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Pathfinding for Airspace with Autonomous Vehicles (PAAV) Multi-Vehicle Operations with Digital Trajectories

The Path Finding for Airspace with Autonomous Vehicles (PAAV) subproject under ATM-X is developing concepts and solutions to allow pilots to supervise multiple uncrewed flights at a time. This line of research stems from industry's desire to leverage Uncrewed Aircraft (UA) operations to achieve maximum productivity from pilot and aircraft resources, driven partially by pilot staffing shortages. Trajectory based solutions delivered by data link offer a potential solution to the multi-vehicle (m:N) problem by minimizing the number of instructions between remote pilots and air traffic controllers. Furthermore, such solutions avoid the need for pilots to monitor multiple voice frequencies at a time for air traffic control instructions to manage multiple flights. This panel presentation will give a brief introduction to PAAV followed by a description of NASA's AutoResolver capability for generating comprehensive air traffic control clearances and communicating them via data link for controller approval and flight execution.

multi vehicle control, trajectory based operations↗

Towards an Open, Distributed Software Architecture for UxS Operations

To address the growing need to evaluate, test, and certify an ever expanding ecosystem of UxS platforms in preparation of cultural integration, NASA Langley Research Center's Autonomy Incubator (AI) has taken on the challenge of developing a software framework in which UxS platforms developed by third parties can be integrated into a single system which provides evaluation and testing, mission planning and operation, and out-of-the-box autonomy and data fusion capabilities. This software framework, named AEON (Autonomous Entity Operations Network), has two main goals. The first goal is the development of a cross-platform, extensible, onboard software system that provides autonomy at the mission execution and course-planning level, a highly configurable data fusion framework sensitive to the platform's available sensor hardware, and plug-and-play compatibility with a wide array of computer systems, sensors, software, and controls hardware. The second goal is the development of a ground control system that acts as a test-bed for integration of the proposed heterogeneous fleet, and allows for complex mission planning, tracking, and debugging capabilities. The ground control system should also be highly extensible and allow plug-and-play interoperability with third party software systems. In order to achieve these goals, this paper proposes an open, distributed software architecture which utilizes at its core the Data Distribution Service (DDS) standards, established by the Object Management Group (OMG), for inter-process communication and data flow. The design decisions proposed herein leverage the advantages of existing robotics software architectures and the DDS standards to develop software that is scalable, high-performance, fault tolerant, modular, and readily interoperable with external platforms and software.

Cross, Charles D.↗

Sense and Avoid Characterization of the Independent Configurable Architecture for Reliable Operations of Unmanned Systems

Abstract—Independent Configurable Architecture for Reliable Operations of Unmanned Systems (ICAROUS) is a distributed software architecture developed by NASA Langley Research Center to enable safe autonomous UAS operations. ICAROUS consists of a collection formally verified core algorithms for path planning, traffic avoidance, geofence handling, and decision making that interface with an autopilot system through a publisher-subscriber middleware. The ICAROUS Sense and Avoid Characterization (ISAAC) test was designed to evaluate the performance of the onboard Sense and Avoid (SAA) capability to detect potential conflicts with other aircraft and autonomously maneuver to avoid collisions, while remaining within the airspace boundaries of the mission. The ISAAC tests evaluated the impact of separation distances and alerting times on SAA performance. A preliminary analysis of the effects of each parameter on key measures of performance is conducted, informing the choice of appropriate parameter values for different small Unmanned Aircraft Systems (sUAS) applications. Furthermore, low-power Automatic Dependent Surveillance – Broadcast (ADS-B) is evaluated for potential use to enable autonomous sUAS to sUAS deconflictions as well as to provide usable warnings for manned aircraft without saturating the frequency spectrum.

Consiglio, Maria↗

Antennas Designed for Advanced Communications for Air Traffic Management (AC/ATM) Project

The goal of the Advanced Communications for Air Traffic Management (AC/ATM) Project at the NASA Glenn Research Center at Lewis Field is to enable a communications infrastructure that provides the capacity, efficiency, and flexibility necessary to realize a mature free-flight environment. The technical thrust of the AC/ATM Project is targeted at the design, development, integration, test, and demonstration of enabling technologies for global broadband aeronautical communications. Since Ku-band facilities and equipment are readily available, one of the near-term demonstrations involves a link through a Kuband communications satellite. Two conformally mounted antennas will support the initial AC/ATM communications links. Both of these are steered electronically through monolithic microwave integrated circuit (MMIC) amplifiers and phase shifters. This link will be asymmetrical with the downlink to the aircraft (mobile vehicle) at a throughput rate of greater than 1.5 megabits per second (Mbps), whereas the throughput rate of the uplink from the aircraft will be greater than 100 kilobits per second (kbps). The data on the downlink can be narrow-band, wide-band, or a combination of both, depending on the requirements of the experiment. The AC/ATM project is purchasing a phased-array Ku-band transmitting antenna for the uplink from the test vehicle. Many Ku-band receiving antennas have been built, and one will be borrowed for a short time to perform the initial experiments at the NASA Glenn Research Center at Lewis Field. The Ku-band transmitting antenna is a 254-element MMIC phased-array antenna being built by Boeing Phantom Works. Each element can radiate 100 mW. The antenna is approximately 43-cm high by 24-cm wide by 3.3-cm thick. It can be steered beyond 60 from broadside. The beamwidth varies from 6 at broadside to 12 degrees at 60 degrees, which is typical of phased-array antennas. When the antenna is steered to 60 degrees, the beamwidth will illuminate approximately five satellites on the orbital arc. Spread spectrum techniques will be employed to keep the power impinging on the adjacent satellites below their noise floor so that no interference results. This antenna is power limited. If the antenna elements (currently 254) are increased by a factor of 4 (1024) or 16 (4096), the gain will increase and the beamwidth will decrease in proportion. For the latter two antenna sizes, the power must be "backed off" to prevent interference with the neighboring satellites. The receiving antenna, which is approximately 90-cm high, 60-cm wide, and 3.5-cm thick, is composed of 1500 phased-array elements. The system phased-array controller can control both a 1500-element receiving antenna and a 500-element transmitting antenna. For ground testing, this controller will allow manual beam pointing and polarization alignment. For normal operation, the system can be connected to the receiving antenna and the navigation system for real-time autonomous track operation. This will be accomplished by first pointing both antennas at the satellite using information from the aircraft data bus. Then, the system phased-array controller will electronically adjust the antenna pointing of the receiving antenna to find the peak signal. After the peak signal has been found, the beam of the transmitting antenna will be pointed to the same steering angles as the receiving antenna. For initial ground testing without an aircraft, the ARINC 429 data bus (ARINC Inc., Annapolis, Maryland) will be simulated by a gyro system purchased for the follow-on to the Monolithic Microwave Integrated Circuit (MMIC) Arrays for Satellite Communication on the Move (MASCOM) Project. MASCOM utilized the Advanced Communications Technology Satellite (ACTS) with a pair of Ka-band experimental phased-array antennas.

Zakrajsek, Robert J.↗

Laboratory testing of candidate robotic applications for space

Robots have potential for increasing the value of man's presence in space. Some categories with potential benefit are: (1) performing extravehicular tasks like satellite and station servicing, (2) supporting the science mission of the station by manipulating experiment tasks, and (3) performing intravehicular activities which would be boring, tedious, exacting, or otherwise unpleasant for astronauts. An important issue in space robotics is selection of an appropriate level of autonomy. In broad terms three levels of autonomy can be defined: (1) teleoperated - an operator explicitly controls robot movement; (2) telerobotic - an operator controls the robot directly, but by high-level commands, without, for example, detailed control of trajectories; and (3) autonomous - an operator supplies a single high-level command, the robot does all necessary task sequencing and planning to satisfy the command. Researchers chose three projects for their exploration of technology and implementation issues in space robots, one each of the three application areas, each with a different level of autonomy. The projects were: (1) satellite servicing - teleoperated; (2) laboratory assistant - telerobotic; and (3) on-orbit inventory manager - autonomous. These projects are described and some results of testing are summarized.

Purves, R. B.↗

Promoting Crew Autonomy: Current Advances and Novel Techniques

Since the dawn of the era of human space flight, mission control centers around the world have played an integral role in guiding space travelers toward mission success. In the International Space Station (ISS) program, astronauts and cosmonauts have the benefit of near constant access to the expertise and resources within mission control, as well as lifeboat capability to quickly return to Earth if something were to go wrong. As we move into an era of longer duration missions to more remote locations, rapid and ready access to mission control on earth will no longer be feasible. To prepare for such missions, long duration crews must be prepared to operate more autonomously, and the mission control paradigm that has been successfully employed for decades must be re-examined. The team at NASA's Payload Operations and Integration Center (POIC) in Huntsville, Alabama is playing an integral role in the development of concepts for a more autonomous long duration crew of the future via research on the ISS.

Harris, Samantha↗

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↗

Autonomous Agents and Intelligent Assistants for Exploration Operations

Human exploration of space will involve remote autonomous crew and systems in long missions. Data to earth will be delayed and limited. Earth control centers will not receive continuous real-time telemetry data, and there will be communication round trips of up to one hour. There will be reduced human monitoring on the planet and earth. When crews are present on the planet, they will be occupied with other activities, and system management will be a low priority task. Earth control centers will use multi-tasking "night shift" and on-call specialists. A new project at Johnson Space Center is developing software to support teamwork between distributed human and software agents in future interplanetary work environments. The Engineering and Mission Operations Directorates at Johnson Space Center (JSC) are combining laboratories and expertise to carry out this project, by establishing a testbed for hWl1an centered design, development and evaluation of intelligent autonomous and assistant systems. Intelligent autonomous systems for managing systems on planetary bases will commuicate their knowledge to support distributed multi-agent mixed-initiative operations. Intelligent assistant agents will respond to events by developing briefings and responses according to instructions from human agents on earth and in space.

Malin, Jane T.↗

Model Based Autonomy for Robust Mars Operations

Space missions have historically relied upon a large ground staff, numbering in the hundreds for complex missions, to maintain routine operations. When an anomaly occurs, this small army of engineers attempts to identify and work around the problem. A piloted Mars mission, with its multiyear duration, cost pressures, half-hour communication delays and two-week blackouts cannot be closely controlled by a battalion of engineers on Earth. Flight crew involvement in routine system operations must also be minimized to maximize science return. It also may be unrealistic to require the crew have the expertise in each mission subsystem needed to diagnose a system failure and effect a timely repair, as engineers did for Apollo 13. Enter model-based autonomy, which allows complex systems to autonomously maintain operation despite failures or anomalous conditions, contributing to safe, robust, and minimally supervised operation of spacecraft, life support, In Situ Resource Utilization (ISRU) and power systems. Autonomous reasoning is central to the approach. A reasoning algorithm uses a logical or mathematical model of a system to infer how to operate the system, diagnose failures and generate appropriate behavior to repair or reconfigure the system in response. The 'plug and play' nature of the models enables low cost development of autonomy for multiple platforms. Declarative, reusable models capture relevant aspects of the behavior of simple devices (e.g. valves or thrusters). Reasoning algorithms combine device models to create a model of the system-wide interactions and behavior of a complex, unique artifact such as a spacecraft. Rather than requiring engineers to all possible interactions and failures at design time or perform analysis during the mission, the reasoning engine generates the appropriate response to the current situation, taking into account its system-wide knowledge, the current state, and even sensor failures or unexpected behavior.

Kurien, James A.↗

Imaging Flash Lidar for Autonomous Safe Landing and Spacecraft Proximity Operation

3-D Imaging flash lidar is recognized as a primary candidate sensor for safe precision landing on solar system bodies (Moon, Mars, Jupiter and Saturn moons, etc.), and autonomous rendezvous proximity operations and docking/capture necessary for asteroid sample return and redirect missions, spacecraft docking, satellite servicing, and space debris removal. During the final stages of landing, from about 1 km to 500 m above the ground, the flash lidar can generate 3-Dimensional images of the terrain to identify hazardous features such as craters, rocks, and steep slopes. The onboard fli1ght computer can then use the 3-D map of terrain to guide the vehicle to a safe location. As an automated rendezvous and docking sensor, the flash lidar can provide relative range, velocity, and bearing from an approaching spacecraft to another spacecraft or a space station from several kilometers distance. NASA Langley Research Center has developed and demonstrated a flash lidar sensor system capable of generating 16k pixels range images with 7 cm precision, at a 20 Hz frame rate, from a maximum slant range of 1800 m from the target area. This paper describes the lidar instrument design and capabilities as demonstrated by the closed-loop flight tests onboard a rocket-propelled free-flyer vehicle (Morpheus). Then a plan for continued advancement of the flash lidar technology will be explained. This proposed plan is aimed at the development of a common sensor that with a modest design adjustment can meet the needs of both landing and proximity operation and docking applications.

Amzajerdian, Farzin↗

Distributed Sensing Node Configuration

A vision and radar sensor integration strategy for surveillance of Advance Air Mobility Mission concept of airspace is contained in the CAD drawing in this publication developed as part of NASA's Transformational Tools and Technology project. 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. Contained herein are drawings that are available in the stp and creo file formats of the distributed sensing nodes. Additional dovetail integration is included to enable rapid changing of embedded system. A day in the life node deployment is included in the 2023_last_flight_day.mp4. Please cite this publication if you use these drawings. This sensor configuration methodology is presented in detail in the publication reference below. Chester Dolph, Thomas Lombaerts, Corey A. Ippolito, Vahram Stepanyan, Evan Kawamura, Keerthana Kannan, George Szatkowski, Todd Ferante, Christopher Morris, Federica Vitiello, Flavia Causa, Roberto Opromolla and Giancarmine Fasano. "Distributed Sensor Fusion of Ground and Air Nodes using Vision and Radar Modalities for Tracking Multirotor Small Uncrewed Air Systems and Birds," AIAA 2024-1781. AIAA SCITECH 2024 Forum. January 2024.

Chester V Dolph↗

Enabling a Voice Management System for Space Applications

The sustainable missions beyond Low Earth Orbit (LEO) envisioned for NASA’s Artemis program will require autonomous capabilities. Moreover, Artemis mission crews will need a means to efficiently interact with a spacecraft’s autonomous systems. This interaction can be facilitated by voice and speech communications because voice-based controls enable users to interact hands- and eyes-free, allowing the user to better focus on critical tasks. The goal of our project was to explore the knowledge and technology needed to successfully design effective Voice User Interfaces (VUIs) for autonomous systems utilizing Human Centered Design (HCD) principles. The focus of the human factors’ aspect of engineering, pays close attention to psychological and physiological principles in the development of autonomous crew operation systems. A main objective was to understand how a crew member, through voice interaction, could efficiently and intuitively communicate with a notional autonomous vehicle system manager. This project was a part of the NASA Moon to Mars eXploration Systems and Habitation (M2M X-Hab) 2020 Academic Innovation Challenge. The work from the BLiSS Team, at the University of Michigan, resulted in the design of a system persona, Diego, to which an astronaut may quickly build trust with autonomous systems, to alleviate known stressors on mental health expected during long duration space missions. Optimal software to facilitate integration of the system persona into a reference Lunar orbiting Gateway station was defined. Additionally, a Speech to Text (STT) system and a Graphical User Interface (GUI) that could be implemented in future missions was developed on an Internet of Things (IOT) platform. The Voice User Interface (VUI) design for the M2M X-Hab 2020 project leveraged previous technology developed by the BLiSS team to incorporate a voice-based interface into 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 spacecraft background noise environment was assessed, a noise mitigation technique was developed, and a relatable personality for the autonomous system was developed in order to facilitate human-like conversations. The success of our effort was largely due to the diversity of the team that included expertise in Space Systems Engineering, Human Computer Interaction, Aerospace Engineering, Computer Science, Biomedical Engineering, and Applied Physics. The diverse perspectives fostered elaborate discussions, resulting in the conception of three main subsystems: (1) User-System, (2) NPAS-System, and (3) Environment-System. The VUI was unique and had to be efficient and intuitive. For this project, 5 subteams were formed, each with a separate objective, Voice Design team, Background Noise Mitigation team, Software Integration team and Graphical User Interface team. The BLiSS team crafted a personality for the VUI to enable human-like conversation and drive user adoption and trust. User surveys were completed and used to help determine the required VUI system personality traits by capturing perspectives and expectations of prospective “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 platform for quick and reliable information transfer. The outcomes of our research were: (1) a working prototype user interface, that is compatible with NASA’s NPAS platform; (2) software that demonstrates the ability of the VUI system 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 in a noisy environment. Our research has laid the foundation for the development of VUI’s for autonomy, and provides a baseline for future VUI developments.

Voice user interface↗

Designing an autonomous environment for mission critical operation of the EUVE satellite

Since the launch of NASA's Extreme Ultraviolet Explorer (EUVE) satellite in 1992, there has only been a handful of occurrences that have warranted manual intervention in the EUVE Science Operations Center (ESOC). So, in an effort to reduce costs, the current environment is being redesigned to utilize a combination of off-the-shelf packages and recently developed artificial intelligence (AI) software to automate the monitoring of the science payload and ground systems. The successful implementation of systemic automation would allow the ESOC to evolve from a seven day/week, three shift operation, to a seven day/week one shift operation. First, it was necessary to identify all areas considered mission critical. These were defined as follows: (1) The telemetry stream must be monitored autonomously and anomalies identified. (2) Duty personnel must be automatically paged and informed of the occurrence of an anomaly. (3) The 'basic' state of the ground system must be assessed. (4) Monitors should check that the systems and processes needed to continue in a 'healthy' operational mode are working at all times. (5) Network loads should be monitored to ensure that they stay within established limits. (6) Connectivity to Goddard Space Flight Center (GSFC) systems should be monitored as well, not just for connectivity of the network itself but also for the ability to transfer files. (7) All necessary peripheral devices should be monitored. This would include the disks, routers, tape drives, printers, tape carousel, and power supplies. (8) System daemons such as the archival daemon, the Sybase server, the payload monitoring software, and any other necessary processes should be monitored to ensure that they are operational. (9) The monitoring system needs to be redundant so that the failure of a single machine will not paralyze the monitors. (10) Notification should be done by means of looking though a table of the pager numbers for current 'on call' personnel. The software should be capable of dialing out to notify, sending email, and producing error logs. (11) The system should have knowledge of when real-time passes and tape recorder dumps will occur and should know that these passes and data transmissions are successful. Once the design criteria were established, the design team split into two groups: one that addressed the tracking, commanding, and health and safety of the science payload and another group that addressed the ground systems and communications aspects of the overall system.

Abedini, Annadiana↗

Using Multimodal Input for Autonomous Decision Making for Unmanned Systems

Autonomous decision making in the presence of uncertainly is a deeply studied problem space particularly in the area of autonomous systems operations for land, air, sea, and space vehicles. Various techniques ranging from single algorithm solutions to complex ensemble classifier systems have been utilized in a research context in solving mission critical flight decisions. Realized systems on actual autonomous hardware, however, is a difficult systems integration problem, constituting a majority of applied robotics development timelines. The ability to reliably and repeatedly classify objects during a vehicles mission execution is vital for the vehicle to mitigate both static and dynamic environmental concerns such that the mission may be completed successfully and have the vehicle operate and return safely. In this paper, the Autonomy Incubator proposes and discusses an ensemble learning and recognition system planned for our autonomous framework, AEON, in selected domains, which fuse decision criteria, using prior experience on both the individual classifier layer and the ensemble layer to mitigate environmental uncertainty during operation.

Neilan, James H.↗

A network control concept for the 30/20 GHz communication system baseband processor

The architecture and system design for a satellite-switched TDMA communication system employing on-board processing was developed by Motorola for NASA's Lewis Research Center. The system design is based on distributed processing techniques that provide extreme flexibility in the selection of a network control protocol without impacting the satellite or ground terminal hardware. A network control concept that includes system synchronization and allows burst synchronization to occur within the system operational requirement is described. This concept integrates the tracking and control links with the communication links via the baseband processor, resulting in an autonomous system operational approach.

Sabourin, D. J.↗

Evaluation of Crew-Centric Onboard Mission Operations Planning and Execution Tool: Year 2

Currently, mission planning for the International Space Station (ISS) is largely affected by ground operators in mission control. The task of creating a week-long mission plan for ISS crew takes dozens of people multiple days to complete, and is often created far in advance of its execution. As such, re-planning or adapting to changing real-time constraints or emergent issues is similarly taxing. As we design for future mission operations concepts to other planets or areas with limited connectivity to Earth, more of these ground-based tasks will need to be handled autonomously by the crew onboard.There is a need for a highly usable (including low training time) tool that enables efficient self-scheduling and execution within a single package. The ISS Program has identified Playbook as a potential option. It already has high crew acceptance as a plan viewer from previous analogs and can now support a crew self-scheduling assessment on ISS or on another mission. The goals of this work, a collaboration between the Human Research Program and the ISS Program, are to inform the design of systems for more autonomous crew operations and provide a platform for research on crew autonomy for future deep space missions. Our second year of the research effort have included new insights on the crew self-scheduling sessions performed by the crew through use on the HERA (Human Exploration Research Analog) and NEEMO (NASA Extreme Environment Mission Operations) analogs. Use on the NEEMO analog involved two self-scheduling strategies where the crew planned and executed two days of EVAs (Extra-Vehicular Activities). On HERA year two represented the first HERA campaign where we were able to perform research tasks. This involved selected flexible activities that the crew could schedule, mock timelines where the crew completed more complex planning exercises, usability evaluation of the crew self-scheduling features, and more insights into the limit of plan complexity that the crew could effectively self-schedule. In parallel we have added in new features and functionality in the Playbook tool based off of our insights from crew self-scheduling in the NASA analogs. In particular this year we have added in the ability for the crew to add, edit, and remove their own activities in the Playbook tool, expanding the type of planning and re-planning possible in the tool and opening up the ability for more free form plan creation. The ability to group and manipulate groups of activities from the plan task list was also added, allowing crew members to add predefined sets of activities onto their mission timeline. In addition we also added a way for crew members to roll back changes in their plan, in order to allow an undo like capability. These features expand and complement the initial self-scheduling features added in year one with the goal of making crew autonomous planning more efficient. As part of this work we have also finished developing the first version of our Playbook Data Analysis Tool, a research tool built to interpret and analyze the unobtrusively collected data obtained during the NASA analog missions through Playbook. This data which includes user click interaction as well as plan change information, through the Playbook Data Analysis Tool, allows us to playback this information as if a video camera was mounted over the crewmember's tablet. While the primary purpose of this tool is to allow usability analysis of crew self-scheduling sessions used on the NASA analog, since the data collected is structured, the tool can automatically derive metrics that would be traditionally tedious to achieve without manual analysis of video playback. We will demonstrate and discuss the ability for future derived metrics to be added to the tool. In addition to the current data and results gathered in year two we will also discuss the preparation and goals of our International Space Station (ISS) onboard technology demonstration with Playbook. This technology demonstration will be preformed as part of the CAST payload starting in late 2016.

onboard planning↗