机科学学院）；Smart Green Transformation Center (GREEN-X), VinUniversity（Vin大学智能绿色转型中心 (GREEN-X)）；Department of Artificial Intelligence and Robotics, Sejong University（成均馆大学人工智能与机器人系）
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）
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）
Recent applications of unmanned aerial systems (UAS) to precision agriculture have shown increased ease and efficiency in data collection at precise remote locations. However, further enhancement of the field requires operation over long periods of time, e.g. days or weeks. This has so far been impractical due to the limited flight times of such platforms and the requirement of humans in the loop for operation. To overcome these limitations, we propose a fully autonomous rotorcraft UAS that is capable of performing repeated flights for long-term observation missions without any human intervent…
National Robotics Engineering Center, the Robotics Institute of Carnegie Mellon University（卡内基梅隆大学机器人研究所国家机器人工程中心）
A robotic system of multiple unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) has the potential for advancing autonomous object geolocation performance. Much research has focused on algorithmic improvements on individual components, such as navigation, motion planning, and perception. In this paper, we present a UGV-UAV object detection and geolocation system, which performs perception, navigation, and planning autonomously in real scale in unstructured environment. We designed novel sensor pods equipped with multispectral (visible, near-infrared, thermal), high resolution (…
University of New South Wales（新南威尔士大学）；Australian National University（澳大利亚国立大学）
The movement of cooperative robots in a densely cluttered environment may not be possible if the formation type is invariant. Hence, we investigate a new method for time-varying formation control for a group of heterogeneous autonomous vehicles, which may include Unmanned Ground Vehicles (UGV) and Unmanned Aerial Vehicles (UAV). We have extended a Negative-Imaginary (NI) consensus control approach to switch the formation shape of the robots whilst only using the relative distance between agents and between agents and obstacles. All agents can automatically create a new safe formation to overco…
As unmanned aerial systems (UASs) increasingly integrate into the US national airspace system, there is an increasing need to characterize how commercial and recreational UASs may encounter each other. To inform the development and evaluation of safety critical technologies, we demonstrate a methodology to analytically calculate all potential relative geometries between different UAS operations performing inspection missions. This method is based on a previously demonstrated technique that leverages open source geospatial information to generate representative unmanned aircraft trajectories. U…
In this article we propose a reactive constrained navigation scheme, with embedded obstacles avoidance for an Unmanned Aerial Vehicle (UAV), for enabling navigation in obstacle-dense environments. The proposed navigation architecture is based on Nonlinear Model Predictive Control (NMPC), and utilizes an on-board 2D LiDAR to detect obstacles and translate online the key geometric information of the environment into parametric constraints for the NMPC that constrain the available position-space for the UAV. This article focuses also on the real-world implementation and experimental validation of…
