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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 487 records · Page 27

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NASA NTRSDate not supplied

An Experimental System for Strategic Flight Path Management in Advanced Air Mobility

In the concept envisioned for Urban Air Mobility (UAM) operations, fleets of electric vertical takeoff and landing (eVTOL) vehicles would operate between vertiports distributed within a densely populated area. These operations would be largely independent from the existing air traffic control system and would place the responsibility for flight planning and aircraft separation on fleet operators. The fourth major level on the UAM Maturity Level scale, UML-4, relies on “collaborative and responsible” automation to enable operations in non-visual conditions with medium traffic density (hundreds of aircraft in one metropolitan region) and medium complexity. This level of service places many requirements on automation systems to assist the operators of these aircraft. NASA has developed the Autonomous Operations Planner (AOP), a reference prototype Flight Path Management automation system, and has modified AOP to support research of anticipated UML-4 operations. AOP creates a four-dimensional flight plan conforming to the constraints of these operations, evaluates and modifies the flight plan during flight as conditions and constraints evolve, and coordinates the flight plan with other airspace users and with service providers. This version of AOP has been integrated into the Sikorsky Autonomy Research Aircraft and used in a flight test activity. In this paper we discuss anticipated characteristics of UAM operations, modifications that were made to AOP to adapt to that environment or to support the flight test, and observations of software and aircraft performance during the flight test. The aircraft achieved four-dimensional conformance with the flight plan and AOP provided adequate planning in almost all cases. We discuss improvements that could be made to AOP to address deficiencies that were observed.

Autonomous Operations Planner↗

NASA NTRS1989

An intelligent, free-flying robot

The ground based demonstration of the extensive extravehicular activity (EVA) Retriever, a voice-supervised, intelligent, free flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The major objective of the EVA Retriever Project is to design, develop, and evaluate an integrated robotic hardware and on-board software system which autonomously: (1) performs system activation and check-out; (2) searches for and acquires the target; (3) plans and executes a rendezvous while continuously tracking the target; (4) avoids stationary and moving obstacles; (5) reaches for and grapples the target; (6) returns to transfer the object; and (7) returns to base.

Reuter, G. J.↗

NASA NTRS1988

An intelligent, free-flying robot

The ground-based demonstration of EVA Retriever, a voice-supervised, intelligent, free-flying robot, is designed to evaluate the capability to retrieve objects (astronauts, equipment, and tools) which have accidentally separated from the Space Station. The major objective of the EVA Retriever Project is to design, develop, and evaluate an integrated robotic hardware and on-board software system which autonomously: (1) performs system activation and check-out, (2) searches for and acquires the target, (3) plans and executes a rendezvous while continuously tracking the target, (4) avoids stationary and moving obstacles, (5) reaches for and grapples the target, (6) returns to transfer the object, and (7) returns to base.

Reuter, G. J.↗

NASA NTRS1989

Planetary Rover local navigation and hazard avoidance

A Planetary Rover will have to be able to navigate through its local environment autonomously, due to communication delays. This implies that the vehicle must be able to sense its environment, plan a course through that environment, and react appropriately to unexpected situations as they appear. All this must be done while guiding the vehicle toward the goals that have been given to it from its operators on the earth. This paper describes research at the Jet Propulsion Laboratory which concentrates on the sensing, perception, planning and execution monitoring that must be carried out by the rover to ensure that a safe and efficient path is found by the rover, and that that path is performed correctly.

Miller, David P.↗

NASA NTRS1990

Fault analysis of multichannel spacecraft power systems

The NASA Marshall Space Flight Center proposes to implement computer-controlled fault injection into an electrical power system breadboard to study the reactions of the various control elements of this breadboard. Elements under study include the remote power controllers, the algorithms in the control computers, and the artificially intelligent control programs resident in this breadboard. To this end, a study of electrical power system faults is being performed to yield a list of the most common power system faults. The results of this study will be applied to a multichannel high-voltage DC spacecraft power system called the large autonomous spacecraft electrical power system (LASEPS) breadboard. The results of the power system fault study and the planned implementation of these faults into the LASEPS breadboard are described.

Dugal-Whitehead, Norma R.↗

NASA NTRS2002

Autoreturn Function for a Remotely Piloted Vehicle

An algorithm to maneuver an air vehicle to intercept and follow a pre-planned path while remaining within an arbitrary, closed boundary is outlined. The immediate application is for an autonomous lost-link return-to-runway function for a remotely piloted vehicle being developed by NASA, but other applications are hypothesized. Results of implementation in a flight simulator are given.

McMinn, J. D.↗

NASA NTRS2016

Self-Aware Vehicles: Mission and Performance Adaptation to System Health

Advances in sensing (miniaturization, distributed sensor networks) combined with improvements in computational power leading to significant gains in perception, real-time decision making/reasoning and dynamic planning under uncertainty as well as big data predictive analysis have set the stage for realization of autonomous system capability. These advances open the design and operating space for self-aware vehicles that are able to assess their own capabilities and adjust their behavior to either complete the assigned mission or to modify the mission to reflect their current capabilities. This paper discusses the self-aware vehicle concept and associated technologies necessary for full exploitation of the concept. A self-aware aircraft, spacecraft or system is one that is aware of its internal state, has situational awareness of its environment, can assess its capabilities currently and project them into the future, understands its mission objectives, and can make decisions under uncertainty regarding its ability to achieve its mission objectives.

Gregory, Irene M.↗

NASA NTRS2023

Progressively Enabling Earth Independent Medical Operations (EIMO)

This panel presents the findings from a series of Technical Interchange Meetings (TIMs) hosted by the Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program. The topics for the TIMs were derived from a 2-day conference of senior leaders and subject matters experts that collectively outlined a multi-faceted strategy designed to optimize crew health and performance through an increasingly autonomous medical approach. The first abstract in this panel outlines the scope of issues related to data collection, usage, transmission and computing capacity to facilitate EIMO. The second presentation provides an overview of the challenges in developing curricula and advanced training tools to baseline knowledge, skills and abilities (KSA), verify clinical competency and assure retention during prolonged durations inherent in exploration-class missions. An overview of the complicated medical supply and resource chain necessary to facilitate EIMO is provided in the third presentation of this panel. The final presentation in this EIMO panel surveys the breadth and depth of demands on cognitive load expected to be experienced by crew on an exploration mission and proposes strategies to mitigate the prospect of cognitive overload through methods to shift task load from the crew to multi-modal artificial intelligence based medical support systems. Taken together, these presentations summarize the challenges to be expected and potential solution spaces to be explored and developed to progressively enable increasing autonomous medical operations to support crewed missions beyond low earth orbit. Through EIMO focused pre-mission planning, integrated data architecture design, innovative training development and AI-assisted task load management, the gradual transition of medical care and decision making from terrestrial to space-based assets enabling support of astronaut health and performance and reducing overall mission risk is achievable.

Jay Lemery↗

NASA NTRSDate not supplied

Progressively Enabling Earth Independent Medical Operations (EIMO)

John Lemery↗

NASA NTRS2005

Path Planning Algorithms for the Adaptive Sensor Fleet

The Adaptive Sensor Fleet (ASF) is a general purpose fleet management and planning system being developed by NASA in coordination with NOAA. The current mission of ASF is to provide the capability for autonomous cooperative survey and sampling of dynamic oceanographic phenomena such as current systems and algae blooms. Each ASF vessel is a software model that represents a real world platform that carries a variety of sensors. The OASIS platform will provide the first physical vessel, outfitted with the systems and payloads necessary to execute the oceanographic observations described in this paper. The ASF architecture is being designed for extensibility to accommodate heterogenous fleet elements, and is not limited to using the OASIS platform to acquire data. This paper describes the path planning algorithms developed for the acquisition phase of a typical ASF task. Given a polygonal target region to be surveyed, the region is subdivided according to the number of vessels in the fleet. The subdivision algorithm seeks a solution in which all subregions have equal area and minimum mean radius. Once the subregions are defined, a dynamic programming method is used to find a minimum-time path for each vessel from its initial position to its assigned region. This path plan includes the effects of water currents as well as avoidance of known obstacles. A fleet-level planning algorithm then shuffles the individual vessel assignments to find the overall solution which puts all vessels in their assigned regions in the minimum time. This shuffle algorithm may be described as a process of elimination on the sorted list of permutations of a cost matrix. All these path planning algorithms are facilitated by discretizing the region of interest onto a hexagonal tiling.

Stoneking, Eric↗

NASA NTRSDate not supplied

Moon to Mars Planetary Autonomous Construction Technology (MMPACT) Lunar Surface Construction Activity at NASA Marshall Space Flight Center

Introduction: The goal of the Moon to Mars Planetary Autonomous Construction Technology (MMPACT) Project at NASA Marshall Space Flight Center (MSFC) is to develop, deliver, and demonstrate on-demand capabilities to protect astronauts and create infrastructure elements on the lunar surface via construction of landing pads, habitats, shelters, roadways, berms, and blast shields using lunar regolith-based materials. MSFC has strong collaborations with industry, academia, and other NASA Centers to accomplish this goal. The MMPACT project consists of three elements. The first focuses on the development of an autonomous construction system. The second focuses on construction feedstock materials development. The third element focuses on the development of a microwave sintering construction capability. The team plans to demonstrate construction on a small Commercial Lunar Payload Services (CLPS) lander in the 2025 timeframe, with a future goal of constructing a subscale landing pad in 2028-2029.The MMPACT project is funded through the Lunar Surface Innovation Initiative, which is part of the Space Technology Mission Directorate. Technology Development: The MMPACT team will evaluate multiple autonomous construction and microwave construction technologies, materials, and construction element forms. Selected technologies will be matured; processes and operations will be defined for the two flight missions. Evaluations of materials, as well as the technology itself, will be demonstrated in simulated lunar environments as part of the technology maturation process. The team is keenly aware of the properties of the lunar environment. Its temperature swings, negligible exosphere, and unprepared site foundations factor into the materials for both construction and hardware, the concept of operations, and the technology’s interdependencies. Materials: The team is looking at materials that can be produced from in-situ resources in an effort to make lunar construction cost-effective. The particular focus of the materials team is cementitious materials, metals, and sintered and melted regolith. These materials will be studied for tensile, compressive, and flexural strength. They will also be tested for their ability to handle thermal swings and vacuum. They will be fully characterized using various microscopy techniques to examine micro-structures, chemistry, and crystal formation. Interdependencies: There are many interdependencies that MMPACT has already identified. These include: •Excavation interface •Regolith feedstock beneficiation •Regolith feedstock storage and provision •Requirements for structures •Site-to-site mobility systems •Availability of lunar simulant •Lander off-loading capabilities •Navigation systems •Power •Regolith composition and mineralogy •Lander specifications •Communication protocols Technology developments in these additional areas would be beneficial to MMPACT.

Moon to Mars Planetary Autonomous Construction Tec↗

NASA NTRS2018

Planning and Execution for Front Delineation and Tracking with Multiple Underwater Vehicles

This work describes a planning architecture for a heterogeneous ﬂeet of marine assets as well as a method for detecting and tracking ocean fronts using multiple autonomous underwater vehicles. Multiple vehicles — equally-spaced along the expected frontal boundary — complete near parallel transects orthogonal to the front. Lateral gradients are used to determine the location of the front crossing from each individual vehicle transect by detecting a change in the observed water property. Adaptive control of the vehicles ensure they remain perpendicular to the estimated frontal boundary as it evolves over time. This method was demonstrated in several experiment periods totaling weeks, in and around Monterey Bay, California in May and June of 2017. We discuss the challenges associated with the implementation of the planning system. We show the capability of this method for repeated sampling across a dynamic two-dimensional ocean front using a ﬂeet of three types of platforms: short-range Iver AUVs, Tethys-Class Long-Range AUVs, and Seagliders. This method extends to tracking gradients of diﬀerent properties using a variety of vehicles.

Chavez, Francisco P.↗

NASA NTRS1991

Autonomous Mars ascent and orbit rendezvous for earth return missions

The details of tha assessment of autonomous Mars ascent and orbit rendezvous for earth return missions are presented. Analyses addressing navigation system assessments, trajectory planning, targeting approaches, flight control guidance strategies, and performance sensitivities are included. Tradeoffs in the analysis and design process are discussed.

Edwards, H. C.↗

NASA NTRS2005

Enabling Interoperable Space Robots With the Joint Technical Architecture for Robotic Systems (JTARS)

Robots that operate independently of one another will not be adequate to accomplish the future exploration tasks of long-distance autonomous navigation, habitat construction, resource discovery, and material handling. Such activities will require that systems widely share information, plan and divide complex tasks, share common resources, and physically cooperate to manipulate objects. Recognizing the need for interoperable robots to accomplish the new exploration initiative, NASA s Office of Exploration Systems Research & Technology recently funded the development of the Joint Technical Architecture for Robotic Systems (JTARS). JTARS charter is to identify the interface standards necessary to achieve interoperability among space robots. A JTARS working group (JTARS-WG) has been established comprising recognized leaders in the field of space robotics including representatives from seven NASA centers along with academia and private industry. The working group s early accomplishments include addressing key issues required for interoperability, defining which systems are within the project s scope, and framing the JTARS manuals around classes of robotic systems.

Bradley, Arthur↗

NASA NTRS1997

An Autonomous Spacecraft Agent Prototype

This paper describes the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. This architecture integrates traditional real-time monitoring and control with constraint-based planning and scheduling, robust multi-threaded execution, and model-based diagnosis and reconfiguration.

New Millennium Remote Agent↗

NASA NTRS2001

The Mars exploration rover: an in situ science mission to Mars

In this paper the concept for a mobile vehicle system which performs an in situ science mission to Mars is described. This rover mission with its requirements for driving, positioning at science selected targets, and remote and in situ measurement will utilize the technologies for hazard avoidance and autonomous navigation supported by ground operation tools which use rover-based imagery for position estimation and motion planning.

Mars rover athena instruments hazard detection haz↗

NASA NTRS2011

Autonomous Aerobraking: A Design, Development, and Feasibility Study

Aerobraking has been used four times to decrease the apoapsis of a spacecraft in a captured orbit around a planetary body with a significant atmosphere utilizing atmospheric drag to decelerate the spacecraft. While aerobraking requires minimum fuel, the long time required for aerobraking requires both a large operations staff, and large Deep Space Network resources. A study to automate aerobraking has been sponsored by the NASA Engineering and Safety Center to determine initial feasibility of equipping a spacecraft with the onboard capability for autonomous aerobraking, thus saving millions of dollars incurred by a large aerobraking operations workforce and continuous DSN coverage. This paper describes the need for autonomous aerobraking, the development of the Autonomous Aerobraking Development Software that includes an ephemeris estimator, an atmospheric density estimator, and maneuver calculation, and the plan forward for continuation of this study.

Prince, Jill L. H.↗

NASA NTRS2022

The Mars 2020 Ground Data System Architecture

The Mars 2020 Mission’s primary objective is to collect 20 geographically unique samples during its prime mission of one and a quarter Martian years, or just over 2 Earth years. Mission planners determined the project needed to develop a system that would enable the operations team to analyze engineering and science data, make science decisions, select viable rover targets at a millimeter resolution and validate an uplink bundle for a car sized rover with more complex science instruments than any previous Mars surface mission. All this had to be done within a five hour time frame. Doing this with a small team would be a challenge, but this had to be accomplished by a large team of engineers and scientists located across North America and Europe. Achieving this level of operational efficiency was unheard of in the prime mission. In addition, the mission had another set of requirements that had nothing to do with surface operations; the Mars 2020 Ground Data System (GDS) was also expected to comply with a new set of security requirements to keep up with the ever changing cybersecurity landscape. The Mars 2020 Ground Data System (GDS) is a re-architected version of the Mars Science Laboratory GDS. The primary goal was to integrate the lessons learned from previous Mars surface missions, accommodate a set of new requirements and capabilities required to ensure mission success, and comply with a new set of cybersecurity controls. The new architecture includes several unique qualities including a data lake, language-agnostic system-wide event-based operations, containerization, automated deployment, network segmentation, infrastructure-as-code, API-driven interfaces, and the first Mars surface GDS to operate primarily in the cloud. The new architecture enabled greater access to the system’s data, tighter integration with the operations team, and a higher level of traceability. The availability of the data also enabled a new set of capabilities previously not possible on surface missions. These new capabilities include an autonomous data to information, pipeline for downlink analysis, horizontal scaling of science data processing capabilities, autonomous round trip data tracking of science and engineering data, integration of flight system state into the tactical planning cycle, high fidelity targeting utilizing kinematic data, and hierarchical image and 3d meshes data representations. This paper will introduce the requirements for the Mars 2020 Mission, the heritage architecture, and the rationale for the changes to achieve the new architecture. The paper will continue to describe the fundamental changes made to the GDS architecture, how these changes enabled a more tightly integrated GDS, and the new capabilities that were enabled by the new architecture. The paper will conclude with the lessons learned from the process of rearchitecting a heritage GDS system and from the first 200 days of operations supporting over 800 users from around the world.

Lopez-Roig, Reynaldo↗