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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 163 records · Page 9
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NASA NTRS2017

Spacecraft/Rover Hybrids for the Exploration of Small Solar System Bodies: Final Report: NASA NIAC - Phase II Study

This study investigated a mission architecture that allows the systematic and affordable in-situ exploration of small solar system bodies, such as asteroids, comets, and Martian moons (Figure 1). The architecture relies on the novel concept of spacecraft/rover hybrids,which are surface mobility platforms capable of achieving large surface coverage (by attitude controlled hops, akin to spacecraft flight), fine mobility (by tumbling), and coarse instrument pointing (by changing orientation relative to the ground) in the low-gravity environments(micro-g to milli-g) of small bodies. The actuation of the hybrids relies on spinning three internal flywheels. Using a combination of torques, the three flywheel motors can produce a reaction torque in any orientation without additional moving parts. This mobility concept allows all subsystems to be packaged in one sealed enclosure and enables the platforms to be minimalistic. The hybrids would be deployed from a mother spacecraft, which would act as a communication relay to Earth and would aid the in-situ assets with tasks such as localization and navigation (Figure 1). The hybrids are expected to be more capable and affordable than wheeled or legged rovers, due to their multiple modes of mobility (both hopping and tumbling), and have simpler environmental sealing and thermal management (since all components are sealed in one enclosure, assuming non-deployable science instruments). In summary, this NIAC Phase II study has significantly increased the TRL (Technology Readiness Level) of the mobility and autonomy subsystems of spacecraft/rover hybrids, and characterized system engineering aspects in the context of a reference mission to Phobos. Future studies should focus on improving the robustness of the autonomy module and further refine system engineering aspects, in view of opportunities for technology infusion.

mobility platforms↗
NASA NTRS2004

An aerobot for global in situ exploration of Titan

This paper describes the design and component testing of an aerobot that would be capable of global in situ exploration of Saturn's moon, Titan, over a 6 to 12 month mission lifetime. The proposed aerobot is a propeller-driven, buoyant vehicle that resembles terrestrial airships. However, the extremely cold Titan environment requires the use of cryogenic materials of construction and careful thermal design for protection of temperature-sensitive payload elements. Multiple candidate balloon materials have been identified based on extensive laboratory testing at 77 K. The most promising materials to date are laminates comprised of polyester fabrics and/or films with areal densities in the range of 40-100 g/m2. The aerobot hull is a streamlined ellipsoid 14 meters in length with a maximum diameter of 3 meters. The enclosed volume of 60 m3 is sufficient to float a mass of 234 kg at a maximum altitude of 8 km at Titan. Forward and aft ballonets are located inside the hull to enable the aerobot to descend to the surface while preserving a fully inflated streamlined shape. Altitude changes are effected primarily through thrust vectoring of the twin main propellers, with pressure modulated buoyancy change via the ballonets available as a slower backup option. A total of 100 W of electrical power is provided to the vehicle by a radioisotope power supply. Up to half of this power is available to the propulsion system to generate a top flight speed in the range of 1-2 m/s. This speed is expected to be greater than the near surface winds at Titan, enabling the aerobot to fly to and hover over targets of interest. A preliminary science payload has been devised for the aerobot to give it the capability for aerial imaging of the surface, atmospheric observations and sampling, and surface sample acquisition and analysis. Targeting, hovering, surface sample acquisition and vehicle health monitoring and automatic safing actions will all require significant on-board autonomy due to the over two hour round trip light time between Titan and Earth. An autonomy architecture and a core set of perception, reasoning and control technologies is under development using a free-flying airship testbed of approximately the same size as the proposed Titan aerobot. Data volume from the Titan science mission is expected to be on the order of 100-300 Mbit per day transmitted either direct to Earth through an 0.8 m high gain antenna or via an orbiter relay using an omni-directional antenna on the aerobot.

mobility↗
NASA NTRSDate not supplied

Scientific Physical and Operations Characterization (SPOC): Studying Scientists in the Wild to Inform Human Planetary Exploration Operations

The objective of the Scientific Physical and Operational Characterization (SPOC) project is to build an evidence-based description of terrestrial field science to inform the operational, physical, and tool requirements for planetary exploration extravehicular activities (xEVAs). EVAs of the future, including Artemis 2024 and beyond, intend to promote scientific productivity (e.g., LEAG science goals)[1]; however, no clear, objective pathway currently exists to enable this goal, particularly with respect to the desired increase in autonomy imparted to future astronauts. The SPOC project applies expertise in the fields of cognitive systems engineering [2-5], biomechanics, wearable sensors [6-8] and hardware/software to more targetly address these issues. In doing so, a terrestrial fieldwork ground-truth can be established that will benefit human and robotic exploration of other planetary surfaces.

M J Miller↗
NASA NTRS1998

Model Based Autonomy for Robust Mars Operations

Space missions have historically relied upon a large ground staff, numbering in the hundreds for complex missions, to maintain routine operations. When an anomaly occurs, this small army of engineers attempts to identify and work around the problem. A piloted Mars mission, with its multiyear duration, cost pressures, half-hour communication delays and two-week blackouts cannot be closely controlled by a battalion of engineers on Earth. Flight crew involvement in routine system operations must also be minimized to maximize science return. It also may be unrealistic to require the crew have the expertise in each mission subsystem needed to diagnose a system failure and effect a timely repair, as engineers did for Apollo 13. Enter model-based autonomy, which allows complex systems to autonomously maintain operation despite failures or anomalous conditions, contributing to safe, robust, and minimally supervised operation of spacecraft, life support, In Situ Resource Utilization (ISRU) and power systems. Autonomous reasoning is central to the approach. A reasoning algorithm uses a logical or mathematical model of a system to infer how to operate the system, diagnose failures and generate appropriate behavior to repair or reconfigure the system in response. The 'plug and play' nature of the models enables low cost development of autonomy for multiple platforms. Declarative, reusable models capture relevant aspects of the behavior of simple devices (e.g. valves or thrusters). Reasoning algorithms combine device models to create a model of the system-wide interactions and behavior of a complex, unique artifact such as a spacecraft. Rather than requiring engineers to all possible interactions and failures at design time or perform analysis during the mission, the reasoning engine generates the appropriate response to the current situation, taking into account its system-wide knowledge, the current state, and even sensor failures or unexpected behavior.

Kurien, James A.↗
NASA NTRS2005

NASA Intelligent Systems Project: Results, Accomplishments and Impact on Science Missions

The Intelligent Systems Project was responsible for much of NASA's programmatic investment in artificial intelligence and advanced information technologies. IS has completed three major project milestones which demonstrated increased capabilities in autonomy, human centered computing, and intelligent data understanding. Autonomy involves the ability of a robot to place an instrument on a remote surface with a single command cycle. Human centered computing supported a collaborative, mission centric data and planning system for the Mars Exploration Rovers and data understanding has produced key components of a terrestrial satellite observation system with automated modeling and data analysis capabilities. This paper summarizes the technology demonstrations and metrics which quantify and summarize these new technologies which are now available for future Nasa missions.

Coughlan, Joseph C.↗
NASA NTRS2001

Autonomy technology at JPL

This paper and exhibit describes the on-going research activities, plans and products of the Autonomy Technology program at NASA Jet Propulsion Laboratory. In this paper, we briefly describe the areas of Mission Planning and Execution, Distributed Autonomous Systems, Science Data Understanding, and Autonomous Guidance and Control.

autonomous rovers distributed systems planning con↗
NASA NTRSDate not supplied

Move to Talk, Talk to Move: Tightly Integrated Communication and Control for Coordinated Swarms of Small Spacecraft

The Move to Talk, Talk to Move: Tightly Integrated Communication and Control for Coordinated Swarms of Small Spacecraft project will build on existing research on collaborative autonomy of multi-agent systems and design techniques that will enable coordinated communication and control of spacecraft. The success of many space exploration and science missions hinges on real-time monitoring of time-varying and/or geographically distributed phenomena. This monitoring can be achieved using a swarm of small spacecraft, which collect data about the environment and share information within the swarm of spacecraft. Current space exploration missions typically issue commands to control each spacecraft individually from Earth, and the data gathered by each spacecraft is also transmitted to Earth separately via X-band communication over the Deep Space Network (DSN). This approach is expensive, slow, and unreliable. Many coordinated tasks amongst a swarm of autonomous agents (or, specifically, small spacecraft) rely on communication. Existing control, estimation, and decision algorithms often assume that mostly reliable communications are available; however, this is often not the case in actual environments and thus is a barrier to operating swarms of small spacecraft.

Qi Han↗
NASA NTRS2018

Integrated Planning and Execution for a Self-Reliant Mars Rover

Planetary rovers exploring the surface of Mars face a challenging operational environment that requires close cooperation between deliberative planning and behavioral execution in order to most efficiently leverage the robot’s capabilities into science value returned to earth. The Self-Reliant Rovers project envisions future rover missions that require only occasional high-level direction from human controllers to successfully conduct detailed in-situ studies of its Martian environs. To achieve this high degree of autonomy, this work leverages a spectrum of planning and execution techniques that allow the rover to respond appropriately to both opportunity and adversity it encounters. Small perturbations are accommodated at first by behavioral adaptation, with more and more extensive disruptions handled in turn by executive administration of plan flexibility, heuristic-guided plan repair strategies, and finally comprehensive replanning from science campaign goals. The integrated system has been deployed and tested on a terrestrial rover in an environment and under scenarios that anticipate those faced by future Mars rovers. This paper recounts complexities of planning and execution coordination faced in the rover domain and the practical solutions employed to address them. Particular emphasis is given to lessons from the field and foibles ripe for remedy by future advances in planning and execution research.

Gaines, Daniel↗
NASA NTRS2000

Autonomy Architectures for a Constellation of Spacecraft

Until the past few years, missions typically involved fairly large expensive spacecraft. Such missions have primarily favored using older proven technologies over more recently developed ones, and humans controlled spacecraft by manually generating detailed command sequences with low-level tools and then transmitting the sequences for subsequent execution on a spacecraft controller. This approach toward controlling a spacecraft has worked spectacularly on previous missions, but it has limitations deriving from communications restrictions - scheduling time to communicate with a particular spacecraft involves competing with other projects due to the limited number of deep space network antennae. This implies that a spacecraft can spend a long time just waiting whenever a command sequence fails. This is one reason why the New Millennium program has an objective to migrate parts of mission control tasks onboard a spacecraft to reduce wait time by making spacecraft more robust. The migrated software is called a "remote agent" and has 4 components: a mission manager to generate the high level goals, a planner/scheduler to turn goals into activities while reasoning about future expected situations, an executive/diagnostics engine to initiate and maintain activities while interpreting sensed events by reasoning about past and present situations, and a conventional real-time subsystem to interface with the spacecraft to implement an activity's primitive actions. In addition to needing remote planning and execution for isolated spacecraft, a trend toward multiple-spacecraft missions points to the need for remote distributed planning and execution. The past few years have seen missions with growing numbers of probes. Pathfinder has its rover (Sojourner), Cassini has its lander (Huygens), and the New Millenium Deep Space 3 (DS3) proposal involves a constellation of 3 spacecraft for interferometric mapping. This trend is expected to continue to progressively larger fleets. For example, one mission proposed to succeed DS3 would have 18 spacecraft flying in formation in order to detect earth-sized planets orbiting other stars. A proposed magnetospheric constellation would involve 5 to 500 spacecraft in Earth orbit to measure global phenomena within the magnetosphere. This work describes and compares three autonomy architectures for a system that continuously plans to control a fleet of spacecraft using collective mission goals instead of goals or command sequences for each spacecraft. A fleet of self-commanding spacecraft would autonomously coordinate itself to satisfy high level science and engineering goals in a changing partially-understood environment making feasible the operation of tens or even a hundred spacecraft (such as for interferometry or plasma physics missions). The easiest way to adapt autonomous spacecraft research to controlling constellations involves treating the constellation as a single spacecraft. Here one spacecraft directly controls the others as if they were connected. The controlling "master" spacecraft performs all autonomy reasoning, and the slaves only have real-time subsystems to execute the master's commands and transmit local telemetry/observations. The executive/diagnostics module starts actions and the master's real-time subsystem controls the action either locally or remotely through a slave. While the master/slave approach benefits from conceptual simplicity, it relies on an assumption that the master spacecraft's executive can continuously monitor the slaves' real-time subsystems, and this relies on high-bandwidth highly-reliable communications. Since unintended results occur fairly rarely, one way to relax the bandwidth requirements involves only monitoring unexpected events in spacecraft. Unfortunately, this disables the ability to monitor for unexpected events between spacecraft and leads to a host of coordination problems among the slaves. Also, failures in the communications system can result in losing slaves. The other two architectures improve robustness while reducing communications by progressively distributing more of the other three remote agent components across the constellation. In a teamwork architecture, all spacecraft have executives and real-time subsystems - only the leader has the planner/scheduler and mission manager. Finally, distributing all remote agent components leads to a peer-to-peer approach toward constellation control.

Barrett, Anthony↗
NASA NTRS1985

The Galileo attitude and articulation control system - A radiation-hard, high precision, state-of-the-art control system

The Galileo mission and spacecraft, consisting of a Jupiter-orbiter and an atmospheric entry probe, are discussed. Components will include: magnetometers and plasma-wave antennas on a boom, high-gain antenna, probe vehicle, two different bus electronics packages, and a radioisotope thermoelectric generator. Instruments, investigators and objectives are tabulated for both probe science and orbiter science investigations. Requirements in the design of the attitude and articulation control system are very stringent because of the complex dynamics, flexible body effects, the need for autonomy, and the severe radiation environment in the Jupiter nighborhood. Galileo was intended to be ready for launch via Space Shuttle in May of 1986.

Stephenson, R. Rhoads↗
NASA NTRS2017

User Needs and Advances in Space Wireless Sensing and Communications

Decades of space exploration and technology trends for future missions show the need for new approaches in space/planetary sensor networks, observatories, internetworking, and communications/data delivery to Earth. The User Needs to be discussed in this talk includes interviews with several scientists and reviews of mission concepts for the next generation of sensors, observatories, and planetary surface missions. These observatories, sensors are envisioned to operate in extreme environments, with advanced autonomy, whereby sometimes communication to Earth is intermittent and delayed. These sensor nodes require software defined networking capabilities in order to learn and adapt to the environment, collect science data, internetwork, and communicate. Also, some user cases require the level of intelligence to manage network functions (either as a host), mobility, security, and interface data to the physical radio/optical layer. For instance, on a planetary surface, autonomous sensor nodes would create their own ad-hoc network, with some nodes handling communication capabilities between the wireless sensor networks and orbiting relay satellites. A section of this talk will cover the advances in space communication and internetworking to support future space missions. NASA's Space Communications and Navigation (SCaN) program continues to evolve with the development of optical communication, a new vision of the integrated network architecture with more capabilities, and the adoption of CCSDS space internetworking protocols. Advances in wireless communications hardware and electronics have enabled software defined networking (DVB-S2, VCM, ACM, DTN, Ad hoc, etc.) protocols for improved wireless communication and network management. Developing technologies to fulfil these user needs for wireless communications and adoption of standardized communication/internetworking protocols will be a huge benefit to future planetary missions, space observatories, and manned missions to other planets.

Kegege, Obadiah↗
NASA NTRSDate not supplied

Starling Swarm Mission – Technology Objectives, Status and Future Applications

NASA’s Starling mission is advancing the readiness of technologies for cooperative groups of space craft referred to as swarms. The Starling swarm of four 6U spacecraft launched in July 2023, and is completing its tests in Low Earth Orbit (LEO) of four key technologies that will enable future swarm missions: onboard maneuver planning and execution to adjust the swarm formation; establishing and maintaining an adhoc network in space; relative and absolute orbit determination using optical sensors; autonomous collaboration between spacecraft for establishing and conducting a science observation plan. A mission extension is also being prepared to demonstrate a space traffic management architecture to address the large and rapidly growing number of space craft in LEO. In this presentation, the objectives of the Starling mission and its extension will be reviewed along with the latest status and mission outcomes. The presentation will also look at the revolutionary potential for swarms in future science and exploration missions and the impact to operations.

SpaceOps Starling Swarm Distributed Spacecraft Net↗
NASA NTRSDate not supplied

Distributed Spacecraft Autonomy - Development of Swarm Autonomy Capability and Scalability for Spacecraft

The Distributed Spacecraft Autonomy project is developing a suite of software tools that enable an operator to command and receive data from a swarm as a single entity, enable a swarm to autonomously coordinate its actions via distributed decision making and reactive closed-loop control, and model swarm behavior in the presence of anomalies or failures. Our use case is the mapping of the electron density of the ionosphere using radio tomography by coordinating the selection of appropriate GPS channels, and by recording Total Electron Count (TEC) measurements. DSA will be demonstrated onboard the NASA Ames Starling mission – a swarm of four small, LEO spacecraft, scheduled to launch in 2021. We will also perform a ground demonstration with simulated and hardware-in-the-loop elements, to validate the tools for controlling swarms of up to 100 assets. The capability to communicate autonomously between the swarm satellites is demonstrated via a sophisticated simulation architecture. Historical Plasmasphere TEC data obtained via dual-band Novatel GPS Receivers are utilized as a representative input dataset for the swarm. The representative TEC data and GPS satellite observability information is fed to the autonomous software package in place of a true real-time ground data collection process. The swarm satellites actively share status updates amongst one another and utilize multi-agent decision making to optimally identify regions of interest in the TEC distribution. The software, aware of the bandwidth limitations of the swarm satellites, prioritizes explorative measurements, which define the range of observability for the satellites, as well as exploitative measurements, which focus on maximizing the observance potential of regions with prolonged, elevated TEC density. The science of this study can ultimately be used to determine the dynamics and coupling of Earth’s magnetosphere, ionosphere, and atmosphere and their response to solar and terrestrial inputs. The findings can be applied to the imaging of critical, transient phenomena in the magnetosphere in later missions. Meanwhile, the swarm autonomy capabilities have far reaching potential in future satellite missions. As an experimental demonstration of the autonomous capabilities of the network, a message is first printed within a core Flight Executive (cFE) application. Two cFE applications that communicate with one another within the same core Flight System (cFS) are shown. Communication between mission applications on the internal cFE bus is extended to utilize Data Distribution Service (DDS) for vehicle-to-vehicle networking. The DDS middleware provides reliable delivery, routing, and topic subscription features over User Datagram Protocol (UDP). Leveraging Linux containerization, a networked set of satellite instances are generated by script to simulate swarm behavior. Swarm commanding and synchronization through the network is demonstrated under various topologies and data-loss conditions. Finally, autonomous swarm scalability from 2 satellites to 100 satellites is shown.

Distributed Autonomy↗
NASA NTRS2003

Resource Management for Real-Time Adaptive Agents

Increased autonomy and automation in onboard flight systems offer numerous potential benefits, including cost reduction and greater flexibility. The existence of generic mechanisms for automation is critical for handling unanticipated science events and anomalies where limitations in traditional control software with fixed, predetermined algorithms can mean loss of science data and missed opportunities for observing important terrestrial events. We have developed such a mechanism by adding a Hierarchical Agent-based ReaLTime technology (HART) extension to our Dynamic Resource Management (DRM) middleware. Traditional DRM provides mechanisms to monitor the realtime performance of distributed applications and to move applications among processors to improve real-time performance. In the HART project we have designed and implemented a performance adaptation mechanism to improve reaktime performance. To use this mechanism, applications are developed that can run at various levels of quality. The DRM can choose a setting for the quality level of an application dynamically at run-time in order to manage satellite resource usage more effectively. A groundbased prototype of a satellite system that captures and processes images has also been developed as part of this project to be used as a benchmark for evaluating the resource management framework A significant enhancement of this generic mission-independent framework allows scientists to specify the utility, or "scientific benefit," of science observations under various conditions like cloud cover and compression method. The resource manager then uses these benefit tables to determine in redtime how to set the quality levels for applications to maximize overall system utility as defined by the scientists running the mission. We also show how maintenance functions llke health and safety data can be integrated into the utility framework. Once thls framework has been certified for missions and successfully flight tested it can be reused with little development overhead for other missions. In contrast, current space missions llke Swift manage similar types of resource trade -off completely with the scientific application code itself, and such code must be re-certified and tested for each mission even if a large portion of the code base is shared. This final report discusses some of the major issues motivating this research effort, provides a literature review of the related work, discusses the resource management framework and ground-based satellite system prototype that has been developed, indicates what work is yet to be performed, and provides a list of publications resulting from this work.

Welch, Lonnie↗
NASA NTRS2018

Low-Latency Teleoperations: Operational Implications for Human Space Exploration

Low-latency teleoperations (LLT) is envisioned to be an element of human exploration missions in a number of different applications. LLT can be broadly considered to encompass any remote operation of an asset with a communication delay that is less than the human response time to allow for what is effectively "real-time" or "near real-time" operations. This paper will explore motivations and operational implications for why and how LLT might be used for human exploration space missions. LLT analyses have been performed under the auspices of the NASA Human Spaceflight Architecture Team (HAT) and Evolvable Mars Campaign (EMC). The EMC created a flexible, evolvable, capability-driven architectural strategy to enable a sustainable long-term human presence at Mars. LLT is envisioned to be part of that strategy for both in-space and on-surface applications, and this paper will expand on operational considerations within that broader strategic context, as well additional contexts. Some operational implications explored in this paper, derived largely from previous work, are: (1) crew mission support, for which we will address roles for Mission Control on earth, balanced with the capability for crew and robotic assets to operate independently, (2) science operations, with a focus on "backroom" support, highly dynamic science, and enhanced science return and efficiency, and (3) operational efficiency at a deep-space destination such as Mars, including implications for communications infrastructures and how to leverage and balance system autonomy with crew operations, both of which can inform the overall operational "choreography" between crew members, multiple shifts, and exploration assets.

human spaceflight↗