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78 records · Page 5

Safe2Ditch Autonomous Crash Management System for Small Unmanned Aerial Systems: Concept Definition and Flight Test Results

Small unmanned aerial systems (sUAS) have the potential for a large array of highly-beneficial applications. These applications are too numerous to comprehensively list, but include search and rescue, fire spotting, precision agriculture, etc. to name a few. Typically sUAS vehicles weigh less than 55 lbs and will be performing flight operations in the National Air Space (NAS). Certain sUAS applications, such as package delivery, will include operations in the close proximity of the general public. The full benefit from sUAS is contingent upon the resolution of several technological areas in order to provide an acceptable level of risk for widespread sUAS operations. Operations of sUAS vehicles pose risks to people and property on the ground as well as manned aviation. Several of the more significant sUAS technological areas include, but are not limited to: autonomous sense and avoid and deconfliction of sUAS from other sUAS and manned aircraft, communications and interfaces between the vehicle and human operators, and the overall reliability of the sUAS and constituent subsystems. While all of the technological areas listed contribute significantly to the safe execution of the sUAS flight operations, contingency or emergency systems can greatly contribute to sUAS risk mitigations to manage situations where the vehicle is in distress. The Safe2Ditch (S2D) system is an autonomous crash management system for sUAS. Its function is to enable sUAS to execute emergency landings and avoid injuring people on the ground, damaging property, and lastly preserving the sUAS and payload. A sUAS flight test effort was performed to test the integration of sub-elements of the S2D system with a representative sUAS multi-rotor.

Glaab, Louis J.↗

Design and Testing of an Approach to Automated In-Flight Safety Risk Management for sUAS Operations

An onboard risk management automation design is presented based on run-time assurance principles, as well as the concept for In-Time Aviation Safety Management Systems (IASMS) as described by the National Academies. The automation is designed to operate independently of the autopilot and perform real-time risk assessment spanning multiple classes of hazards, predict constraint violations, and track autopilot states. In the event of elevated risk conditions or predicted constraint violations, the automation will select from a set of available contingencies and trigger autopilot mode changes if necessary to mitigate risk exposure. The onboard automation also informs the remote operator/pilot of what the independent monitor is observing and any contingency decisions or actions that may arise during flight. Details of an implementation of this design and results of verification and validation activities, as required to meet stringent NASA software and system assurance standards, are also presented. This includes simulation and flight testing using small unmanned aircraft systems.

Ersin Ancel↗

Considerations for an Integrated UAS CNS Architecture

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating revolutionary and advanced universal, reliable, always available, cyber secure and affordable Communication, Navigation, Surveillance (CNS) options for all altitudes of UAS operations. In Spring 2015, NASA issued a Call for Proposals under NASA Research Announcements (NRA) NNH15ZEA001N, Amendment 7 Subtopic 2.4. Boeing was selected to conduct a study with the objective to determine the most promising candidate technologies for Unmanned Air Systems (UAS) air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. The overall objectives are to develop UAS CNS requirements and then develop architectures that satisfy the requirements for UAS in both controlled and uncontrolled air space. This contract is funded under NASAs Aeronautics Research Mission Directorates (ARMD) Aviation Operations and Safety Program (AOSP) Safe Autonomous Systems Operations (SASO) project and proposes technologies for the Unmanned Air Systems Traffic Management (UTM) service.There is a need for accommodating large-scale populations of Unmanned Air Systems (UAS) in the national air space. Scale obviously impacts capacity planning for Communication, Navitation, and Surveillance (CNS) technologies. For example, can wireless communications data links provide the necessary capacity for accommodating millions of small UASs (sUAS) nationwide? Does the communications network provide sufficient Internet Protocol (IP) address space to allow air traffic control to securely address both UAS teams as a whole as well as individual UAS within each team? Can navigation and surveillance approaches assure safe route planning and safe separation of vehicles even in crowded skies?Our objective is to identify revolutionary and advanced CNS alternatives supporting UASs operating at all altitudes and in all airspace while accurately navigating in the absence of navigational aids. These CNS alternatives must be reliable, redundant, always available, cyber-secure, and affordable for all types of vehicles including small UAS to large transport category aircraft. The approach will identify CNS technology candidates that can meet the needs of the range of UAS missions to specific air traffic management applications where they will be most beneficial and cost effective.

Templin, Fred L.↗

Considerations for an Integrated UAS CNS Architecture

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is investigating revolutionary and advanced universal, reliable, always available, cyber secure and affordable Communication, Navigation, Surveillance (CNS) options for all altitudes of UAS operations. In Spring 2015, NASA issued a Call for Proposals under NASA Research Announcements (NRA) NNH15ZEA001N, Amendment 7 Subtopic 2.4. Boeing was selected to conduct a study with the objective to determine the most promising candidate technologies for Unmanned Air Systems (UAS) air-to-air and air-to-ground data exchange and analyze their suitability in a post-NextGen NAS environment. The overall objectives are to develop UAS CNS requirements and then develop architectures that satisfy the requirements for UAS in both controlled and uncontrolled air space. This contract is funded under NASAs Aeronautics Research Mission Directorates (ARMD) Aviation Operations and Safety Program (AOSP) Safe Autonomous Systems Operations (SASO) project and proposes technologies for the Unmanned Air Systems Traffic Management (UTM) service.There is a need for accommodating large-scale populations of Unmanned Air Systems (UAS) in the national air space. Scale obviously impacts capacity planning for Communication, Navigation, and Surveillance (CNS) technologies. For example, can wireless communications data links provide the necessary capacity for accommodating millions of small UASs (sUAS) nationwide? Does the communications network provide sufficient Internet Protocol (IP) address space to allow air traffic control to securely address both UAS teams as a whole as well as individual UAS within each team? Can navigation and surveillance approaches assure safe route planning and safe separation of vehicles even in crowded skies?Our objective is to identify revolutionary and advanced CNS alternatives supporting UASs operating at all altitudes and in all airspace while accurately navigating in the absence of navigational aids. These CNS alternatives must be reliable, redundant, always available, cyber-secure, and affordable for all types of vehicles including small UAS to large transport category aircraft. The approach will identify CNS technology candidates that can meet the needs of the range of UAS missions to specific air traffic management applications where they will be most beneficial and cost effective.

Templin, Fred L.↗

MPATH (Measuring Performance for Autonomy Teaming with Humans) Ground Control Station: Design Approach and Initial Usability Results

Envisioned future Advanced Air Mobility (AAM) operations will require a transition of aircraft command and control from onboard pilots to remote operators. The National Aeronautics and Space Administration (NASA) has developed a research ground control station (GCS) software called MPATH (Measuring Performance for Autonomy Teaming with Humans) to study the human factors of remote operators in a representative AAM environment, where small uncrewed aerial systems (sUAS; simulated or real) act as surrogates for larger AAM aircraft. A primary focus of the research being conducted with the MPATH GCS is scalability (i.e., one human managing multiple vehicles). MPATH has demonstrated to be a useful capability for human factors research and remote operations. Two initial usability studies and a multi-vehicle control assessment were recently conducted, and usability data and operator feedback were collected. Generally, participants rated MPATH high on usability and interface quality, whereas information quality was rated slightly lower. These results were supported by specific feedback. Several generalized GCS design recommendations are proposed based on the results and feedback from these flight activities. Future updates to MPATH will incorporate the proposed recommendations. In practice, these recommendations could be used by any GCS software designer or developer to promote usability and safety.

Advanced Air Mobility↗

UTM UAS Serivce Supplier Development: Sprint 1 Toward Technical Capability Level 4

NASA's UAS Traffic Management (UTM) Project has been tasked with developing concepts and initial implementations for integrating and managing small unmanned aircraft systems (UAS) into the low altitude airspace. To accomplish this task, the Project planned a phased approach based on four Technical Capability Levels (TCLs). As of this writing, TCL4 is currently in development for a late Spring 2019 flight demonstration. This TCL is focused on operations in an urban environment and includes the handling of high density and large-scale off-nominal conditions, vehicle-to-vehicle communications, detect-and-avoid technologies, communication requirements, public safety operations, airspace restrictions, and other related goals. Through research and testing to date, NASA has developed an architecture for UTM that depends on commercial entities collaboratively providing services that are traditionally provided by the Air Navigation Service Provider(ANSP) in manned aviation. A key component of this architecture is the UAS Service Supplier (USS), which acts as a communications bridge between UAS operators and the ANSP when necessary. In addition, the collection of USSs form a USS Network to collaboratively manage the airspace through the sharing of data and the adherence to a standard or set of standards required to participate in this USS Network. This document provides a record of the first step in the development of interoperable USSs that will ultimately support TCL4 flight testing and formalization of the overall UTM concept. To develop these USSs and the underlying specifications for them, NASA has planned a series of "Sprints" to work with industry partners in implementing the features and proposed specifications for USSs to participate in TCL4. This report describes Sprint One. In this Sprint, the focus was on establishing a baseline for the Application Programming Interfaces (APIs) and their associated data models. In addition, the concept of UAS Volume Reservations (UVR) (areas that impose restrictions on sUAS that are allowed to operate) was tested. NASA provided the specifications and iterated on them with partners while implementers developed to those specifications. NASA then tested each partner's implementation to ensure compatibility with all other implementers. This process helped all stakeholders gain confidence that the foundation for future Sprints was solid.

UAS service supplier↗