Results for “Autonomy” — Page 30

NASA NTRS2016

Workshop on Assurance for Autonomous Systems for Aviation

This report describes the workshop on Assurance for Autonomous Systems for Aviation that was held in January 2016 in conjunction with the SciTech 2016 conference held in San Diego, CA. The workshop explored issues related to assurance for autonomous systems and also the idea of trust in these systems. Specifically, we focused on discussing current practices for assurance of autonomy, identifying barriers specific to autonomy as related to assurance as well as operational scenarios demonstrating the need to address the barriers. Furthermore, attention was given to identifying verification techniques that may be applicable to autonomy, as well as discussing new research directions needed to address barriers, thereby involving potential shifts in current practices.

assurance↗

NASA NTRS2019

Artificial Intelligence: Powering Human Exploration of the Moon and Mars

Artificial Intelligence (AI) is a growing field of computa- tional science techniques designed to mimic functions per- formed by people. Advancements in autonomy will depend on a portfolio of AI technologies. Automated planning and scheduling is a venerable field of study in AI, and is needed for a variety of mission planning functions. Plan execution technology is less well studied, but important for auton- omy and robotics. Specialized forms of automated reason- ing and machine learning are key technologies to enable fault management. Over the past decade, the NASA Au- tonomous Systems and Operations (ASO) project has devel- oped and demonstrated numerous autonomy enabling tech- nologies employing AI techniques. Our work has employed AI in three distinct ways to enable autonomous mission op- erations capabilities. Crew Autonomy gives astronauts tools to assist in the performance of each of these mission oper-ations functions. Vehicle System Management uses AI tech- niques to turn the astronaut's spacecraft into a robot, allow- ing it to operate when astronauts are not present, or to reduce astronaut workload. AI technology also enables Autonomous Robots as crew assistants or proxies when the crew are not present. When these capabilities are used to enable astro- nauts to operate autonomously, they must be integrated with user interfaces, introducing numerous human factors con- siderations; when these capabilities are used to enable vehi- cle system management, they must be integrated with flight software, and run on embedded processors under the control of real-time operating systems.We first describe human spaceflight mission operations capabilities. The remainder of the paper will describe the ASO project, and the development and demonstration per- formed by ASO since 2011. We will describe the AI tech- niques behind each of these demonstrations, which include a variety of symbolic automated reasoning and machine learn- ing based approaches. Finally, we conclude with an assess- ment of future development needs for AI to enable NASA's future Exploration missions.

Mission Operations↗

NASA NTRSDate not supplied

LANDO: Developing Autonomous Surface Operations for Planetary Surfaces

The Lightweight Surface Manipulation System (LSMS) AutoNomy capabilities Development for surface Operations and construction (LANDO) project is an Early Career Initiative (ECI) selected for funding by the Space Technology Mission Directorate (STMD) beginning in fiscal year 2022. Over the two-year project duration, the LANDO project will deliver a general-purpose autonomy framework applicable to serial and tension-actuated manipulation agents, that has been validated using an existing prototype of the LSMS-L35 (35-kg wrist lift capacity on the lunar surface, sized for a Commercial Lunar Payload Services (CLPS) mission). Specific to the LANDO project, the autonomous LSMS-L35 will be used to demonstrate autonomous payload handling capabilities for Lunar and other planetary surfaces, directly addressing STMD capability gaps in autonomous surface construction (ASC) operations, advanced robotics and spacecraft autonomy technologies, and technologies supporting emerging space industries including the On-orbit Servicing, Assembly and Manufacturing (OSAM) National Initiative. In this paper, an overview of the LANDO ECI project is presented.

autonomy↗

NASA NTRSDate not supplied

LANDO: Developing autonomous surface operations for planetary surfaces

The Lightweight Surface Manipulation System (LSMS) AutoNomy capabilities Development for surface Operations and construction (LANDO) project is an Early Career Initiative (ECI) selected for funding by the Space Technology Mission Directorate (STMD) beginning in fiscal year 2022. Over the two-year project duration, the LANDO project will deliver a general-purpose autonomy framework applicable to serial and tension-actuated manipulation agents, that has been validated using an existing prototype of the LSMS-L35 (35-kg wrist lift capacity on the lunar surface, sized for a Commercial Lunar Payload Services (CLPS) mission). Specific to the LANDO project, the autonomous LSMS-L35 will be used to demonstrate autonomous payload handling capabilities for Lunar and other planetary surfaces, directly addressing STMD capability gaps in autonomous surface construction (ASC) operations, advanced robotics and spacecraft autonomy technologies, and technologies supporting emerging space industries including the On-orbit Servicing, Assembly and Manufacturing (OSAM) National Initiative. In this paper, an overview of the LANDO ECI project is presented.

autonomy↗

NASA NTRSDate not supplied

Autonomous In-space Construction, Maintenance, and Reconfiguration Using Programmable Meta-Material

NASA ARC's Coded Structures Laboratory (CSL) is developing autonomous construction, maintenance, and reconfiguration technologies to meet long-duration and deep space infrastructure needs, in accordance with long-term NASA goals of "in-space reliance" and "mass-less exploration." We seek to achieve these capabilities by utilizing a "programmable meta-material" approach that integrates emerging advances in materials (mechanical meta-materials), manufacturing (cooperative mobile robotics), and autonomy (multi-agent planning algorithms). Through the ARMADAS project, we have shown assembly of high-performance engineered cellular materials using multiple cooperating mobile robotic assemblers. In this paper, we describe how such a programmable meta-material architecture may shift the paradigm of how we design, build, manufacture, and operate future space infrastructure and assets. The core of a programmable meta-material architecture consists of 3 main technology sub-areas: the structure, the assembly agents, and the assembly algorithms. We co-design these systems to ensure an adaptable system that can create and reconfigure structures from a base set of building block components. From this core technology, we can branch out and expand the capability of the system through additional secondary component types and robotic agents to perform activities such as inspections, maintenance, repair, payload installation, or perform power and communications interconnect. As these technologies mature, future designers will be able to utilize the system to rapidly integrate and operate assets in space or on planetary surfaces from a set of well-tested part library, or create their own modules to integrate into the system. A core trait to the development of this system is the automation approach. Because of the modular and functional discrete (pixel-like) nature of the structural system, a diverse set of powerful algorithms for analysis, planning, and simulation can be adapted and leveraged to optimize construction, maintenance, and dynamic reorganization (as hardware with programmable form and function). With an ability to free the design space from launch vehicle constraints and fundamentally shift how a mission is designed and conducted, we discuss the influence of a programmable meta-material architecture on mission design, build, and operations. For the "design phase", we discuss project lifecycle effects, costs, time, and performance. For the "build phase", we discuss reusability, ISRU, manufacturing, material logistics, and scalability. And for "operations", we discuss autonomy, maintenance and upgrades, reliability, and reconfiguration. Autonomy and modularity are the primary enabling traits of this system. Engineering systems that utilize a modular and reconfiguration building block approach such as digital communication and computation systems, currently lead all other areas of technology in size and complexity scalability. NASA is extending the benefits and flexibility of digital systems to hardware systems, to optimize materials lifecycle management and expand our space exploration mission capabilities.

in space assembly↗

NASA NTRSDate not supplied

Challenges and Opportunities in Autonomous Flight

This talk discusses the challenges and opportunities for autonomy in aviation. We cover the autonomy drivers, what we consider fundamental building blocks for autonomous flight and success of assigned mission. We provide some examples from our work of integrating different algorithms to deal with contingencies that arise in flight. We also discuss a potential need to assess progress to autonomy across various aviation niches and evolving sectors and propose a framework to do so.

autonomy↗

NASA NTRSDate not supplied

Benchmark Problem for Autonomous Urban Air Mobility

This paper introduces a Community Benchmark Problem (CBP) for Intelligent Contingency Management (ICM) for Urban Air Mobility (UAM) aircraft. The CBP aims to provide a common framework for measuring and comparing the progress of autonomy solutions for UAM aircraft in handling emergency situations. The paper proposes a methodology for defining and quantifying five measures of complexity that capture the challenges and requirements of ICM for UAM: Mission, Environmental, Autonomy, Decision-Making, and Mission Fault. In addition, it proposes a methodology for defining and quantifying mission risk acceptability with the same goals: Contingency Management, Mission Success, Operational, Mission Redefinition, and Environmental. We describe how to use these measures to track progress of the development of ICM capability, as well as to create scenarios and evaluate the performance of different autonomy solutions.

autonomy↗

NASA NTRSDate not supplied

Community Benchmark Problem for Intelligent Contingency Management

This paper introduces a Community Benchmark Problem (CBP) for Intelligent Contingency Management (ICM) for Urban Air Mobility (UAM) aircraft. The CBP aims to provide a common framework for measuring and comparing the progress of autonomy solutions for UAM aircraft in handling emergency situations. The paper proposes a methodology for defining and quantifying five measures of complexity that capture the challenges and requirements of ICM for UAM: Mission, Environmental, Autonomy, Decision-Making, and Mission Fault. In addition, it proposes a methodology for defining and quantifying mission risk acceptability with the same goals: Contingency Management, Mission Success, Operational, Mission Redefinition, and Environmental. We describe how to use these measures to track progress of the development of ICM capability, as well as to create scenarios and evaluate the performance of different autonomy solutions.

autonomy↗

NASA NTRSDate not supplied

Autonomous Flight and Its Challenges

Aviation is undergoing a revolution and a paradigm change. New technologies are moving aviation towards on-demand transportation. To fully realize the promise of “anyone, anytime, anywhere” transportation, autonomy must play a key role. Our research team is focused on the intersection of new vehicle eVTOL configurations, popularly known as “air taxis”, and autonomous flight in complex urban environment. It has been widely recognized that dealing with contingencies, especially in safe, scalable and flexible way, is the most difficult challenge for autonomy. The presentation is intended to outline what we consider fundamental challenges and describe our current approaches. Moreover, we are working on establishing wide ranging collaborations to address these fundamental autonomy challenges in a relevant environment with real-world assumptions and constraints. Hence, we would like to take this opportunity to discuss open challenge problems with this research community.

autonomy↗

NASA NTRS1982

Space power subsystem automation technology

The technology issues involved in power subsystem automation and the reasonable objectives to be sought in such a program were discussed. The complexities, uncertainties, and alternatives of power subsystem automation, along with the advantages from both an economic and a technological perspective were considered. Whereas most spacecraft power subsystems now use certain automated functions, the idea of complete autonomy for long periods of time is almost inconceivable. Thus, it seems prudent that the technology program for power subsystem automation be based upon a growth scenario which should provide a structured framework of deliberate steps to enable the evolution of space power subsystems from the current practice of limited autonomy to a greater use of automation with each step being justified on a cost/benefit basis. Each accomplishment should move toward the objectives of decreased requirement for ground control, increased system reliability through onboard management, and ultimately lower energy cost through longer life systems that require fewer resources to operate and maintain. This approach seems well-suited to the evolution of more sophisticated algorithms and eventually perhaps even the use of some sort of artificial intelligence. Multi-hundred kilowatt systems of the future will probably require an advanced level of autonomy if they are to be affordable and manageable.

Graves, J. R.↗

NASA NTRS1984

Autonomous spacecraft design methodology

A methodology for autonomous spacecraft design blends autonomy requirements with traditional mission requirements and assesses the impact of autonomy upon the total system resources available to support fault-tolerance and automation. A baseline functional design can be examined for autonomy implementation impacts, and the costs, risk, and benefits of various options can be assessed. The result of the process is a baseline design that includes autonomous control functions.

Divita, E. L.↗

NASA NTRS1987

Autonomous intelligent systems

NASA's Office of Aeronautics and Space Technology (OAST) has instituted a 'Systems Autonomy' technology development program aimed at the creation of increasingly sophisticated AI systems. Expert system production will in due course be followed by fully autonomous AI systems capable of the complex mission objectives of the Space Station, as well as of lunar and Martian exploration. AI systems must demonstrate the degree of their autonomy in a real-time operational environment, and then undergo mating to robotics technologies. OAST's Systems Autonomy Program and Robotics Program are discussed with a view to anticipated difficulties in their integration.

Lum, H.↗

NASA NTRS1987

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.↗

NASA NTRS1992

Lazy checkpoint coordination for bounding rollback propagation

Independent checkpointing allows maximum process autonomy but suffers from potential domino effects. Coordinated checkpointing eliminates the domino effect by sacrificing a certain degree of process autonomy. In this paper, we propose the technique of lazy checkpoint coordination which preserves process autonomy while employing communication-induced checkpoint coordination for bounding rollback propagation. The introduction of the notion of laziness allows a flexible trade-off between the cost for checkpoint coordination and the average rollback distance. Worst-case overhead analysis provides a means for estimating the extra checkpoint overhead. Communication trace-driven simulation for several parallel programs is used to evaluate the benefits of the proposed scheme for real applications.

Wang, Yi-Min↗

NASA NTRS1993

Lazy checkpoint coordination for bounding rollback propagation

Independent checkpointing allows maximum process autonomy but suffers from potential domino effects. Coordinated checkpointing eliminates the domino effect by sacrificing a certain degree of process autonomy. In this paper, we propose the technique of lazy checkpoint coordination which preserves process autonomy while employing communication-induced checkpoint coordination for bounding rollback propagation. The introduction of the notion of laziness allows a flexible trade-off between the cost for checkpoint coordination and the average rollback distance. Worst-case overhead analysis provides a means for estimating the extra checkpoint overhead. Communication trace-driven simulation for several parallel programs is used to evaluate the benefits of the proposed scheme for real applications.

Wang, Yi-Min↗

NASA NTRS1994

Distributed intelligence for ground/space systems

DI is short for Distributed Intelligence for Ground/Space Systems and the DI Study is one in a series of ESA projects concerned with the development of new concepts and architectures for future autonomous spacecraft systems. The kick-off of DI was in January 1994 and the planned duration is three years. The background of DI is the desire to design future ground/space systems with a higher degree of autonomy than seen in today's missions. The aim of introducing autonomy in spacecraft systems is to: (1) lift the role of the spacecraft operators from routine work and basic troubleshooting to supervision; (2) ease access to and increase availability of spacecraft resources; (3) carry out basic mission planning for users; (4) enable missions which have not yet been feasible due to eg. propagation delays, insufficient ground station coverage etc.; and (5) possibly reduce mission cost. The study serves to identify the feasibility of using state-of-the-art technologies in the area of planning, scheduling, fault detection using model-based diagnosis and knowledge processing to obtain a higher level of autonomy in ground/space systems.

Aarup, Mads↗

NASA NTRS1995

Limits to ground control in autonomous spacecraft

In this paper the autonomy concept used by ESA and NASA is critically evaluated. Moreover, a more proper ground control/spacecraft organizational structure is proposed on the basis of a new, more elaborated concept of autonomy. In an extended theoretical discussion its definitional properties and functionalities are established. The rather basic property of adaptivity leads to the categorization of behaviour into the modes of satisfaction and avoidance behaviour. However, the autonomy property with the most profound consequences is goal-robustness. The mechanism that implements goal-robustness tests newly generated goals and externally received goals on consistency with high-level goals. If goals appear not to be good instantiations or more acceptable replacements of existing goals, they are rejected. This means that ground control has to cooperate with the spacecraft instead of (intermittently) commanding it.

Wan, Alfred D. M.↗

NASA NTRS1998

Mission Operations with an Autonomous Agent

The Remote Agent (RA) is an Artificial Intelligence (AI) system which automates some of the tasks normally reserved for human mission operators and performs these tasks autonomously on-board the spacecraft. These tasks include activity generation, sequencing, spacecraft analysis, and failure recovery. The RA will be demonstrated as a flight experiment on Deep Space One (DSI), the first deep space mission of the NASA's New Millennium Program (NMP). As we moved from prototyping into actual flight code development and teamed with ground operators, we made several major extensions to the RA architecture to address the broader operational context in which PA would be used. These extensions support ground operators and the RA sharing a long-range mission profile with facilities for asynchronous ground updates; support ground operators monitoring and commanding the spacecraft at multiple levels of detail simultaneously; and enable ground operators to provide additional knowledge to the RA, such as parameter updates, model updates, and diagnostic information, without interfering with the activities of the RA or leaving the system in an inconsistent state. The resulting architecture supports incremental autonomy, in which a basic agent can be delivered early and then used in an increasingly autonomous manner over the lifetime of the mission. It also supports variable autonomy, as it enables ground operators to benefit from autonomy when L'@ey want it, but does not inhibit them from obtaining a detailed understanding and exercising tighter control when necessary. These issues are critical to the successful development and operation of autonomous spacecraft.

Pell, Barney↗