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At least 55 records · Page 3

Distributed Sensor Fusion of Ground and Air Nodes Using Vision and Radar Modalities for Tracking Multirotor Small Uncrewed Air Systems and Birds

High-density airspace operations with multiple aircraft type and potentially noncooperative aircraft require distributed sensor detection and tracking systems to monitor airspace for safe, autonomous flight operations for advanced air mobility, urban air mobility, and high density small uncrewed air systems (SUAS) flight concepts. This work collected data using a distributed radar and camera sensor framework during the NASA Advanced Air Mobility High Density Vertiplex project SUAS flight operation. Node locations include on an onboard SUAS, affixed to the Landing and Impact Research Facility with approximate 200ft elevation, on a tripod on first-floor roof with an approximate elevation of 20 ft, and on a tripod on a concrete pad that is approximately 4 ft above sea level. Each node includes camera, radar, and GPS.

Beyond Visual Line of Sight↗

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↗

Visual and Inertial Datasets for an eVTOL Aircraft Approach and Landing Scenario

A National Aeronautics and Space Administration (NASA) project developing computer vision algorithms for autonomous flight is producing real-world datasets with cameras mounted on aircraft. In related domains, such as autonomous driving, open datasets are key to innovation and advancement in computer vision and autonomous perception for future Advanced Air Mobility (AAM) operations. Few vision datasets, however, are publicly available in the aviation context. This paper introduces preliminary datasets containing several examples of approach and landing scenarios. The platform aircraft include a multirotor small unmanned aerial system (sUAS) and a crewed helicopter as surrogates for future electric vertical take-off and landing (eVTOL) aircraft. The dataset provides video imagery with associated inertial navigation system-global positioning system (INS-GPS) position and attitude estimates and other sensors. Surveyed locations of the visual features of the landing area are included. This dataset is the first to be released in an ongoing effort to collect and share large, diverse datasets relevant to autonomous aviation; community critique that can inform and improve future flight campaigns is welcome.

Nelson Brown↗

High Density Vertiplex: Scalable Autonomous Operations Prototype Assessment Simulation

Urban Air Mobility (UAM) is a rapidly growing topic within the field of aviation because of the impact a refined ecosystem and uncrewed aerial vehicles could have on modern society, such as urban air mobility, cargo, and emergency transport. Before the UAM concept can be actualized, research is needed to understand how to integrate these new classes of vehicles and operations into the National Airspace System. One under-researched but critical piece of infrastructure required for UAM operations is Vertiport operations. Vertiports are the envisioned takeoff and landing locations for these uncrewed aerial vehicles. To accommodate the high use of the vertiport, new technologies and roles will be required for optimal use. At NASA, the High Density Vertiplex sub-project targets research into vertiports. The High Density Vertiplex team created an Urban Air Mobility ecosystem to test and evaluate different concepts and tools used to support higher density operations at vertiports. Part of the test and evaluation included the Prototype Assessment Operations simulation of highdensity operations around a vertiport to study vertiport management and vertiport operations. The research team also evaluated how the prototype Urban Air Mobility ecosystem supported fleet managers, ground control station operators, and vertiport managers in execution of nominal and off-nominal high-density operations. Results from this simulation provided insight regarding UAM ecosystem research and development and vertiport automation systems.

Small Uncrewed Aerial Vehicle (sUAS)↗

High Density Vertiplex: Scalable Autonomous Operations Prototype Assessment Simulation

Urban Air Mobility is a rapidly growing topic within the field of aviation because of the impact a refined ecosystem and uncrewed aerial vehicles could have on modern society, such as urban air, cargo, and emergency transport. Before the UAM concept can be actualized, research is needed to understand how to integrate these new classes of vehicles and operations into the National Airspace System. One under-researched but critical piece of infrastructure required for UAM operations is Vertiport operations. Vertiports are the envisioned takeoff and landing locations for these uncrewed aerial vehicles. To accommodate the high use of the vertiport, new technologies and roles will be required for optimal use. At NASA, the High Density Vertiplex sub-project targets research into vertiports. The High Density Vertiplex team created their own Advanced Air Mobility ecosystem to test and evaluate different concepts and tools used to support higher density operations at vertiports. Part of the test and evaluation included the Prototype Assessment Operations simulation of high-density operations around a vertiport to study vertiport management and vertiport operations. The research team also evaluated how their simulated Urban Air Mobility ecosystem supported fleet managers, ground control station operators, and vertiport managers in execution of nominal and off-nominal high-density operations. Takeaways from this simulation helped the team evaluate well how the users of the ecosystem were able to use the components of the ecosystem to complete Urban Air Mobility missions.

Small Uncrewed Aerial Vehicle (sUAS)↗

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗

Off-Nominal Event Analysis in Autonomous Flights Based on Explainable Artificial Intelligence

A key objective in the Urban Air Mobility program at NASA is to intelligently perform an autonomous flight in a complex urban environment under all weather conditions with guaranteed levels of safety. To accomplish this, the mission manager (central decision-making module) of the vehicle needs to make informed decisions between various Courses of Action (CoA) based on its' interpretation of the inputs it receives. If an off-nominal event is detected either based on the amalgamation of sensor data or the use of machine learning models, the mission manager may greatly benefit from identification of the input features that most likely contributed to that specific event. Such an understanding is usually not possible to obtain from the classical machine learning models (deep learning) due to the inherent black box like structure. However, this understanding is achieved using eXplainable Artificial Intelligence (XAI) models that provide a human interpretable rationale for the predictions made. This work presents a game theory inspired XAI model for the off-nominal assessment of autonomous flights. The proposed approach based on Shapley values is model agnostic, provides local as well as global explanation and satisfies the four axioms (efficiency, symmetry, dummy, additivity) to achieve fair contribution. The versatility of the approach is first demonstrated on a simulated dataset in which the significance of each input to flight phase prediction is clearly identified. Subsequently, data from simulated flight trajectories are fed into the model which reveal the input features that most likely contributed to a rotor failure event thereby empowering the mission manager to take the appropriate CoA.

autonomy↗

Perception Testing in Fog for Autonomous Flight

As the path towards Urban Air Mobility (UAM) continues to take shape, there are outstanding technical challenges to achieving safe and effective air transportation operations under this new paradigm. To inform and guide technology development for UAM, NASA is investigating the current state-of-the-art in key technology areas including traffic management, detect-and-avoid, and autonomy. In support of this effort, a new perception testbed was developed at NASA Ames Research Center to collect data from an array of sensing systems representative of those that could be found on a future UAM vehicle. This testbed, featuring a Light-Detection-and-Ranging (LIDAR) instrument, a long-wave infrared sensor, and a visible spectrum camera was deployed for a multiday test campaign in the Fog Chamber at Sandia National Laboratories (SNL), in Albuquerque, New Mexico. During the test campaign, fog conditions were created for tests with targets including a human, a resolution chart, and a small unmanned aerial vehicle (sUAV). Here, this paper describes in detail, the developed perception testbed, the experimental setup in the fog chamber, the resulting data, and presents an initial result from analysis of the data with the evaluation of methods to increase contrast through filtering techniques.

aeronautics↗

Perception Testing in Fog for Autonomous Flight

As the path towards Urban Air Mobility (UAM) continues to take shape, there are outstanding technical challenges to achieving safe and effective air transportation operations under this new paradigm. To inform and guide technology development for UAM, NASA is investigating the current state-of-the-art in key technology areas including traffic management, detect-and-avoid, and autonomy. In support of this effort, a new perception testbed was developed at NASA Ames Research Center to collect data from an array of sensing systems representative of those that could be found on a future UAM vehicle. This testbed, featuring a Light-Detection-and-Ranging (LIDAR) instrument, a long-wave infrared sensor, and a visible spectrum camera was deployed for a multiday test campaign in the Fog Chamber at Sandia National Laboratories (SNL), in Albuquerque, New Mexico. During the test campaign, fog conditions were created for tests with targets including a human, a resolution chart, and a small unmanned aerial vehicle (sUAV). This paper describes in detail, the developed perception testbed, the experimental setup in the fog chamber, the resulting data, and presents an initial result from analysis of the data with the evaluation of methods to increase contrast through filtering techniques.

advanced air mobility↗

M.I.N.G., Mars Investment for a New Generation: Robotic construction of a permanently manned Mars base

A basic procedure for robotically constructing a manned Mars base is outlined. The research procedure was divided into three areas: environment, robotics, and habitat. The base as designed will consist of these components: two power plants, communication facilities, a habitat complex, and a hangar, a garage, recreation and manufacturing facilities. The power plants will be self-contained nuclear fission reactors placed approx. 1 km from the base for safety considerations. The base communication system will use a combination of orbiting satellites and surface relay stations. This system is necessary for robotic contact with Phobos and any future communication requirements. The habitat complex will consist of six self-contained modules: core, biosphere, science, living quarters, galley/storage, and a sick bay which will be brought from Phobos. The complex will be set into an excavated hole and covered with approximately 0.5 m of sandbags to provide radiation protection for the astronauts. The recreation, hangar, garage, and manufacturing facilities will each be transformed from the four one-way landers. The complete complex will be built by autonomous, artificially intelligent robots. Robots incorporated into the design are as follows: Large Modular Construction Robots with detachable arms capable of large scale construction activities; Small Maneuverable Robotic Servicers capable of performing delicate tasks normally requiring a suited astronaut; and a trailer vehicle with modular type attachments to complete specific tasks; and finally, Mobile Autonomous Rechargeable Transporters capable of transferring air and water from the manufacturing facility to the habitat complex.

Amos, Jeff↗

NASA Electric Vertical Takeoff and Landing (eVTOL) Aircraft Technology for Public Services – A White Paper

History has shown that our personal life is highly dependent on the technology that people have developed. A strategic scan of the aerospace environment at the beginning of the 21st century strongly suggests that the world might be approaching a new age of airpower—the era of electrified/hybrid aircraft propulsion. Undeniably, starting from the Montgolfier Brothers balloon flight in 1783, to the Wright Brothers piston engine flight in 1903, and the jet engine of the 1960s, or the space age of today, one can say that leaps in propulsion technology have marked the different ages of human flight. The technological advancements, brought at the beginning of 21st century by the revolution in data exchange, computational power, sensors, wireless communication, internet, and autonomy, contributed to the vision of this new age of propulsion we are approaching. Historically, conventional vertical takeoff and landing (VTOL) aircraft have been equipped with propulsion units relying on complex internal combustion machines (turbines, piston engines, for example), and complex mechanical arrangements (gearboxes, shafts, variable pitch propeller). By contrast, electric VTOL aircraft (eVTOL)1 rely on simpler propulsion units (electric motors and in some cases fixed-pitch propellers). This promotes redundancy and improves tolerance to failures, in turn improving safety. The use of simpler electric propulsion units should also allow significant acquisition and operating cost reductions. Whether full-electric (relying solely on batteries) or hybrid-electric (relying on a combination of batteries, fuel-powered engines, and generators.), eVTOLs are also expected to generate less noise and air pollution than conventional aircraft with similar payloads. According to the 2019 Annual Review of IATA (International Air Transport Association) [ref.1], due to an expected increase in air transport traffic by 5% every year and a doubling of air transport passenger numbers to 8.2 billion by 2037 significant challenges are posed to the aviation industry. Furthermore, this report does not factor in the expected demand for short-range (intra-city) air transportation, which is in development and yet to be operational. The increased demand to fly creates a responsibility to expand in a sustainable manner and an endeavor to develop more environmentally-friendly aircraft. eVTOL aircraft, either piloted or autonomous, is gathering considerable interest worldwide. Modern and novel full-electric or hybrid-electric eVTOL configurations enable a new paradigm shift in air transportation as the aviation industry remains committed to its goals of carbon-neutral growth from 2020 onwards and cutting CO2 emissions to half 2005 levels by 2050. While electric power has been used for decades, recent developments in mobile electric/hybrid propulsion coupled with advanced materials and autonomous systems may create the possibility to transition into the next age of air mobility propelled by electric/hybrid VTOL aircraft technology. Although eVTOL aircraft might seem like an incremental improvement or even a counterintuitive regression with regard to past VTOL development, it has in fact the potential to transform air mobility across a wide range of government applications. Previous transformations in aviation generated dramatic leaps in performance, but the cost was commensurate with performance, limiting quantity produced. This next age appears to take a different approach. Performance may not increase, but at this moment technology is poised for future urban mobility that will spawn commercial passenger drone services, that is, autonomous (pilotless) air taxis and thereby add a new dimension to the urban transportation mix of the future [ref. 2]. Advances in electric propulsion, autonomous flight technology, and 5G communication networks will enable this fast new-growing market to become a reality. It is now time to envision the introduction of electric/hybrid eVTOL aircraft for Public Services2. We believe that in the next decades eVTOL aircraft will have the potential to become an essential tool to Public Service agencies around the world in applications such as firefighting, public safety, search and rescue, disaster relief and law enforcement. This is due to several major factors. • First, with the increasing popularity of small, unmanned aircraft vehicles (UAVs) or drones, many companies today are focusing on the development of passenger UAVs designed to accommodate up to five passengers or equivalent cargo payload. Many such configurations are electric or hybrid-electric designs with VTOL capabilities. Several of these projects have started a flight test program and many more are expected to be in the experimental and development phase in 2020. Such revolutionary vehicles could be in commercial operations by 2030. These eVTOL systems could be ready for selected Public Services missions even sooner. • Second, although these advanced eVTOL vehicles under development still need access to fuel (hybrid) and/or electric charging capability, they can take off and land from almost anywhere. Therefore, such vehicles, both manned and unmanned can be successfully integrated for the critical missions of the Public Services with extra deployment flexibilities. • Third, advancement in electric propulsion systems in the automotive industry together with NASA’s leading efforts in electrification of aircraft propulsion systems, FAA’s ongoing active eVTOL certification programs, and EASA’s proposed framework for the certification of electric/hybrid small category VTOL aircraft in Europe [ref. 3] will help accelerate industry electric propulsion system development and integration. • Finally, eVTOL vehicles could be deployed for Public Services sooner than air taxi or other commercial applications, since Public Services missions may be more easily approved based on specific mission criteria, localized airworthiness authority for public-use aircraft3, and are normally operating under centralized airspace management and control by the theater command. Moreover, public perception and acceptance are generally less of a concern when operations save lives and benefit the wider community. The prioritized introduction of eVTOL aircraft in Public Services is ambitious, but we believe it is achievable in the coming decades if fundamental enablers (people and technologies) are engaged in defining the objectives and needs of these missions. The revolution that is currently taking place in eVTOL aircraft represents an unprecedented opportunity to develop a safer, more affordable, more available and more environmentally friendly future of vertical flight. To ensure that these novel aircraft meet the future expectations of Public Services, it is essential to take a collaborative and multi-disciplinary approach to their development, across engineering disciplines, policy-making, program management, business case development, manufacturing, and flight demonstrations. It should be noted that the term eVTOL (in the near term) used throughout this publication implies aircraft capable of transporting up to 5 persons which may or may not include a pilot if operated fully autonomously, assuming an average of 200 pounds (91 kg) per person or equivalent payload and a range up to 60 miles plus a suitable reserve. Hybrid or hydrogen powered eVTOLs would have greater range. For example, a “3-seat” eVTOL aircraft may only be able to carry two fully equipped firemen, and payload capacity is more relevant when used for the supply mission. Moreover, this paper concentrates on the “last-mile” solutions with a deployment time of no more than 6 hours. Although not specifically discussed in this document, it is understood that the future of Transformative Vertical Flight in general and Public Services, in particular, will also involve smaller UAVs that will undoubtedly play a crucial role in future aerial operations. For example, smaller unmanned aircraft may be used to dispatch medical supplies, portable filtration systems or perform the Search task of future Search and Rescue (SAR) operations. Close collaboration between the aircraft industry, the Civil Aviation Authorities (CAA), e.g., Federal Aviation Administration (FAA), European Aviation Safety Agency (EASA), Transport Canada Civil Aviation (TCCA) and the Department of Defense (DoD) certifiers, will help identify Public Services requirements, define expectations and limit development cost and timescales. Take the US Air Force Agility Prime as an example, the majority of the eVTOL application opportunities and mission elements identified are in line with the NASA TVF WG-4 objectives and use cases. Together, it forms a strong partnership to accelerate the development, certification, and practical deployment for public service missions. The US Air Force Agility Prime has been a collaboration partner on this white paper, and provided valuable input and recommendations. Most of the eVTOL public service mission elements discussed in this paper and additional use cases envisioned by the NASA TVF WG-4 team are shared by the Agility Prime program. The focus and efforts of the Agility Prime in product and system development, industry and government partnership, accelerated certifications as well as early test and deployment are totally in sync with the path forward recommended by this white paper. This kind of collaboration and partnership will help enable the practical use of the eVTOL for public service missions, benefit the eVTOL public acceptance, and accelerate the eVTOL industry revolution.

Johnny T. Doo↗

Designing a Flight Test of a Flight Path Management System for Advanced Air Mobility Research

The National Aeronautics and Space Administration (NASA) has completed a flight test to evaluate the performance of an onboard prototype automation system operating in future high density urban airspace. The test was part of a research investigation of the Urban Air Mobility (UAM) concept, with a focus on a future environment having hundreds of simultaneous operations over a metropolitan area. The complexity of this future UAM airspace may require automation capable of replanning an aircraft’s path in the presence of traffic and other changing constraints. A live-virtual-constructive (LVC) approach was used to conduct the test. Prototype automation technology was integrated into one of the two live aircraft, which were combined with virtual traffic to create a mixed reality environment at the target airspace density. In-flight evaluation enabled verification of the automation’s functions and discovery of any unexpected behaviors resulting from its operation in an actual flight environment. The in-flight evaluation also provided data for validation of air traffic simulations. This paper discusses the design, methodology, and challenges overcome to conduct a successful flight test. Remaining challenges, future work, and recommendations to improve the flight test capability are also discussed.

Advanced Air Mobility↗

Experimental Testing of Data Fusion in A Distributed Ground-Based Sensing Network for Advanced Air Mobility

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles(UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with two independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10%increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by one of the two radars.

Federica Vitiello↗

Demonstration of Data Processing and Fusion from Distributed Radars for AAM Surveillance

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles (UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with three independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10% increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by two of the radars.

Federica Vitiello↗