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Autonomy Verification & Validation Roadmap and Vision 2045

Advanced capabilities planned for the next generation of autonomous and increasingly autonomous air vehicles will include non-traditional components based on artificial intelligence, machine learning, and complex optimization and planning algorithms. These complex components will be used to provide enhanced safety and high-level decision-making functions. However, there are serious barriers to the deployment of autonomous aircraft in the National Airspace System (NAS). Current civil aviation certification processes are based on the concept that the correct behavior of a system or a component must be completely specified and verified prior to operation. This report from the Autonomy Verification and Validation (V&V) Roadmap and Vision 2045 project presents the most recent effort to build a comprehensive list of verification challenges and needs for autonomous aircraft, a roadmap to meet those autonomy V&V needs, the services they can enable, and point to the certification gaps they fill. To accomplish these goals, we assembled a team of world-class researchers from the aerospace industry (Boeing, Collins Aerospace, and GeneralElectric) and academia (University of Michigan, University of Texas, and Massachusetts Institute of Technology) with deep expertise in autonomy, aerospace systems, and assurance of Artificial Intelligence/machine learning systems.

Software Assurance↗

Enabling Advanced Automation in Spacecraft Operations with the Spacecraft Emergency Response System

True autonomy is the Holy Grail of spacecraft mission operations. The goal of launching a satellite and letting it manage itself throughout its useful life is a worthy one. With true autonomy, the cost of mission operations would be reduced to a negligible amount. Under full autonomy, any problems (no matter the severity or type) that may arise with the spacecraft would be handled without any human intervention via some combination of smart sensors, on-board intelligence, and/or smart automated ground system. Until the day that complete autonomy is practical and affordable to deploy, incremental steps of deploying ever-increasing levels of automation (computerization of once manual tasks) on the ground and on the spacecraft are gradually decreasing the cost of mission operations. For example, NASA's Goddard Space Flight Center (NASA-GSFC) has been flying spacecraft with low cost operations for several years. NASA-GSFC's SMEX (Small Explorer) and MIDEX (Middle Explorer) missions have effectively deployed significant amounts of automation to enable the missions to fly predominately in 'light-out' mode. Under light-out operations the ground system is run without human intervention. Various tools perform many of the tasks previously performed by the human operators. One of the major issues in reducing human staff in favor of automation is the perceived increased in risk of losing data, or even losing a spacecraft, because of anomalous conditions that may occur when there is no one in the control center. When things go wrong, missions deploying advanced automation need to be sure that anomalous conditions are detected and that key personal are notified in a timely manner so that on-call team members can react to those conditions. To ensure the health and safety of its lights-out missions, NASA-GSFC's Advanced Automation and Autonomy branch (Code 588) developed the Spacecraft Emergency Response System (SERS). The SERS is a Web-based collaborative environment that enables secure distributed fault and resource management. The SERS incorporates the use of intelligent agents, threaded discussions, workflow, database connectivity, and links to a variety of communications devices (e.g., two-way paging, PDA's, and Internet phones) via commercial gateways. When the SERS detects a problem, it notifies on-call team members, who then can remotely take any necessary actions to resolve the anomalies.The SERS goes well beyond a simple '911' system that sends out an error code to everyone with a pager. Instead, SERS' software agents send detailed data (i.e., notifications) to the most appropriate team members based on the type and severity of the anomaly and the skills of the on-call team members. The SERS also allows the team members to respond to the notifications from their wireless devices. This unique capability ensures rapid response since the team members no longer have to go to a PC or the control center for every anomalous event. Most importantly, the SERS enables safe experimentation with various techniques for increasing levels of automation, leading to robust autonomy. For the MIDEX missions at NASA GSFC, the SERS is used to provide 'human-in-the-loop' automation. During lights-out operations, as greater control is given to the MIDEX automated systems, the SERS can be configured to page remote personnel and keep them informed regarding actions taking place in the control center. Remote off-duty operators can even be given the option of enabling or inhibiting a specific automated response in near real time via their two-way pagers. The SERS facilitates insertion of new technology to increase automation, while maintaining the safety and security of mission resources. This paper will focus on SERS' overall functionality and how SERS has been designed to handle the monitoring and emergency response for missions with varying levels of automation. The paper will also convey some of the key lessons learned from SERS' deployment across of variety of missions, highlighting this incremental approach to achieving 'robust autonomy'.

Breed, Julie↗

AMO-EXPRESS-2.5: Crew Autonomy Onboard the International Space Station

NASA is committed to landing American astronauts, including the first woman and the next man, on the Moon by 2024. Currently, the crew cannot take on all functions performed by the ground today, so the future crews will need more automation to reduce the crew workload for future missions. Of significant importance for these missions is the balance between crew autonomy and vehicle automation. The Advanced Exploration Systems (AES) Autonomous Systems and Operations (ASO) Project has been investigating the ability to evaluate crew self-scheduling and activity monitoring for future space missions. The ASO project designed the Autonomous Mission and Operations- EXpedite the PRocessing of Experiments to Space Station Rack-2.5 (AMO-EXPRESS-2.5) payload to evaluate crew self-scheduling and activity monitoring. The AMO-EXPRESS-2.5 builds on the previous AMO-EXPRESS and AMO-EXPRESS-2.0 demonstrations on ISS. The AMO-EXPRESS-2.5 demonstration goals are to prove crew self-scheduling by planning through diagnosing systems expertise, failure detection, procedure recommendation and situational awareness. This paper will describe the development, test and execution results of the AMO-EXPRESS-2.5 demonstration, and will also outline the future planned development and operational efforts to enable autonomy for future deep space manned missions.

Brooke C. Allen↗

NASA IVHM Technology Experiment for X-vehicles (NITEX)

The purpose of the NASA IVHM Technology Experiment for X-vehicles (NITEX) is to advance the development of selected IVHM technologies in a flight environment and to demonstrate the potential for reusable launch vehicle ground processing savings. The technologies to be developed and demonstrated include system-level and detailed diagnostics for real-time fault detection and isolation, prognostics for fault prediction, automated maintenance planning based on diagnostic and prognostic results, and a microelectronics hardware platform. Complete flight The Evolution of Flexible Insulation as IVHM consists of advanced sensors, distributed data acquisition, data processing that includes model-based diagnostics, prognostics and vehicle autonomy for control or suggested action, and advanced data storage. Complete ground IVHM consists of evolved control room architectures, advanced applications including automated maintenance planning and automated ground support equipment. This experiment will advance the development of a subset of complete IVHM.

Sandra, Hayden↗

A Facility and Architecture for Autonomy Research

Autonomy is a key enabling factor in the advancement of the remote robotic exploration. There is currently a large gap between autonomy software at the research level and software that is ready for insertion into near-term space missions. The Mission Simulation Facility (MST) will bridge this gap by providing a simulation framework and suite of simulation tools to support research in autonomy for remote exploration. This system will allow developers of autonomy software to test their models in a high-fidelity simulation and evaluate their system's performance against a set of integrated, standardized simulations. The Mission Simulation ToolKit (MST) uses a distributed architecture with a communication layer that is built on top of the standardized High Level Architecture (HLA). This architecture enables the use of existing high fidelity models, allows mixing simulation components from various computing platforms and enforces the use of a standardized high-level interface among components. The components needed to achieve a realistic simulation can be grouped into four categories: environment generation (terrain, environmental features), robotic platform behavior (robot dynamics), instrument models (camera/spectrometer/etc.), and data analysis. The MST will provide basic components in these areas but allows users to plug-in easily any refined model by means of a communication protocol. Finally, a description file defines the robot and environment parameters for easy configuration and ensures that all the simulation models share the same information.

Pisanich, Greg↗

Robots for Astrobiology!

The search for life and its study is known as astrobiology. Conducting that search on other planets in our Solar System is a major goal of NASA and other space agencies, and a driving passion of the community of scientists and engineers around the world. We practice for that search in many ways, from exploring and studying extreme environments on Earth, to developing robots to go to other planets and help us look for any possible life that may be there or may have been there in the past. The unique challenges of space exploration make collaborations between robots and humans essential. The products of those collaborations will be novel and driven by the features of wholly new environments. For space and planetary environments that are intolerable for humans or where humans present an unacceptable risk to possible biologically sensitive sites, autonomous robots or telepresence offer excellent choices. The search for life signs on Mars fits within this category, especially in advance of human landed missions there, but also as assistants and tools once humans reach the Red Planet. For planetary destinations where we do not envision humans ever going in person, like bitterly cold icy moons, or ocean worlds with thick ice roofs that essentially make them planetary-sized ice caves, we will rely on robots alone to visit those environments for us and enable us to explore and understand any life that we may find there. Current generation robots are not quite ready for some of the tasks that we need them to do, so there are many opportunities for roboticists of the future to advance novel types of mobility, autonomy, and bio-inspired robotic designs to help us accomplish our astrobiological goals. We see an exciting partnership between robotics and astrobiology continually strengthening as we jointly pursue the quest to find extraterrestrial life.

Robotics↗

Evolution paths for advanced automation

As Space Station Freedom (SSF) evolves, increased automation and autonomy will be required to meet Space Station Freedom Program (SSFP) objectives. As a precursor to the use of advanced automation within the SSFP, especially if it is to be used on SSF (e.g., to automate the operation of the flight systems), the underlying technologies will need to be elevated to a high level of readiness to ensure safe and effective operations. Ground facilities supporting the development of these flight systems -- from research and development laboratories through formal hardware and software development environments -- will be responsible for achieving these levels of technology readiness. These facilities will need to evolve support the general evolution of the SSFP. This evolution will include support for increasing the use of advanced automation. The SSF Advanced Development Program has funded a study to define evolution paths for advanced automaton within the SSFP's ground-based facilities which will enable, promote, and accelerate the appropriate use of advanced automation on-board SSF. The current capability of the test beds and facilities, such as the Software Support Environment, with regard to advanced automation, has been assessed and their desired evolutionary capabilities have been defined. Plans and guidelines for achieving this necessary capability have been constructed. The approach taken has combined indepth interviews of test beds personnel at all SSF Work Package centers with awareness of relevant state-of-the-art technology and technology insertion methodologies. Key recommendations from the study include advocating a NASA-wide task force for advanced automation, and the creation of software prototype transition environments to facilitate the incorporation of advanced automation in the SSFP.

Healey, Kathleen J.↗

Promoting Astronaut Autonomy in Human Spaceflight Missions

Mission operations will have to adapt for long duration, long distance human spaceflight missions. This change is driven mainly by the significantly different communication availability between Earth and space. As astronauts travel farther from Earth, the one-way communication latency increases; the amount of bandwidth will be limited; and there will be period of long and/or no communication. Currently, ground flight controllers collaborate and cooperate with astronauts in space to accomplish essential operational functions. Astronaut autonomy, i.e., the crew’s ability to work more independently from mission control, will be a key enabler in future exploration missions. Over the last several years, the NASA Ames Human-Computer Interaction (HCI) Group has investigated various ways to promote and support astronaut autonomy in human spaceflight missions. Software prototypes are researched, designed, implemented, and assessed for their ability to enable astronaut autonomy. From integrated Internet of Thing for Space, advanced procedures interfaces, comm-delayed chats, and self-scheduling tools, the HCI Group has explored different aspects of astronaut autonomy. Specifically, the self-scheduling tool Playbook has been evaluated in analog extreme environments and onboard the International Space Station, successfully paving the way for future autonomous astronauts.

crew autonomy↗

The Challenges of Human-Autonomy Teaming

Machine intelligence is improving rapidly based on advances in big data analytics, deep learning algorithms, networked operations, and continuing exponential growth in computing power (Moores Law). This growth in the power and applicability of increasingly intelligent systems will change the roles humans, shifting them to tasks where adaptive problem solving, reasoning and decision-making is required. This talk will address the challenges involved in engineering autonomous systems that function effectively with humans in aeronautics domains.

Human-Autonomy teaming↗

The Challenges of Human-Autonomy Teaming

Machine intelligence is improving rapidly based on advances in big data analytics, deep learning algorithms, networked operations, and continuing exponential growth in computing power (Moores Law). This growth in the power and applicability of increasingly intelligent systems will change the roles humans, shifting them to tasks where adaptive problem solving, reasoning and decision-making is required. This talk will address the challenges involved in engineering autonomous systems that function effectively with humans in aeronautics domains.

artificial intelligence↗

Digital Flight Rules

Explore the source record for details and available documents.

Digital Flight Rules↗

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems.

context-sensitive↗

A Modeling Approach for Handling Qualities and Controls Safety Analysis of Electric Air Taxi Vehicles

The combination of modern advances in electric propulsion, fly-by-wire controls, autonomy, and increasing demand for short range air taxi operations, is currently producing an outburst of vehicle designs more diverse than ever before. Advanced software tools are needed to support the rapid and safe introduction of any design into the airspace, including the safety of the deployed flight control system and vehicle handling qualities. This paper presents a methodology for building air taxi vehicle models with distributed electric propulsion for use in analyzing flight control system safety at the conceptual design level.The approach builds on existing software tools capable of outputting aeromechanics-based linear perturbation models for Vertical Take-off and Landing vehicles with multiple rotors. Rotor torque inputs are then converted into equivalent voltage control inputs, and the linear state and input dynamics matrices are modified to include electric motor dynamics with common parameters for direct-current electric motors. The linear perturbation dynamics are then stitched across multiple operating points into a quasi-Linear Parameter Varying model that covers the full flight envelope. A Model Predictive Controller is developed for use with the full envelope model, and a tradeoff analysis between handling quality and motor requirements is demonstrated using a six passenger NASA air taxi reference design.

Urban Air Mobility↗

Simulating Autonomous Telecommunication Networks for Space Exploration

Currently, most interplanetary telecommunication systems require human intervention for command and control. However, considering the range from near Earth to deep space missions, combined with the increase in the number of nodes and advancements in processing capabilities, the benefits from communication autonomy will be immense. Likewise, greater mission science autonomy brings the need for unscheduled, unpredictable communication and network routing. While the terrestrial Internet protocols are highly developed their suitability for space exploration has been questioned. JPL has developed the Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE) tool to help characterize network designs and protocols. The results will allow future mission planners to better understand the trade offs of communication protocols. This paper discusses various issues with interplanetary network and simulation results of interplanetary networking protocols.

Segui, John S.↗

Crew Health and Performance Integrated Data System Platform Project Updates

Future human exploration missions introduce a new paradigm as crews move further from the resupply and near real-time ground support typical of Low Earth Orbit missions today. Without immediate support from ground-based personnel, exploration crews will be more reliant on inflight data and technology to respond to emergencies and anomalies. Today, in-flight data is often siloed, unsynchronized, and largely inaccessible in real time. Many data sets require manual entry and/or data transfer between vehicles and the ground. These issues contribute to risks in supporting crew autonomy for future exploration missions. An integrated data system platform is needed to mitigate these risks by supporting a new generation of technologies and employing advanced analytical and predictive modeling techniques to enable crew autonomy for future exploration missions. The Crew Health and Performance Integrated Data System Platform (CHP-IDSP) project is laying a foundation for future in-flight informatics by providing a back-end architecture for collecting, storing, and integrating multiple sources of data generated by and around the crew. This cohesive integration point will streamline the management of CHP data (e.g., environmental, exercise, medical, sleep, performance, etc.) and facilitate situation awareness and decision support required by the crew and remote support of exploration missions. This presentation will describe the ongoing development effort of the path-to-flight CHP-IDSP software and the demonstration of its core capabilities. This includes a brief history of the project, the human-centered process used to identify data needs and workflows feeding the development of scenarios and requirements, and current subsystem development status. Current integrations, including the Chiron exploration electronic health record application, will be discussed. Future work includes collaboration with additional CHP domains and a flight technology demonstration.

Data integration↗

Crew Health and Performance Integrated Data Service Platform (CHP-IDSP): Project Updates

Future human exploration missions introduce a new paradigm as crews move further from the resupply and near real-time ground support typical of Low Earth Orbit missions today. Without immediate support from ground-based personnel, exploration crews will be more reliant on inflight data and technology to respond to emergencies and anomalies. Today, in-flight data is often siloed, unsynchronized, and largely inaccessible in real time. Many data sets require manual entry and/or data transfer between vehicles and the ground. These issues contribute to risks in supporting crew autonomy for future exploration missions. An integrated data services platform is needed to mitigate these risks by supporting a new generation of technologies and employing advanced analytical and predictive modeling techniques to enable crew autonomy for future exploration missions. The Crew Health and Performance Integrated Data System Platform (CHP-IDSP) project is laying a foundation for future in-flight informatics by providing a back-end architecture for collecting, storing, and integrating multiple sources of data generated by and around the crew. This cohesive integration point will streamline the management of CHP data (e.g., environmental, exercise, medical, sleep, performance, etc.) and facilitate situation awareness and decision support required by the crew and remote support of exploration missions. This presentation will describe the ongoing development effort of the path-to-flight CHP-IDSP software and the demonstration of its core capabilities. This includes a brief history of the project, the human-centered process used to identify data needs and workflows feeding the development of scenarios and requirements, and current subsystem development status. Current integrations, including the Chiron exploration electronic health record application, will be discussed. Future work includes collaboration with additional CHP domains and a flight technology demonstration.

Software↗

Preliminary Development of Multi-Vehicle (m:N) Operations with NASA Langley’s Remote Vehicle Operations Center

To achieve the vision of Advanced Air Mobility (AAM), a transition from localized operations of aircraft to remote operations is being pursued across many use cases. This transition will allow fewer human operators to manage more increasingly autonomous aircraft (i.e., m operators managing N vehicles, or m:N). To study this operational concept, the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) has developed a prototype remote vehicle operations center and ground control station (GCS) software to conduct research with simulated and real flight operations. To date, flight operations at LaRC have been limited to one vehicle per operator. However, the current paper describes initial development and considerations for enabling m:N flight operations at LaRC. Further, the research described in this paper provides the foundation for a concept of operations (ConOps) that will be developed to support remote operators managing multiple increasingly autonomous vehicles, with the goal of exploring human-autonomy teaming (HAT) concepts that enable more advanced m:N operations. Two key enablers have been identified to facilitate successful m:N operations: GCS software updates for multi-vehicle management and procedural updates for vehicle handoffs during off-nominal events. Additionally, specific modifications were identified across five key areas: technology and software, team structure, inter-team communication, contingency plans, and operator decision flows. Next steps in forming the LaRC m:N ConOps will include working with subject-matter experts to identify off-nominal scenarios, implementing the recommended GCS functionality for m:N operations, and performing integration testing of facility capabilities and new operational procedures. Although the future m:N ConOps will be tailored to the NASA LaRC remote operations facility and flight range, it is intended to be a transparent, accessible, and reality-based exemplar for external organizations seeking to create or evaluate their own m:N operational concepts.

m:N↗

Application of Human-Autonomy Teaming (HAT) Patterns to Reduce Crew Operations (RCO)

Unmanned aerial systems, advanced cockpits, and air traffic management are all seeing dramatic increases in automation. However, while automation may take on some tasks previously performed by humans, humans will still be required to remain in the system for the foreseeable future. The collaboration between humans and these increasingly autonomous systems will begin to resemble cooperation between teammates, rather than simple task allocation. It is critical to understand this human-autonomy teaming (HAT) to optimize these systems in the future. One methodology to understand HAT is by identifying recurring patterns of HAT that have similar characteristics and solutions. This paper applies a methodology for identifying HAT patterns to an advanced cockpit project.

design patterns↗