Results for “Autonomy” — Page 88

NASA NTRSDate not supplied

Streamlining GNC Architecture Development and FSW Integration for the Mars Ascent Vehicle

The Mars Ascent Vehicle (MAV) will be the first vehicle to perform an ascent from the surface of another atmospheric planetary body outside of the Earth-Moon system. Significant light-time delay requires complete autonomy of flight throughout ascent, and naturally a high level of reliability is desired in both MAV’s hardware and software subsystems. The MAV Guidance, Navigation and Controls (GNC) team and the MAV Flight Software (FSW) team have partnered together to improve the efficiency of algorithm integration onto the MAV flight processor, and to increase confidence that said integration is successful and without human error. An interface architecture is proposed for the GNC suite that allows both the guidance and navigation subsystems to provide code algorithms directly in C++, and the controls subsystem to provide MATLAB Simulink auto-coded algorithms. Several continuous integration/deployment (CI/CD) methodologies have been considered for ease of transition of algorithm code from the GNC team to the FSW team. The GNC/FSW teams also worked together to develop a cFS-friendly wrapper which abstracts the integration of the GNC algorithm code into an interface-level API that is compatible with cFS. Several iterations of vehicle GNC code have been produced between the GNC/FSW team’s partnership, and this strong interface between these two teams have allowed the GNC/FSW teams to greatly increase confidence of efficient and error-free implementation of the GNC code onto MAV for a successful flight.

Engineering↗

NASA NTRSDate not supplied

Using Recorded Airspace Traffic Data to Create Simulation Scenarios for Trajectory-Based Operations

The National Aeronautics and Space Administration is supporting research to transition from the current air traffic management paradigm to Trajectory-Based Operations targeting the 2035-2045 timeframe. Trajectory-Based Operations in the National Airspace System focuses on modernizing current operations and technology to increase efficiency, predictability, resilience, and flexibility while migrating toward greater operational autonomy across the airspace. To understand the impact of new technologies and procedures that enable Trajectory-Based Operations, simulation studies must be conducted using realistic scenarios. This paper describes techniques that can be employed when using recorded airspace traffic data to create scenarios representative of a 2040 Trajectory-Based Operations airspace. The paper provides a use case example and suggests how this methodology may be applied to other simulations studying concepts, technologies, and procedures in a future airspace system.

Billy K. Buck↗

NASA NTRSDate not supplied

Scientific Physical and Operations Characterization (SPOC): Studying Scientists in the Wild to Inform Human Planetary Exploration Operations

The objective of the Scientific Physical and Operational Characterization (SPOC) project is to build an evidence-based description of terrestrial field science to inform the operational, physical, and tool requirements for planetary exploration extravehicular activities (xEVAs). EVAs of the future, including Artemis 2024 and beyond, intend to promote scientific productivity (e.g., LEAG science goals)[1]; however, no clear, objective pathway currently exists to enable this goal, particularly with respect to the desired increase in autonomy imparted to future astronauts. The SPOC project applies expertise in the fields of cognitive systems engineering [2-5], biomechanics, wearable sensors [6-8] and hardware/software to more targetly address these issues. In doing so, a terrestrial fieldwork ground-truth can be established that will benefit human and robotic exploration of other planetary surfaces.

M J Miller↗

NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗

NASA NTRSDate not supplied

How the Internet of "Space" Things will Disrupt and Transform Astronaut Work-life

Future long duration exploration missions will require astronauts to work and behave more autonomously. Over the last several years, we have been investigating how integrating sensors into an astronaut’s environment enables crew autonomy. This paper describes the prototypes we have deployed in Earth analogs investigating the concept of the Internet of “Space” Things.

procedure execution↗

NASA NTRSDate not supplied

Knowledge Discovery for Early Failure Assessment of Complex Engineered Systems Using Natural Language Processing

Emerging complex engineered systems may have unexpected safety issues due to novel operational environments, increasing autonomy, human-machine interaction, and other factors. To prevent failures in operation or testing that necessitate costly redesign, it is desirable to predict likely failure modes early in the design process. Information about past engineering failures in natural language format presents one possible solution by enabling the retrieval of information that can inform new designs. However, identifying documents containing usable information and extracting the required information can be prohibitively time-consuming when implemented at scale. In this research, an automated natural language processing (NLP) framework is proposed to discover relevant knowledge from documents containing failure-related design information. The framework is applied to NASA’s Lessons Learned Information System (LLIS),which is publicly available. Documents containing usable information are filtered using two different NLP-based models. Next, from the identified usable documents, a failure taxonomy is extracted using a partitioned hierarchical topic modeling approach. Partitions of the document describe different sections of the failure taxonomy – i.e., failure, cause of failure, and recommendations – as indicated by the structure of the original document. The extracted failure taxonomy can be leveraged in early design failure assessment methods. Moreover, the framework can be used to identify documents containing usable failure-related design information from other databases and extract relevant information from these documents.

Documentation and Information Science↗

NASA NTRSDate not supplied

Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.

air traffic control↗

NASA NTRSDate not supplied

Strategic and Tactical Functions in an Autonomous Air Traffic Management System

This paper evaluates, by means of fast-time simulation, performance of a candidate system for autonomous air traffic management. Advancing towards autonomy in air traffic management may be necessary in order for new air vehicle types such as electric Vertical Take Off and Landing (eVTOL) to operate safely and efficiently in airspace shared with conventional traffic. To account for uncertain prediction, autonomous air traffic management was divided into two integrated and coordinated subsystems: strategic scheduling, performed at predeparture, and tactical conflict detection and resolution, performed throughout the flight. The conflict detection and resolution subsystem contained a second tactical scheduling function that applied to flights operating in the airspace near the destination airport. This paper compares and contrasts the two subsystems and uses fast-time simulation to demonstrate the comparisons. A scenario of 54 flights inbound to Newark Liberty International Airport was simulated multiple times with different parameters. The scenario was created using flight plans recorded from the National Airspace System on a low weather, average traffic day in April 2018. Whereas the routes were not changed, the departure times of the flights were modified to increase arrival rates at the Newark runway and arrival meter fixes. Results of the simulations showed that the autonomous air traffic management system was able to safely manage the traffic, even with prediction uncertainty. In addition, they showed the importance of including flight holding maneuvers, in addition to path stretching, in conflict detection and resolution and of coordinating strategic and tactical scheduling. Finally, a tradeoff between absorbing the delay calculated by strategic scheduling on the ground versus in the air showed that taking most of the delay on the ground is cost effective for a simple idealized cost function. However, taking a little of the delay in the air prevented throughput on the runway from dropping for short periods due to trajectory prediction uncertainty.

air traffic control↗

NASA NTRSDate not supplied

Design and Testing of Autonomous Distributed Space Systems

Distributed Space Systems (DSS) are an emerging class of mission designs that enable new scientific and commercial opportunities. In order to enable those new opportunities, these systems will need to have significantly expanded autonomous capabilities compared to their single-spacecraft predecessors. In this paper, we present Distributed Spacecraft Autonomy (DSA) project, a payload on NASA's Starling spacecraft experiment. We first describe a step-by-step process for characterizing what features are needed in an autonomous DSS, and show how this process applied to DSA. We then describe the Starling mission, a four-spacecraft swarm hosting multiple DSS payloads. We then describe DSA, which will mature in-space networking and autonomous planning technologies to measure topside ionosophere features using data from the Starling spacecraft's GPS receivers. We describe how DSA will coordinate observations of GPS satellites using Starling's underlying communications infrastructure combined with novel DSS technology. The flight validation of DSS technology will provide mature technology to enable future DSS missions.

Nicholas Cramer↗

NASA NTRS2021

Parametric Study of State-of-Charge for an Electric Aircraft in Urban Air Mobility

The envisioned concept of urban air mobility is anticipated to support passenger transportation, cargo delivery, and emergency services in major metropolitan areas with increasing autonomy levels in the future. Distributed electric propulsion powered electric vertical takeoff and landing aircraft are expected to enable urban air mobility. However, the low specific energy of onboard lithium-ion polymer batteries and wind conditions impose constraints on flight endurance. Therefore, to enable autonomous urban air mobility operations using electric aircraft, one of the critical steps from a safety and efficiency perspective is to understand how various operational and environmental conditions impact the state-of-charge of the onboard lithium-ion polymer batteries. This research performs a parametric study of the state-of-charge for a NASA-proposed conceptual multirotor aircraft flight in the urban environment. The parameters considered for the parametric analysis are cruise airspeed, cruise altitude, climb and descent profiles, wind conditions (wind magnitude, wind direction relative to the route, and wind magnitude uncertainty), and required time of arrival.

Urban Air Mobility↗

NASA NTRS2021

Parametric Study of State of Charge for an Electric Aircraft in Urban Air Mobility

The envisioned concept of urban air mobility is anticipated to support passenger transportation, cargo delivery, and emergency services in major metropolitan areas with increasing autonomy levels in the future. Distributed electric propulsion powered electric vertical takeoff and landing aircraft are expected to enable urban air mobility. However, the low specific energy of onboard lithium-ion polymer batteries and wind conditions impose constraints on flight endurance. Therefore, to enable autonomous urban air mobility operations using electric aircraft, one of the critical steps from a safety and efficiency perspective is to understand how various operational and environmental conditions impact the state-of-charge of the onboard lithium-ion polymer batteries. This research performs a parametric study of the state-of-charge for a NASA-proposed conceptual multirotor aircraft flight in the urban environment. The parameters considered for the parametric analysis are cruise airspeed, cruise altitude, climb and descent profiles, wind conditions (wind magnitude, wind direction relative to the route, and wind magnitude uncertainty), and required time of arrival.

Urban Air Mobility↗

NASA NTRS2021

Advanced Multimodal Solutions for Information Presentation

High-workload, fast-paced, and degraded sensory environments are the likeliest candidates to benefit from multimodal information presentation. For example, during extra-vehicular activity (EVA) and telerobotic operations, the sensory restrictions associated with such a hostile environment provide a major challenge to maintaining the situation awareness (SA) required for safe operations. In particular, orientation, navigation, and collision avoidance are critical aspects of EVA tasks that need to be addressed to ensure the safety of the crew and the success of the mission. Multimodal displays hold promise to enhance situation awareness and task performance by utilizing different sensory modalities and maximizing their effectiveness based on appropriate interaction between modalities. Multimodal displays will also play an important role for long-duration information systems and will likely begin to be developed in the early phases of cislunar Gateway, and later lunar or Mars transit missions. Information systems are envisioned for LDEMs that require spacecraft with greater crew autonomy and increased dependence on computer-provided information needed to perform routine tasks, as well as time- and safety critical tasks. Such a system will require a single, common interface that is easy to learn and use and accesses key information from all relevant vehicle/habitat systems to enable task performance in both nominal and emergency conditions. Understanding of multimodal display technologies and their interactions will help to inform interface guidelines for LDEMs. The scope of the current report is an analysis of potential multimodal display technologies for long duration missions and, in particular, will focus on their potential role in EVA activities. The review will address multimodal (combined visual, auditory and/or tactile) displays investigated by the National Aeronautics and Space Administration (NASA), industry, and Department of Defense (DoD). It also considers the need for adaptive information systems to accommodate a variety of operational contexts such as crew status (e.g., fatigue, workload level) and task environment (e.g., EVA, habitat, rover, spacecraft). Current approaches to guidelines and best practices for combining modalities for the most effective information displays are also reviewed. Potential issues in developing interface guidelines for LDEMs are briefly considered.

multimodal displays↗

NASA NTRS2021

Strategic and Tactical Functions in an Autonomous Air Traffic Management System

This paper evaluates, by means of fast-time simulation, performance of a candidate system for autonomous air traffic management. Advancing towards autonomy in air traffic management may be necessary in order for new air vehicle types such as electric Vertical Take Off and Landing (eVTOL) to operate safely and efficiently in airspace shared with conventional traffic. To account for uncertain prediction, autonomous air traffic management was divided into two integrated and coordinated subsystems: strategic scheduling, performed at predeparture, and tactical conflict detection and resolution, performed throughout the flight. The conflict detection and resolution subsystem contained a second tactical scheduling function that applied to flights operating in the airspace near the destination airport. This paper compares and contrasts the two subsystems and uses fast-time simulation to demonstrate the comparisons. A scenario of 54 flights inbound to Newark Liberty International Airport was simulated multiple times with different parameters. The scenario was created using flight plans recorded from the National Airspace System on a low weather, average traffic day in April 2018. Whereas the routes were not changed, the departure times of the flights were modified to increase arrival rates at the Newark runway and arrival meter fixes. Results of the simulations showed that the autonomous air traffic management system was able to safely manage the traffic, even with prediction uncertainty. In addition, they showed the importance of including flight holding maneuvers, in addition to path stretching, in conflict detection and resolution and of coordinating strategic and tactical scheduling. Finally, a tradeoff between absorbing the delay calculated by strategic scheduling on the ground versus in the air showed that taking most of the delay on the ground is cost effective for a simple idealized cost function. However, taking a little of the delay in the air prevented throughput on the runway from dropping for short periods due to trajectory prediction uncertainty.

air traffic control↗

NASA NTRS2021

Initial Validation of a Simulation System for Studying Interoperability in Future Air Traffic Management Systems

Future air traffic management systems will need to accommodate large numbers of increasingly diverse air vehicles with different operating paradigms. To support this trend, they will digitally share copious amounts of information via a common communication architecture. Operators will deploy programs that create and negotiate flight plans via the architecture’s communication protocols. These programs will autonomously make decisions that must be arbitrated by the architecture and robust to uncertainty. To study interoperability in air traffic management, a new airspace simulation system was composed by integrating a legacy airspace simulation, an air traffic control model, and a new research communication architecture. It was used to evaluate air traffic management concepts by adapting it to handle congested arrival traffic at Newark Liberty International Airport and executing simulations. Results demonstrated the ability of the simulation system to model in detail strategic traffic flow management, predeparture flight planning, and air traffic control working in concert. Subsequent studies can use the simulation system to study interoperability, autonomy, digital communication, and uncertainty in future air traffic management systems.

air traffic control↗

NASA NTRSDate not supplied

Enabling a Voice Management System for Space Applications, Design and Software Development

Sustainable missions, beyond low Earth orbit, will require autonomous capabilities in order to achieve NASA’s Artemis program objectives. Correspondingly, the crew must have a means to efficiently interact with these autonomous systems; this can be facilitated via voice and speech communications. Voice-based controls enable the user to access autonomous systems hands-free/eyes-free, allowing the user to better focus on critical tasks. The goal of this project was to explore the knowledge and technology needed to successfully design effective voice interfaces for autonomous systems. The main objective was to understand how a crew member, through voice interaction, could most efficiently and intuitively communicate with a notional autonomous vehicle system manager. This project leveraged prior research conducted by the University of Michigan’s Bioastronautics and Life Support System (BLiSS) team as part of a NASA Moon to Mars eXploration Systems and Habitation (M2M X-Hab) 2020 Academic Innovation Challenge. The X-Hab 2020 work from the BliSS Team resulted in an intuitive graphical user interface/user experience that was built on an Internet of Things (IOT) platform. The Voice User Interface (VUI) design for the M2M X-Hab 2021 project leveraged this technology and incorporated a voice-based assistant and NASA’s Platform for Autonomous Systems (NPAS) software. This required technologies to convert voice to text, conduct semantic interpretations, and convert responses from the autonomous system to text and to speech; additionally, the background noise environment of spacecraft was assessed, and a relatable personality for the autonomous system to facilitate human-like conversations was created. This work’s success was largely due to the diverse team that included expertise in Space Systems Engineering, Human Computer Interaction, Aerospace Engineering, Computer Science, Biomedical Engineering, and Applied Physics. The differing perspectives fostered elaborate discussions, resulting in the conception of three main interactions: (1) User-System, (2) NPAS-System, and (3) Environment-System. The system developed, i.e. the VUI, had to be unique, efficient, and intuitive; thus, the team crafted a personality for the system to enable human-like conversation. User surveys sent to students and young professionals were used to help determine these personality traits by capturing perspectives and expectations of the “Artemis Generation Astronauts”. To further simulate human-like conversations, the system had to be able to quickly interpret user speech and be able to integrate with NASA’s NPAS system for quick and reliable information transfer. Results of this research include (1) a working prototype user interface, that is compatible with NASA’s NPAS system; (2) software that demonstrates the ability to interpret user requests and respond appropriately; (3) the capability to implement fully expanded conversations between user and system using intuitive communication in four request categories; and (4) software and hardware recommendations that optimize the system’s ability to operate, i.e. be heard, in a noisy environment. The technologies chosen for this project’s demonstrations included the following: Raspberry Pi, RASA, Mozilla Deep Speech, Coqui, RTX Voice and Adobe XD. This work has laid the foundation for the development of VUI’s used for autonomy, and is intended to provide guidance for future VUI development.

Tara Vega↗

NASA NTRSDate not supplied

Lunar Node 1 and Beyond

Lunar Node 1 (LN-1) is an S-band Navigation beacon for lunar applications that was recently designed and built at MSFC. As part of NASA's Commercial Lunar Payload Services initiative, this beacon will be delivered to the moon's surface on Intuitive Machine's NOVA-C lunar lander in November 2021. During this mission, LN-1’s goal will be to demonstrate navigation technologies that can support local surface and orbital operations around the moon, enabling autonomy which would decrease dependency on heavily utilized Earth based assets like the Deep Space Network. To do this, LN-1’s design leverages Cubesat components as well as the Multi-spacecraft Autonomous Positioning System (MAPS) algorithms, which enable the autonomous spacecraft positioning through communication-integrated navigation measurements. In addition to demonstrating the MAPS payload, the radio will also be used in standard tone-based non-coherent ranging and Doppler tracking to provide an alternate approaches and comparisons for navigation performance. LN-1 will represent a single node in a potential greater MAPS network of assets. While LN-1 awaits launch to demonstrate this initial use of one-way navigation, designs are already under way for proposed subsequent missions like LN-2 to enable expanded capability. The next steps in these missions seek to include a receive capability to allow two-way ranging support with other operational spacecraft in the lunar vicinity, and to provide some component upgrades related to the radio, power, and thermal systems that will improve the longevity of the payload in the harsh lunar environment. The LN-1 design details, status, and potential forward work with mission like LN-2 will be outlined in this presentation.

Evan John Anzalone↗

NASA NTRSDate not supplied

Towards a Measure of Situation Awareness for Space Mission Schedulers

The success of space flight missions relies on support provided to astronauts through specialist knowledge of ground-based personnel. One of the many essential tasks that ground personnel provide is the scheduling of flight crew daily activities. Future long duration exploration missions will require astronauts to assume planning and scheduling responsibilities in order to facilitate increased autonomy from ground support. Although situation awareness is critical to the scheduling task, a sufficient measure for this domain has not been developed. This paper documents the approach and process by which the authors developed a framework for measuring situation awareness in space mission schedulers and presents the measure applications’ initial results.

human factors in spaceflight↗

NASA NTRSDate not supplied

Lunar Base Construction Overview

Previous lunar missions and campaigns have been restricted to using robotic landers and lunar orbiting satellites as well as sortie type of operations using astronaut crews (NASA Apollo program). The next phase of lunar exploration has begun under NASA’s Artemis program and there has been an international response where other nations such as China, Russia, India, Canada, Japan and the European Union of nations, have all expressed interest in either collaborating or competing with NASA on the Moon. This next phase has an over arching goal of achieving a permanent human presence on the Moon via sustainable methods. A lunar base with human occupancy will require infrastructure to provide shelter, utilities, landing/launch pads, roads, communications, power and all the other necessities to sustain human life and protect equipment. Since human biology is not well suited for surviving in the lunar environment, there will be many forms of automated equipment, autonomy and robotic helpers that will minimize the amount of Extra-Vehicular Activity (EVA) required by the crew. This will mean that the radiation dosage received by the crew will stay within acceptable and safe career doses. The required infrastructure must be constructed, but the mass and logistics of bringing all the construction materials from Earth are prohibitive, which makes the necessary construction difficult to achieve. In-Situ Resource Utilization (ISRU) aims to solve this challenge by sourcing construction materials locally or “in-situ”. This means that their transportation can be completely eliminated, resulting in large cost savings by avoiding the launch out of Earth’s deep gravity well and subsequent trans lunar injection, lunar orbit capture and landing. This paper will give an overview of the required construction tasks and related equipment that will be required to robotically build a lunar base using in-situ resources. It will also organize these tasks into logical groupings so that technology development and implementation can be pursued within a framework that can be referenced by all involved.

Construction↗