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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Towards An Autonomous sUAS Operating in UTM TCL4+ and STEReO Fire Scenario

This study presents two sUAS payload point designs for enabling autonomous BVLOS flight in UTM TCL4+ urban environments and STEReO fire responses. The payload components for the first payload include an onboard computer and a 360 LIDAR. The second payload, which is a continuation of the first, adds a range finder altimeter, downward-facing monocular camera, forward-facing thermal and visible light dual camera, vehicle-to-vehicle radio modem, and Li-ion smart battery. The components are mounted on enclosed structural frames that were designed in-house. Placing the autonomy components onboard leverages the advantages of sUAS over manned aircraft such as low-cost, quick response time, and increased scalability. Autonomous capabilities include embedded processing, SLAM, object and fire detection, and V2V communication. Data processing is conducted onboard the aircraft to eliminate the dependency on a groundstation downlink. The first iteration of the payload is tested in both simulation and flight tests while the continuing iteration is in development.

Autonomous UAS↗
NASA NTRS2021

State of the Industry: UAS Sensor Review

This report is a follow on from HF Designworks’ 2018 report on state of the present and state of the art sensor technologies as they related to Ground Based Detect and Avoid (GBDAA) systems for Unmanned Aircraft Systems (UAS). In this update, HF Designworks again looks to UAS test sites, manufacturers, vendors, and users to identify the latest sensor technologies covering not just GBDAA, but additional UAS sensor types; including airborne. For this latest report, the following sensor types were reviewed, as well as a few that don’t quite fit within the following categories: Electro-Optical / Infrared (EO/IR), LiDAR, RADAR, Radiofrequency (RF) scanner, Acoustic, and Other. From our interviews and research with various organizations and individuals, we found both interesting new technologies as well as improvements to many technologies first reviewed in 2018. Compared with our 2018 findings, many of the new technologies have helped produce sensors that are smaller, lighter, require less power, and have better range and resolution than those discussed in 2018. However, challenges still exist. There is no single currently available and FAA approved sensor suite that can adequately provide complete detect and avoid capabilities to meet the needs of UAS beyond visual line of sight (BVLOS) in the civilian airspace.

unmanned aircraft systems↗
NASA NTRSDate not supplied

Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Monte Carlo Tree Search Approach

Numerous unmanned aircraft systems operating at low altitudes to deliver goods and services may one day become ubiquitous in our cities. In the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) framework, such a concept is envisioned, where aerial vehicles operate beyond visual line of sight (BVLOS) within specifically reserved and time stamped “corridors” in the airspace. For example, these corridors or operational intent volumes can connect an aerial vehicle’s origin site to its destination site for package delivery operations. There may also be more than one corridor available for an aerial vehicle to choose from and often different corridors may intersect with one another. Thus, it is imperative to ensure flight trajectories belonging to different aerial vehicles are not in conflict. Per the UTM CONOPs, we assume that a vehicle almost always stays inside its corridor or operational volume. This work provides a framework for strategic deconfliction of UTM or package delivery drones, where we schedule the departure time of all vehicles subject to various temporal constraints (including the corridor deconfliction at the intersections). We present the “multi-route weighted package delivery problem” which serves as an exemplifying model for strategic deconfliction in UTM. In the multi-route weighted package delivery problem, a graph network is given which consists of a set of depots (source) and drop-off (destination) nodes, with multiple routes (defined as a sequence of waypoints) connecting the depots to drop-off nodes. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is for a known set of aerial vehicles to depart from the depots, choose a route and take off time, while avoiding conflicts with other aerial vehicles, and minimizing both risk and distance traveled. We provide a mixed integer linear programming (MILP) formulation of the problem, as well as a heuristic solution based on Monte Carlo Tree Search (MCTS) – a method used in game theory and artificial intelligence – to overcome limitations inherent to optimal solvers. Computational results show the advantages of using MCTS over the MILP formulation; the former can provide a sub-optimal solution quickly, and may sometimes even reach an optimal solution, whereas the latter may not even produce a solution in reasonable time. Furthermore, results from both the MILP formulation and MCTS methods were validated using a preliminary agent-based simulator implementing the UTM concept of operations. Thus, the MCTS method can be seen as a scalable solution to the complex multi-route weighted package delivery problem and may possibly be extended to similar complex optimization problems.

Kenny Chour↗
NASA NTRSDate not supplied

Wind Tunnel Testing of Static Aerodynamic and Power Consumption Characteristics of an Octocopter

The introduction of multirotor unmanned aircraft systems (UAS) in low-altitude airspace poses significant safety challenges. Further development of advanced aviation systems is needed to realize the full potential of UAS applications, particularly for urban and beyond visual line-of-sight (BVLOS) operations. The NASA System Wide Safety (SWS) project is developing key technologies to mitigate future airspace safety risks involving autonomous aircraft operation in densely populated areas. An important part of these technologies requires flight dynamics and performance models to assess feasible trajectories, power consumption requirements, and operational envelope limitations. To support these efforts, this research seeks to improve the accuracy of multirotor aerodynamic models and investigate stability characteristics relevant to flight safety. This paper presents a recent study of an octocopter vehicle using the NASA Langley 12-Foot Low-Speed Tunnel (LST). Results from isolated-airframe (no propellers) and powered-airframe tests are presented. A one-factor-at-a-time (OFAT) approach was used to explore the effect of propeller advance ratio and vehicle angle of attack on vehicle forces, moments, and power consumption. The results show nonlinear aerodynamic behavior and indicate regions where aerodynamic interaction effects may be significant.

George V. Altamirano↗
NASA NTRS2024

Federal USS Synthesis Effort: 2023 Flight Test Report. A NASA and Department of Defense Joint Evaluation of Multi-Domain Airspace Integration

In recent years, advancements in technology have greatly improved the utility and applicability of Uncrewed Aircraft Systems (UAS) and have highlighted the need for and importance of UAS Traffic Management (UTM). Onboard sense and avoid systems, ground-based sensors, and long- range command and control (C2) systems have significantly expanded the possibilities for UAS beyond visual line of sight (BVLOS) operations. Initially, research on UTM flights focused on their interactions with other UTM operations, but that has since been expanded to include interactions with the flight profiles of Advanced Air Mobility (AAM) and upper Class E Traffic Management (ETM) operations. Recognizing the potential of these systems and the increase in UAS autonomy, the Department of Defense (DoD) is working towards integrating these missions and systems into a unified DoD Federal ecosystem. The Federal USS Synthesis Effort (FUSE) aims to develop a live system that can efficiently combine this wide range of UTM, AAM, and ETM systems, thus enabling expanded operations within a single common operating environment. The goal of the Federal USS Synthesis Effort (FUSE) is for NASA and the DoD to develop a live system that can efficiently combine UTM, AAM, and ETM systems. The most recent endeavor in this effort was a live flight test conducted near Grand Forks Air Force Base in June, 2023, where the FUSE ecosystem successfully demonstrated integrating UTM, AAM, and ETM operations while providing a single, shared COP to users. Additional investigations were made during the test, including assessing the usefulness of the system and its capability to support UAS weighing over 55 lbs.; testing user messaging capabilities and a DoD adaptation of a Federal USS; and assessing user workload, automated vs manual control, and the usability of NASA’s XTMClient.

Federal USS↗
NASA NTRSDate not supplied

Confidence-Based Buffer for Strategic Deconfliction with Probabilistic Operational Intent

This paper presents a methodology to expand the 95% confidence level of the elliptical geometry given by Unmanned Aircraft System (UAS) operators planning to fly Beyond Visual Line of Sight (BVLOS) to any confidence level before being fed to the strategic deconfliction (SD) module, effectively increasing the separation buffer between Operational Intents (OIs). To assess the performance of this approach, it is integrated within an adaptation of the Rolling Horizon with K-Position Search volume-based strategic deconfliction approach, previously developed at NASA Ames, preventing the 4D overlapping of OIs shaped by ellipses instead of traditional blocks. Safety and efficiency metrics are evaluated through the deconfliction of four simulated package delivery route network structures across the San Francisco Metropolitan Area with increasing numbers of crossing waypoints (network complexity). Safety assessment entails the in-house creation of a metric to quantify collision occurrences per flight hour based on the frequency at which the probabilistic operational volume segments are sampled, whereas efficiency is measured using ground delay. Results indicate that the largest buffer growth occurs when increasing the confidence level beyond 99.9% and demonstrate the negative impact of network complexity on both metrics, regardless of the OI geometry. Further, the ellipse-based SD adaptation more accurately estimates temporal separation at crossings, allowing deconflicted vehicles to be closer together. It is concluded that the proposed methodology enables the desired confidence level to serve as an effective controller of buffer size.

safety↗
NASA NTRS2022

Applicability of Digital Flight to the Operations of Self-Piloted Unmanned Aircraft Systems in the National Airspace System

Unmanned Aircraft Systems (UAS) hold great promise for a new era of specialized missions, including personal air transportation, cargo flight operations, aerial surveys, inspections, firefighting and more. The anticipated market growth is significant. To unlock its scalability and incumbent benefits requires a human to oversee multiple flights simultaneously, focusing on multi-vehicle mission management and relinquishing to autonomous systems their active role in controlling the aircrafts’ flight paths. Key to the realization of these scalability benefits is minimally-encumbered access to the National Airspace System (NAS), which poses some unique challenges for self-piloted UAS aircraft operations. These include the requirement for compatibility with existing airspace structures and operations including Visual Flight Rules (VFR) and Instrument Flight Rules (IFR), neither of which were developed to accommodate the unique needs and capabilities of UAS. This paper explores the applicability of Digital Flight to the operations of self-piloted UAS. As proposed by NASA, Digital Flight is a flight operations capability, enabled by a set of cooperative procedures and digital technologies, in which flight operators ensure flight-path safety through automated separation and flight path management in lieu of visual procedures and Air Traffic Control separation services. Flights operating under potentially-forthcoming rules of Digital Flight employ advanced automation technologies, information sharing, connectivity to operational data, and cooperative behaviors through distributed decision-making to maintain safety and achieve mission objectives. Designed for integration with VFR and IFR operations in shared NAS airspace, potentially as a third set of flight rules, Digital Flight may provide the mechanism for UAS operators – and all aircraft operators – to scale and diversify their operations beyond what is achievable under current regulations.

DFR↗