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Development of an Airspace Simulation and Modeling Tool for Enhanced Spectrum Management

The emergence of new aerial vehicles into the National Airspace System creates an increased demand for aeronautical communications to support aviation operations. However, the issue of spectrum scarcity remains an ever-present concern, and the growing demand cannot be supported using existing spectrum allocation strategies. As a result, a new spectrum management approach is required, and the National Aeronautics and Space Administration (NASA) is investigating advanced concepts to modernize the management and use of aviation spectrum by leveraging the latest advancements in wireless communications, big data and machine learning. This research proposes an autonomous spectrum allocation concept, which allocates communications resources, such as spectrum and power, based on the predicted communications and air traffic demands throughout the airspace, as opposed to the use of fixed allocations as is done today. This approach will result in improved spectrum utilization efficiency and enhanced airspace capacity. The autonomous spectrum allocation concept decomposes into three research areas: demand prediction, resource allocation, and use case evaluation. As part of the use case evaluation effort, a modeling and simulation capability is currently under development. This simulation capability includes the implementation of various features, including visualization of both live or virtually-generated airspace traffic, simulation scenario development, simulation management with data collection, and flight plan creation with corresponding trajectory generation. This modeling and simulation capability will continue to evolve as new and advanced airspace applications are introduced into existing and emerging operational environments.

Eric J. Knoblock

Autonomous planetary rover at Carnegie Mellon

This report describes progress in research on an autonomous robot for planetary exploration. In 1989, the year covered by this report, a six-legged walking robot, the Ambler, was configured, designed, and constructed. This configuration was used to overcome shortcomings exhibited by existing wheeled and walking robot mechanisms. The fundamental advantage of the Ambler is that the actuators for body support are independent of those for propulsion; a subset of the planar joints propel the body, and the vertical actuators support and level the body over terrain. Models of the Ambler's dynamics were developed and the leveling control was studied. An integrated system capable of walking with a single leg over rugged terrain was implemented and tested. A prototype of an Ambler leg is suspended below a carriage that slides along rails. To walk, the system uses a laser scanner to find a clear, flat foothold, positions the leg above the foothold, contacts the terrain with the foot, and applies force enough to advance the carriage along the rails. Walking both forward and backward, the system has traversed hundreds of meters of rugged terrain including obstacles too tall to step over, trenches too deep to step in, closely spaced rocks, and sand hills. In addition, preliminary experiments were conducted with concurrent planning and execution, and a leg recovery planner that generates time and power efficient 3D trajectories using 2D search was developed. A Hero robot was used to demonstrate mobile manipulation. Indoor tasks include collecting cups from the lab floor, retrieving printer output, and recharging when its battery gets low. The robot monitors its environment, and handles exceptional conditions in a robust fashion, using vision to track the appearance and disappearance of cups, onboard sonars to detect imminent collisions, and monitors to detect the battery level.

Whittaker, William

Development Approach for the Accommodation of Materials Science Research for the Materials Science Research Facility on the International Space Station

The Materials Science Research Facility (MSRF) is a modular facility comprised of autonomous Materials Science Research Racks (MSRR's) for research in the microgravity environment afforded by the International Space Station (ISS). The initial MSRF concept consists of three Materials Science Research Racks (MSRR-1, MSRR-2, and MSRR-3) which will be developed for a phased deployment beginning on the third Utilization Flight (UF-3). The facility will house materials processing apparatus and common subsystems required for operating each device. Each MSRR is a stand alone autonomous rack and will be comprised of either on-orbit replaceable Experiment Modules, Module Inserts, investigation unique apparatus, and/or multiuser generic processing apparatus. Each MSRR will support a wide range of materials science themes in the NASA research program and will use the ISS Active Rack Isolation System (ARIS). MSRF is being developed for the United States Laboratory Module and will provide the apparatus for satisfying near-term and long-range Materials Science Discipline goals and objectives.

Schaefer, D. A.

Handling Trajectory Uncertainties for Airborne Conflict Management

Airborne conflict management is an enabling capability for NASA's Distributed Air-Ground Traffic Management (DAG-TM) concept. DAGTM has the goal of significantly increasing capacity within the National Airspace System, while maintaining or improving safety. Under DAG-TM, autonomous aircraft maintain separation from each other and from managed aircraft unequipped for autonomous flight. NASA Langley Research Center has developed the Autonomous Operations Planner (AOP), an onboard decision support system that provides airborne conflict management (ACM) and strategic flight planning support for autonomous aircraft pilots. The AOP performs conflict detection, prevention, and resolution from nearby traffic aircraft and area hazards. Traffic trajectory information is assumed to be provided by Automatic Dependent Surveillance Broadcast (ADS-B). Reliable trajectory prediction is a key capability for providing effective ACM functions. Trajectory uncertainties due to environmental effects, differences in aircraft systems and performance, and unknown intent information lead to prediction errors that can adversely affect AOP performance. To accommodate these uncertainties, the AOP has been enhanced to create cross-track, vertical, and along-track buffers along the predicted trajectories of both ownship and traffic aircraft. These buffers will be structured based on prediction errors noted from previous simulations such as a recent Joint Experiment between NASA Ames and Langley Research Centers and from other outside studies. Currently defined ADS-B parameters related to navigation capability, trajectory type, and path conformance will be used to support the algorithms that generate the buffers.

Barhydt, Richard

Interface of the transport systems research vehicle monochrome display system to the digital autonomous terminal access communication data bus

An upgrade of the transport systems research vehicle (TSRV) experimental flight system retained the original monochrome display system. The original host computer was replaced with a Norden 11/70, a new digital autonomous terminal access communication (DATAC) data bus was installed for data transfer between display system and host, while a new data interface method was required. The new display data interface uses four split phase bipolar (SPBP) serial busses. The DATAC bus uses a shared interface ram (SIR) for intermediate storage of its data transfer. A display interface unit (DIU) was designed and configured to read from and write to the SIR to properly convert the data from parallel to SPBP serial and vice versa. It is found that separation of data for use by each SPBP bus and synchronization of data tranfer throughout the entire experimental flight system are major problems which require solution in DIU design. The techniques used to accomplish these new data interface requirements are described.

Easley, W. C.

UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations

Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.

Davila, Carlos G.

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight methods is paramount for establishing an effective architecture for autonomous systems. A fundamental objective of the ATTRACTOR (Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability) project was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation environment for test and evaluation of autonomous systems. The Autonomous Entity Operations Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single- and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. Together AEON and BEAM enable sim-to-flight with minimal configuration changes. By using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the lab and in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight methods is paramount for establishing an effective architecture for autonomous systems. A fundamental objective of the ATTRACTOR (Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability) project was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation environment for test and evaluation of autonomous systems. The Autonomous Entity Operations Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single- and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. Together AEON and BEAM enable sim-to-flight with minimal configuration changes. By using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the lab and in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley

Preliminary Concepts for the Materials Science Research Facility on the International Space Station

The Materials Science Research Facility (MSRF) is designed to accommodate the current and evolving cadre of peer-reviewed materials science investigations selected to conduct research in the microgravity environment of the International Space Station (ISS). The MSRF consists of modular autonomous Materials Science Research Racks (MSRR's). The initial MSRF concept consists of three Materials Science Research Racks (MSRR-1, MSRR-2, and MSRR-3) which will be developed for a phased deployment beginning on Utilization Flight 3. Each MSRR is a stand-alone autonomous rack and will be comprised of either on-orbit replaceable Experiment Modules, Module Inserts, investigation unique apparatus, or multi-user generic processing apparatus Each MSRR will support a wide variety of scientific investigations.

Cobb, S.D.

Reflections on 20 Years of Research on the International Space Station

November 2, 2000 began an era of continuous human presence on the International Space Station (ISS). That first crewed expedition to the ISS had few scientific instruments and facilities to work with, yet managed to conduct 52research investigations. Today, crew oversee upwards of 300 investigations during their time aboard. Indeed, over the past 20 years the ISS has evolved into a robust laboratory with dozens of research facilities, capabilities for the autonomous monitoring and conduct of research, and a growing array of scientific tools available and observational instruments active. As a result, the station has hosted more than 3,000 research investigations generating more than 2,400 scientific publications across every major discipline of science. The ISS Program Science Forum is composed of senior science representatives across the station’s international partnership. It provides multilateral science leadership to the ISS Program. Indeed, ISS research has evolved to become a truly international activity encompassing the participation of more than 4,000 investigators from over 100 countries whose research has been completed or is ongoing. This paper provides an overview of the research and technology development conducted to date and reflects upon the accomplishments, impacts and future direction of ISS research from the perspective of the member organizations of the Program Science Forum. Research areas which have been a focus of ISS research to date and key implications both for future space exploration and scientific advancement are presented. Major Earth benefits derived from ISS research are discussed. Finally, the paper provides insight into areas of emphasis for future research including the maturation of technological capabilities needed for deep space exploration, including lunar exploration programs such as Artemis and future missions to Mars

International Space Station

ARK: Autonomous mobile robot in an industrial environment

This paper describes research on the ARK (Autonomous Mobile Robot in a Known Environment) project. The technical objective of the project is to build a robot that can navigate in a complex industrial environment using maps with permanent structures. The environment is not altered in any way by adding easily identifiable beacons and the robot relies on naturally occurring objects to use as visual landmarks for navigation. The robot is equipped with various sensors that can detect unmapped obstacles, landmarks and objects. In this paper we describe the robot's industrial environment, it's architecture, a novel combined range and vision sensor and our recent results in controlling the robot in the real-time detection of objects using their color and in the processing of the robot's range and vision sensor data for navigation.

Nickerson, S. B.

A Grassroots Network and Community Roadmap for Interconnected Autonomous Science Laboratories for Accelerated Discovery

Scientific discovery is being revolutionized by AI and autonomous systems, yet current autonomous laboratories remain isolated islands unable to collaborate across institutions. We present the Autonomous Interconnected Science Lab Ecosystem (AISLE), a grassroots network transforming fragmented capabilities into a unified system that shorten the path from ideation to innovation to impact and accelerates discovery from decades to months. AISLE addresses five critical dimensions: (1) cross-institutional equipment orchestration, (2) intelligent data management with FAIR compliance, (3) AI-agent driven orchestration grounded in scientific principles, (4) interoperable agent communication interfaces, and (5) AI/ML-integrated scientific education. By connecting autonomous agents across institutional boundaries, autonomous science can unlock research spaces inaccessible to traditional approaches while democratizing cutting-edge technologies. This paradigm shift toward collaborative autonomous science promises breakthroughs in sustainable energy, materials development, and public health.

Ferreira da Silva, Rafael [Oak Ridge National Labo

A Persistent Simulation Environment for Autonomous Systems

The age of Autonomous Unmanned Aircraft Systems (AUAS) is creating new challenges for the accreditation and certification requiring new standards, policies and procedures that sanction whether a UAS is safe to fly. Establishing a basis for certification of autonomous systems via research into trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR), a new NASA Convergent Aeronautics Solution (CAS) project. Simulation Environments to test and evaluate AUAS decision making may be a low-cost solution to help certify that various AUAS systems are trustworthy enough to be allowed to fly in current general and commercial aviation airspace. NASA is working to build a peer-to-peer persistent simulation (P3 Sim) environment. The P3 Sim will be a Massively Multiplayer Online (MMO) environment were AUAS avatars can interact with a complex dynamic environment and each other. The focus of the effort is to provide AUAS researchers a low-cost intuitive testing environment that will aid training for and assessment of decisions made by autonomous systems such as AUAS. This presentation focuses on the design approach and challenges faced in development of the P3 Sim Environment is support of investigating trustworthiness of autonomous systems.

Kelley, Benjamin N.

Applications of graphics to support a testbed for autonomous space vehicle operations

Researchers describe their experience using graphics tools and utilities while building an application, AUTOPS, that uses a graphical Machintosh (TM)-like interface for the input and display of data, and animation graphics to enhance the presentation of results of autonomous space vehicle operations simulations. AUTOPS is a test bed for evaluating decisions for intelligent control systems for autonomous vehicles. Decisions made by an intelligent control system, e.g., a revised mission plan, might be displayed to the user in textual format or he can witness the effects of those decisions via out of window graphics animations. Although a textual description conveys essentials, a graphics animation conveys the replanning results in a more convincing way. Similarily, iconic and menu-driven screen interfaces provide the user with more meaningful options and displays. Presented here are experiences with the SunView and TAE Plus graphics tools used for interface design, and the Johnson Space Center Interactive Graphics Laboratory animation graphics tools used for generating out out of the window graphics.

Schmeckpeper, K. R.

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight frameworks is paramount for establishing an effective architecture for autonomous systems. Hardware test flights are time-consuming and cost prohibitive during early system design and development. Simulation environments can be useful tools to accelerate algorithm development and testing. However, transitions from simulation to flight (sim-to-flight) can be challenging, unless systems are designed with this transition in mind and with the necessary capabilities built into the architecture and framework. One of the objectives of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. ATTRACTOR’s objective was to construct computational concepts of trustworthiness and justifiable trust in multi-agent autonomous teams, to inform future certification of safety-critical and time-critical autonomous systems in aviation. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation (ModSim) environment for test and evaluation of autonomous systems. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single-and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. The Autonomous Entity Operational Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications, enabling sim-to-flight with minimal configuration changes. Using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley

Overview of Challenges to Integrating Remotely-Piloted Operations into the National Airspace System

An oral presentation summarizing key challenges to integrating remotely-piloted operations into the National Airspace System. The presentation provides an overview of NASA's Pathfinding for an Airspace with Autonomous Vehicles sub-project, recent research activities focused on enabling autonomous cargo delivery, and some of the challenges that have been learned so far from these activities.

Husni Idris

Intelligent data reduction for autonomous power systems

Since 1984 Marshall Space Flight Center was actively engaged in research and development concerning autonomous power systems. Much of the work in this domain has dealt with the development and application of knowledge-based or expert systems to perform tasks previously accomplished only through intensive human involvement. One such task is the health status monitoring of electrical power systems. Such monitoring is a manpower intensive task which is vital to mission success. The Hubble Space Telescope testbed and its associated Nickel Cadmium Battery Expert System (NICBES) were designated as the system on which the initial proof of concept for intelligent power system monitoing will be established. The key function performed by an engineer engaged in system monitoring is to analyze the raw telemetry data and identify from the whole only those elements which can be considered significant. This function requires engineering expertise on the functionality of the system, the mode of operation and the efficient and effective reading of the telemetry data. Application of this expertise to extract the significant components of the data is referred to as data reduction. Such a function possesses characteristics which make it a prime candidate for the application of knowledge-based systems' technologies. Such applications are investigated and recommendations are offered for the development of intelligent data reduction systems.

Floyd, Stephen A.