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  • 1
    Publication Date: 2013-08-29
    Description: The need for spacecraft mobile robots continues to grow. These robots offer the potential to increase the capability, productivity, and duration of space missions while decreasing mission risk and cost. Spacecraft Mobile Robots (SMRs) can serve a number of functions inside and outside of spacecraft from simpler tasks, such as performing visual diagnostics and crew support, to more complex tasks, such as performing maintenance and in-situ construction. One of the predominant challenges to deploying SMRs is to reduce the need for direct operator interaction. Teleoperation is often not practical due to the communication latencies incurred because of the distances involved and in many cases a crewmember would directly perform a task rather than teleoperate a robot to do it. By integrating a mixed-initiative constraint-based planner with an executive that supports adjustably autonomous control, we intend to demonstrate the feasibility of autonomous SMRs by deploying one inside the International Space Station (ISS) and demonstrate in simulation one that operates outside of the ISS. This paper discusses the progress made at NASA towards this end, the challenges ahead, and concludes with an invitation to the research community to participate.
    Keywords: Cybernetics, Artificial Intelligence and Robotics
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  • 2
    Publication Date: 2018-06-06
    Description: The advent of spacecraft mobile robots-free-flyng sensor platforms and communications devices intended to accompany astronauts or remotely operate on space missions both inside and outside of a spacecraft-has demanded the development of a simple and effective navigation schema. One such system under exploration involves the use of a laser-camera arrangement to predict relative positioning of the mobile robot. By projecting laser beams from the robot, a 3D reference frame can be introduced. Thus, as the robot shifts in position, the position reference frame produced by the laser images is correspondingly altered. Using normalization and camera registration techniques presented in this paper, the relative translation and rotation of the robot in 3D are determined from these reference frame transformations.
    Keywords: Spacecraft Design, Testing and Performance
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  • 3
    Publication Date: 2018-06-06
    Description: This paper presents an overview of an ongoing research and development effort at the NASA Ames Research Center to create an autonomous control system for an internal spacecraft autonomous mobile monitor. It primary functions are to provide crew support and perform intra- vehicular sensing activities by autonomously navigating onboard the International Space Station. We describe the mission roles and high-level functional requirements for an autonomous mobile monitor. The mobile monitor prototypes, of which two are operational and one is actively being designed, physical test facilities used to perform ground testing, including a 3D micro-gravity test facility, and simulators are briefly described. We provide an overview of the autonomy framework and describe each of its components, including those used for automated planning, goal-oriented task execution, diagnosis, and fault recovery. A sample mission test scenario is also described.
    Keywords: Spacecraft Instrumentation and Astrionics
    Type: 7th International Symposium on Artificial Intelligence, Robotics and Automation in Space; Nara; Japan
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  • 4
    Publication Date: 2018-06-06
    Description: We present an multi-agent model-based autonomy architecture with monitoring, planning, diagnosis, and execution elements. We discuss an internal spacecraft free-flying robot prototype controlled by an implementation of this architecture and a ground test facility used for development. In addition, we discuss a simplified environment control life support system for the spacecraft domain also controlled by an implementation of this architecture. We discuss adjustable autonomy and how it applies to this architecture. We describe an interface that provides the user situation awareness of both autonomous systems and enables the user to dynamically edit the plans prior to and during execution as well as control these agents at various levels of autonomy. This interface also permits the agents to query the user or request the user to perform tasks to help achieve the commanded goals. We conclude by describing a scenario where these two agents and a human interact to cooperatively detect, diagnose and recover from a simulated spacecraft fault.
    Keywords: Cybernetics, Artificial Intelligence and Robotics
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  • 5
    Publication Date: 2019-07-13
    Description: Remote Agent (RA) is a model-based, reusable artificial intelligence (At) software system that enables goal-based spacecraft commanding and robust fault recovery. RA was flight validated during an experiment on board of DS1 between May 17th and May 21th, 1999.
    Keywords: Cybernetics, Artificial Intelligence and Robotics
    Type: Technology Validation; Feb 08, 2000 - Feb 09, 2000; Pasadena, CA; United States
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  • 6
    Publication Date: 2019-07-13
    Description: Writing autonomous software is complex, requiring the coordination of functionally and technologically diverse software modules. System and mission engineers must rely on specialists familiar with the different software modules to translate requirements into application software. Also, each module often encodes the same requirement in different forms. The results are high costs and reduced reliability due to the difficulty of tracking discrepancies in these encodings. In this paper we describe a unified approach to planning and execution that we believe provides a unified representational and computational framework for an autonomous agent. We identify the four main components whose interplay provides the basis for the agent's autonomous behavior: the domain model, the plan database, the plan running module, and the planner modules. This representational and problem solving approach can be applied at all levels of the architecture of a complex agent, such as Remote Agent. In the rest of the paper we briefly describe the Remote Agent architecture. The new agent architecture proposed here aims at achieving the full Remote Agent functionality. We then give the fundamental ideas behind the new agent architecture and point out some implication of the structure of the architecture, mainly in the area of reactivity and interaction between reactive and deliberative decision making. We conclude with related work and current status.
    Keywords: Cybernetics, Artificial Intelligence and Robotics
    Type: Intelligent Agent Systems; Jul 01, 2000; Venice; Italy
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  • 7
    Publication Date: 2019-07-18
    Description: This paper describes the integration of the Remote Agent (RA), a spacecraft autonomy system which is scheduled to control the Deep Space 1 spacecraft during a flight experiment in 1999. The RA is a reusable, model-based autonomy system that is quite different from software typically used to control an aerospace system. We describe the integration challenges we faced, how we addressed them, and the lessons learned. We focus on those aspects of integrating the RA that were either easier or more difficult than integrating a more traditional large software application because the RA is a model-based autonomous system. A number of characteristics of the RA made integration process easier. One example is the model-based nature of RA. Since the RA is model-based, most of its behavior is not hard coded into procedural program code. Instead, engineers specify high level models of the spacecraft's components from which the Remote Agent automatically derives correct system-wide behavior on the fly. This high level, modular, and declarative software description allowed some interfaces between RA components and between RA and the flight software to be automatically generated and tested for completeness against the Remote Agent's models. In addition, the Remote Agent's model-based diagnosis system automatically diagnoses when the RA models are not consistent with the behavior of the spacecraft. In flight, this feature is used to diagnose failures in the spacecraft hardware. During integration, it proved valuable in finding problems in the spacecraft simulator or flight software. In addition, when modifications are made to the spacecraft hardware or flight software, the RA models are easily changed because they only capture a description of the spacecraft. one does not have to maintain procedural code that implements the correct behavior for every expected situation. On the other hand, several features of the RA made it more difficult to integrate than typical flight software. For example, the definition of correct behavior is more difficult to specify for a system that is expected to reason about and flexibly react to its environment than for a traditional flight software system. Consequently, whenever a change is made to the RA it is more time consuming to determine if the resulting behavior is correct. We conclude the paper with a discussion of future work on the Remote Agent as well as recommendations to ease integration of similar autonomy projects.
    Keywords: Cybernetics, Artificial Intelligence and Robotics
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  • 8
    Publication Date: 2019-11-28
    Description: Throughout the world, especially in dense urban environments, the quality of life is being negatively impacted by ever growing commute time. Travel, beyond commuting, is increasingly driven by door-to-door challenges ? not just gate-to-gate considerations. Air Mobility may be an approach to address these challenges, as it can effectively convert our 2D mobility system to a 3D mobility system, vastly increasing mobility options.
    Keywords: Aeronautics (General)
    Type: ARC-E-DAA-TN75871 , Air Mobility presentation to AirXOS; Nov 25, 2019; Moffett Field, CA; United States
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  • 9
    Publication Date: 2019-11-13
    Description: This presentation covers the value proposition and challenges of permanently extending life beyond Earth. It proposes that this can be most expeditiously accomplished by starting with a population of small Closed Ecological Systems (CES)s, each with several specie populations that enable each CES to persist indefinitely without the need to add resources, remove wastes, or require human intervention. Each CES is instrumented and controlled so that it can be remotely maintained, experiments performed, and data collected. Data from the entire population of CESs are managed in a cloud server database for analyses on how to improve the performance of each CES as well as formulate new CESs. The presentation discusses a modular, artificial-spacecraft prototype that could be used to fly CES modules in space under various gravity and radiation conditions to study changes in the CESs relative to their counterparts that remain on Earth as the control group. The presentation concludes with the next, low-cost steps for rapidly executing the approach described.
    Keywords: Man/System Technology and Life Support
    Type: ARC-E-DAA-TN61215
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  • 10
    Publication Date: 2019-11-13
    Description: An adjustably-autonomous intelligent systems approach for developing Closed Ecosystems (CESs) is presented, which includes a design concept and preliminary design details for the Controlled Closed-Ecosystem Development System (CCEDS) and the Orbiting Modular Artificial-Gravity Spacecraft (OMAGS). The paper is divided into three sections: CESs, the CCEDS Design Concept, and Orbiting Fractional-Gravity Closed Ecosystems OMAGS design concept. The first section briefly describes Closed EcoSystems (CESs), complex adaptive systems, biomes, microbial microbiomes, and their relevance for the study of astrobiology. This section also discusses initial efforts in the development of Closed Environment Life Support Systems (CELSSs) for sustainable communities in space and on Earth. This section concludes with a discussion of the bioregenerative life support system challenge of and the corresponding consequences due to the inverse relationship of the very small human biomass/non-human biomass ratio overall on the Earth with respect to the extremely large human biomass/non-human-biomass ratio found in cities and the International Space Station. The second section describes the CCEDS design concept, which consists of a population of controlled colonies of CES Modules (CESMs), each an integrated CES, continually generating data for an intelligent system that operates the CESs and their CESMs. A variety of CESM types and their use are briefly described. The CCEDS intelligent system uses an evolutionary computation algorithm described in this section to develop and optimize these CESs to increase their viability duration and the size of the animals they support with the ultimate goal to support populations of humans, both on Earth and in space. The CCEDS architecture, its five control subsystems, and its five evolutionary computation levels are also discussed. The section concludes with a discussion of several CCEDS design strategies. The third section summarizes the OMAGS design concept for a spacecraft with a payload consisting of CESs in an orbiting spacecraft centrifuge that operates for at least 5 years. The spacecraft concept is described including its 150cm-radius centrifuge with a 2 ton & 3,000 liter bioscience payload capacity for 24 CESMs. The centrifuge design has four physical levels for its CESMs, each level subject to a different fractional gravity level. This section presents the spacecraft benefits of being designed and operated such that the spacecraft and payload centrifuge wheel counter-rotate resulting in net zero angular momentum and zero gyroscopic forces. Artificial-gravity generation by centripetal acceleration is also discussed. This section concludes by showing the external specifications of the CESMs and their layout in the centrifuge, followed by discussing the multi-payload module rationale. In tandem, the CCEDS and OMAGS systems can be used to foster gravitational ecosystem research for developing sustainable communities in space and on Earth.
    Keywords: Man/System Technology and Life Support; Cybernetics, Artificial Intelligence and Robotics
    Type: NASA/TM-2018?56787 , ARC-E-DAA-TN62686
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