Counter and Unmanned Aerial Systems (cUAS/UAS) Vision For The Future
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45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
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Counter and Unmanned Aerial Systems (cUAS/UAS) Vision For The Future
Explore the source record for details and available documents.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
Outline for the Operational Use of Unmanned Aerial Systems During a Radiological Emergency
This is a presentation that will be given at the International Conference on the Development of Preparedness for National and International Emergency Response (EPR2021), 11–15 October 2021, in Vienna, Austria.
UAS Aerial Radiological Measurements↗
Unmanned Aerial Systems Studies for Spent Fuel Transport Security.
Abstract not provided.
Durbin, Samuel↗
Unmanned Aerial Vehicle Systems for Disaster Relief: Tornado Alley
Unmanned aerial vehicle systems are currently in limited use for public service missions worldwide. Development of civil unmanned technology in the United States currently lags behind military unmanned technology development in part because of unresolved regulatory and technological issues. Civil unmanned aerial vehicle systems have potential to augment disaster relief and emergency response efforts. Optimal design of aerial systems for such applications will lead to unmanned vehicles which provide maximum potentiality for relief and emergency response while accounting for public safety concerns and regulatory requirements. A case study is presented that demonstrates application of a civil unmanned system to a disaster relief mission with the intent on saving lives. The concept utilizes unmanned aircraft to obtain advanced warning and damage assessments for tornados and severe thunderstorms. Overview of a tornado watch mission architecture as well as commentary on risk, cost, need for, and design tradeoffs for unmanned aerial systems are provided.
DeBusk, Wesley M.↗
Case study of UAS ignition of prescribed fire in a mixedwood on the William B. Bankhead National Forest, Alabama
Abstract Background For at least four decades, practitioners have recognized advantages of aerial versus ground ignition for maximizing the effectiveness of prescribed fires. For example, larger areas can be ignited in less time, or ignition energy may be variously targeted over an area in accordance with the uneven distribution of fuels. The maturation of wireless communication, geopositioning systems, and unmanned aerial systems (UAS) has enhanced those advantages, and UAS approaches also provide further advantages relative to helicopter ignitions, such as reduced risk to human safety, lower operating costs, and higher operational flexibility. In a long running study at the Bankhead National Forest in northcentral Alabama, prescribed fire has been used for nearly 20 years. Most of the burns have been hand-ignited via drip torches, while some have been aerially ignited via helicopter. In March 2022, for the first time, a UAS was used to ignite prescribed fires across a landscape that included a long-term research stand. This field note relates comparisons of both fire behavior and fuel consumption metrics for the UAS-ignited burn versus previous burns on the same stand, and versus burns of other research stands in the same year. Results The UAS-ignited prescribed fire experienced burn effects similar to those from ground-ignited prescribed fires on the same stand in previous years, as well as those from ground-ignited prescribed fires on other stands in the same year. Conclusion This post hoc analysis suggests that UAS ignition approaches may be sufficient for achieving prescribed burn goals, thereby enabling practitioners to realize the advantages offered by that ignition mode.
Environmental Sciences & Ecology↗
Secure and Safe Assured Autonomy (S2A2)
Aviation’s future will likely see the integration of a wide variety of Advanced Air Mobility (AAM) systems including Unmanned Aerial Systems (UAS) for cargo/delivery, personal air vehicles, and commercial Urban Air Mobility (UAM)vehicles. However, substantial challenges exist that could delay (and possibly prevent) these developments and thus research is needed in a variety of areas to leverage technologies in autonomy, Air Traffic Management (ATM), multi-redundant flight systems architectures, and advanced wireless connectivity like 5G to meet these challenges. The goal of this ULI project is to develop new technologies and innovative operational concepts which will ensure safe, secure and robust integration of autonomous vehicles into Advanced Air Mobility-tailored transportation infrastructure. All this must be done while maintaining inter-operability with current civil air transportation systems and associated safety standards. The project is organized into four Technical Challenges (TCs) areas designed to provide unique UAM solutions and a transition roadmap for industry and government to utilize research product output.
Koushik Datta↗
Thermal Analysis on Cryogenic Liquid Hydrogen Tank on an Unmanned Aerial Vehicle System
Thermal analyses are performed on the liquid hydrogen (LH2) tank designed for an unmanned aerial vehicle (UAV) powered by solar arrays and a regenerative proton-exchange membrane (PEM) fuel cell. A 14-day cruise mission at a 65,000 ft altitude is considered. Thermal analysis provides the thermal loads on the tank system and the boiling-off rates of LH2. Different approaches are being considered to minimize the boiling-off rates of the LH2. It includes an evacuated multilayer insulation (MLI) versus aerogel insulation on the LH2 tank and aluminum versus stainless steel spacer rings between the inner and outer tank. The resulting boil-off rates of LH2 provided by the one-dimensional model and three-dimensional finite element analysis (FEA) on the tank system are presented and compared to validate the results of the three-dimensional FEA. It concludes that heat flux through penetrations by conduction is as significant as that through insulation around the tank. The tank system with MLI insulation and stainless steel spacer rings result in the lowest boiling-off rate of LH2.
Wang, Xiao-Yen↗
ICAROUS: Integrated Configurable Architecture for Unmanned Systems
NASA's Unmanned Aerial System (UAS) Traffic Management (UTM) project aims at enabling near-term, safe operations of small UAS vehicles in uncontrolled airspace, i.e., Class G airspace. A far-term goal of UTM research and development is to accommodate the expected rise in small UAS traffic density throughout the National Airspace System (NAS) at low altitudes for beyond visual line-of-sight operations. This video describes a new capability referred to as ICAROUS (Integrated Configurable Algorithms for Reliable Operations of Unmanned Systems), which is being developed under the auspices of the UTM project. ICAROUS is a software architecture comprised of highly assured algorithms for building safety-centric, autonomous, unmanned aircraft applications. Central to the development of the ICAROUS algorithms is the use of well-established formal methods to guarantee higher levels of safety assurance by monitoring and bounding the behavior of autonomous systems. The core autonomy-enabling capabilities in ICAROUS include constraint conformance monitoring and autonomous detect and avoid functions. ICAROUS also provides a highly configurable user interface that enables the modular integration of mission-specific software components.
Consiglio, Maria C.↗
ICAROUS - Integrated Configurable Algorithms for Reliable Operations Of Unmanned Systems
NASA's Unmanned Aerial System (UAS) Traffic Management (UTM) project aims at enabling near-term, safe operations of small UAS vehicles in uncontrolled airspace, i.e., Class G airspace. A far-term goal of UTM research and development is to accommodate the expected rise in small UAS traffic density throughout the National Airspace System (NAS) at low altitudes for beyond visual line-of-sight operations. This paper describes a new capability referred to as ICAROUS (Integrated Configurable Algorithms for Reliable Operations of Unmanned Systems), which is being developed under the UTM project. ICAROUS is a software architecture comprised of highly assured algorithms for building safety-centric, autonomous, unmanned aircraft applications. Central to the development of the ICAROUS algorithms is the use of well-established formal methods to guarantee higher levels of safety assurance by monitoring and bounding the behavior of autonomous systems. The core autonomy-enabling capabilities in ICAROUS include constraint conformance monitoring and contingency control functions. ICAROUS also provides a highly configurable user interface that enables the modular integration of mission-specific software components.
Consiglio, María↗
Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems
Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with cameras and/or LiDAR sensors are being widely used for topographic mapping in a variety of applications such as precision agriculture, coastal monitoring, and archaeological documentation. Integration of image-based and LiDAR point clouds can provide a comprehensive 3D model of the area of interest. For such integration, ensuring a good alignment between data from the different sources is critical. Although many works have been conducted on this topic, there is still a need for a rigorous integration approach that minimizes the discrepancy between camera and LiDAR data caused by inaccurate system calibration parameters and/or trajectory artifacts. This study proposes an automated tightly-coupled camera/LiDAR integration workflow for GNSS/INS-assisted UAV systems. The proposed strategy is conducted in three main steps. First, an image-based point cloud is generated using a LiDAR/GNSS/INS-assisted structure from motion (SfM) strategy. Then, feature correspondences between image-based and LiDAR point clouds are automatically identified. Finally, an integrated-bundle adjustment procedure including image points, LiDAR raw measurements, and GNSS/INS information is conducted to minimize the discrepancy between point clouds from different sensors while estimating system calibration parameters and refining the trajectory information. The proposed SfM strategy and integration framework are evaluated using five datasets. The SfM results show that using LiDAR data can facilitate feature matching and further increase the number of reconstructed 3D points. The experimental results also illustrate that the developed automated camera/LiDAR integration strategy is capable of accurately estimating system calibration parameters to achieve good alignment among camera/LiDAR data from single/multiple systems. Finally, an absolute accuracy in the range of 3–5 cm is achieved for the image/LiDAR point clouds after the integration process.
42 ENGINEERING↗
A Remote Vehicle Operations Center’s Role in Collecting Human Factors Data
The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. Data collected within the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center will be used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. Presented in this paper is an overview of ROAM, with a focus on the design components that support human factors data collection and a review of initial usability results of the facility.
Human factors↗
A Remote Vehicle Operations Center’s Role in Collecting Human Factors Data
The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. Data collected within the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center will be used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. Presented in this paper is an overview of ROAM, with a focus on the design components that support human factors data collection and a review of initial usability results of the facility.
Human factors↗
Intelligent Consequence Control by Aerial Reconnoiter Using Unmanned Systems (ICARUS)
Last minute presentation requested for EMISIG webex meeting on March 2, 2021.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
A HIRF-Map Certification Approach for UAM, AAM, and UAS Vehicles
Advanced Air Mobility (AAM), Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles will fly in airspace similar to Transport Category Rotorcraft, requiring them to meet stringent requirements for High-Intensity Radiated Fields (HIRF) certification. The environment is notably severe, particularly compared to fixed-wing aircraft, due to operations at lower altitudes. This potentially exposes the vehicles to high-power transmitters on the ground, leading to significant challenges. High-level HIRF exposure can result in avionic system upsets, interference, and undesirable effects. Shielding and circuit protection against HIRF pose significant barriers concerning size, weight, and cost, especially for emerging electric vertical take-off and landing (eVTOL) and electric short take-off and landing (eSTOL) vehicles. This paper proposes a novel HIRF protection approach, aiming to reduce costs by certifying vehicles to a "vehicle tolerance level" lower than that required for Transport Category Rotorcraft. The remaining protection is achieved by maintaining a safe distance from known HIRF sources. This distance is calculated based on the vehicle's tolerance level and transmitter characteristics, such as transmit power, antenna beamwidth, and direction. Tailored flight maps are developed to identify transmitters and avoidance zones within an operating area or along a flight path, enabling restricted vehicle operations. Vehicles with higher tolerance levels could have smaller HIRF avoidance zones, allowing them to operate closer to transmitters. Transmitter data are sourced from government databases, such as those of the Federal Communications Commission (FCC) and the National Oceanic and Atmospheric Administration (NOAA). A map tool is developed using Matlab to calculate and visualize HIRF avoidance zones based on available databases. The tool determines stand-off distances based on input vehicle tolerance levels, displaying results on various base maps depicting HIRF-restricted areas. Illustrations cover various FCC transmitters, including AM/FM/TV transmitters, satellite earth stations, and NOAA weather radars. The HIRF zones of smaller transmitters, such as land-mobile radios, pagers, microwave links, and cellular towers, are also illustrated. An example of flight planning around transmitters is provided. For now, airports and government-owned lands are excluded due to limited access to sensitive transmitter data. Despite this approach, a minimum HIRF tolerance level for vehicles may still be necessary to cover mobile devices, cellular base stations, transmitters on other AAM vehicles, and other small power devices not included in the FCC databases. The paper discusses findings and areas for improving existing databases and suggests an approach for better access to sanitized data in more restricted government databases. This method significantly deviates from the standard approach and introduces slightly higher flight-planning complexity. However, the potential cost savings are considerable. Future AAM/UAM/UAS aeronautical charts could potentially incorporate these new HIRF avoidance zones. Keywords—HIRF; Map; AAM; UAM; UAS; Advanced Air Mobility; Urban Air Mobility; Unmanned Aerial Systems; Certification.
HIRF↗
Usability Test of a Prototype UAS (Unmanned Aircraft Systems) Awareness Interface for Public Users
A tool to give the public a window into Unmanned Aerial Systems (UAS) Traffic Management (UTM) operations was created from an existing data collection tool. The interface included a map and a table showing details about UAS operations that could be queried in a number of ways. Eleven participants attended the study, successfully completing a 19-item task set in about 30 minutes. They correctly found information for 87% of the non-subjective tasks at a rate of around a minute per task, and rated the usability of the tool at the end of the session above the industry benchmark. Participants gave favorable reviews of the "public portal tool", even reporting that they would be satisfied with less information that it presented. There were one or two elements of the display that users found distracting and some navigation functions that need improvement, but on balance, the public representatives liked the features they saw in, and had few criticisms of, the public portal tool. One important issue for the small Unmanned Aerial System community to resolve will be how much or how little information should be available about UTM operations to members of the public.
Martin, Lynne H.↗
Runtime Analysis with R2U2: A Tool Exhibition Report
We present R2U2 (Realizable, Responsive, Unobtrusive Unit), a hardware- supported tool and framework for the continuous monitoring of safetycritical and embedded cyber-physical systems.With the widespread advent of autonomous systems such as Unmanned Aerial Systems (UAS), satellites, rovers, and cars, real-time, on-board decision making requires unobtrusive monitoring of properties for safety, performance, security, and system health. R2U2 models combine past-time and future-time Metric Temporal Logic, “mission time” Linear Temporal Logic, probabilistic reasoning with Bayesian Networks, and modelbased prognostics. The R2U2 monitoring engine can be instantiated as a hardware solution, running on an FPGA, or as a software component. The FPGA realization enables R2U2 to monitor complex cyber-physical systems without any overhead or instrumentation of the flight software. In this tool exhibition report, we present R2U2 and demonstrate applications on system runtime monitoring, diagnostics, software health management, and security monitoring for a UAS. Our tool demonstration uses a hardware-based processor-in-the-loop “iron-bird” configuration.
Johann Martin Schumann↗
Concept, Design, & Implementation of a Remote Vehicle Operations Center for Autonomous Missions
The National Aeronautics and Space Administration is supporting research to develop a prototype remote vehicle operations center at Langley Research Center to explore current and future advanced air mobility operations using small unmanned aerial systems vehicles as surrogates for future, larger-scale passenger carrying vehicles. The prototype facility known as the Remote Operations for Autonomous Missions (ROAM) Unmanned Aerial Systems (UAS) Operations Center is being used to explore different roles and responsibilities of remote operators managing multiple autonomous vehicles, with the goal of exploring human-autonomy teaming concepts that enable m:N operations (i.e., m operators managing N vehicles). ROAM has developed into a world-class research, development, and technology (RD&T) environment that can support both the collection of human factors data and the command and control of remote vehicles in beyond visual line of sight conditions. ROAM provides a key capability to enable full end-to-end hardware- and human-in-the-loop simulation testing, connecting with simulated small-UAS and creating a seamless Live-Virtual-Constructive (LVC) environment. This report describes the development of the ROAM UAS Operations Center from concept through design, culminating in the current implementation at NASA’s Langley Research Center.
CERTAIN↗