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140 records · Page 8

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↗

Implementing Delay/Disruption Tolerant Networking for NASA’s Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) Mission

NASA’s Plankton, Aerosol, Clouds, ocean Ecosystem (PACE) mission will be the first NASA science mission to use Delay/Disruption Tolerant Networking (DTN) for routine operations. The DTN Bundle Protocol (BP) is being integrated into the core Flight Software (cFS) for the transfer of house-keeping files. DTN nodes will also be integrated into the Near Space Network (NSN) ground stations and the PACE Mission Operations Center. This paper will describe the DTN implementations, the PACE DTN operations concept and how this mission is a significant step towards the Solar System Internet.

dtn↗

Dynamic Assurance of Autonomous Systems through Ground Control Software

Assurance cases are being increasingly acknowledged as a way to build trust in complex systems with autonomous capabilities [1]. An assurance case is a comprehensive, defensible, and valid justification that a system will function as intended for the specific mission and operating environment. Such justifications for systems with autonomous capabilities are often based on various probabilistic quantifications [2]. Due to the dynamic nature of the environmental conditions in which these systems operate, as well as the changing nature of the autonomous systems themselves, these probabilistic quantifications cannot be simply estimated once during design time. Rather, they need to be continually evaluated during systems operations to ensure that the assurance case justifications are valid. We refer to the assurance case that combines both the static and dynamic elements as a Dynamic Assurance Case (DAC). Such complex systems with autonomous capabilities are often deployed with a Ground Control Software (GCS) component to enable remote operation. Whether the system is composed of a single unit or a fleet of units, deployed distributed or in remote environments, GCS acts as a window into the behavior of the deployed system. It receives telemetry from the system, issues commands to the system and provides various functionalities to visualize the system performance. We propose a dynamic assurance framework where the GCS acts as a relay between the autonomous system and its DAC. GCS can be used to measure both unit-specific as well as system-wide probabilistic quantifications using the incoming telemetry. We embed these quantifications throughout the DAC as variables that can be updated by external sources. We use the GCS to periodically update these variables, which allows us to continually evaluate the formally defined assurance case justifications. We demonstrate our dynamic assurance framework in the NASA Ames project Troupe1 that aims at developing a fleet of rovers capable of au- tonomously mapping their environment. The rovers work cooperatively, each collecting data for different parts of the environment. Each rover runs an identical core Flight System (cFS) [4] application. Troupe1 uses OpenC3 Cosmos [5] as the ground system, and AdvoCATE [3] to capture the system DAC. We show how we can measure both rover-specific and system-wide quantifications in Cosmos using its Ruby scripting editor and pass them into the DAC modelled in AdvoCATE. Then, we show how these incoming variables can be embedded in different parts of the DAC and how effects of their updates can be observed

Irfan Sljivo↗

Flight Software for the LOFTID Re-Entry Vehicle

NASA’s Low-Earth Orbit Flight Test of an Inflatable Decelerator, or LOFTID, demonstrated re-entry from low-Earth orbit of a 6-meter aeroshell designed to be used as a heat shield that is larger than the rocket shroud, enabling the return of much greater mass. The LOFTID Flight Software was developed in-house and consists of three components: the Power Distribution software, the Data Recorder software, and the Camera Controller software, along with the Ground Software used for testing, operations, data integrity, and data processing. This presentation will discuss issues found in developing the Power Distribution software in cFS on a non-Linux POSIX platform, designing an efficient architecture for recording of high bandwidth data, controlling over a dozen cameras in-flight, and creating the ground support tools to verify data integrity and support the post-processing of flight data.

Paul Brewster↗

Advancing Autonomy in Distributed Space Systems: Insights From on-Orbit Testing with the Starling 1.0 Mission

Autonomous decision-making is crucial for enhancing mission effectiveness in Distributed Space Systems (DSS), particularly in multi-spacecraft operations where communication constraints and mission complexity pose challenges. The Distributed Spacecraft Autonomy (DSA) team at NASA’s Ames Research Center is advancing autonomy in DSS through five key technical areas: distributed resource and task management, reactive operations, system modeling and simulation, human-swarm interaction, and ad hoc network communications. The DSA experiment onboard the Starling 1.0 Mission showcases collaborative resource allocation for multi-point science data collection with four small spacecraft. Autonomy in decision-making is highlighted as a crucial factor for multi-spacecraft missions, enabling spacecraft to operate independently, reducing reliance on ground control. This capability is particularly significant for future deep-space missions, where communication delays and limited data transmission capacity make traditional command and control approaches impractical. This demonstration focuses on a GPS Channel Selection Experiment, leveraging emergent capabilities like "shared sampling" and "simultaneous sampling" to optimize channel selection across the spacecraft swarm. The experiment aims to capture ionospheric phenomena such as the Equatorial Ionization Anomaly and Polar Patches. The DSA system's autonomous reconfiguration ability is showcased, emphasizing its adaptability to natural phenomena without significant integration efforts. The GPS Channel Selection Experiment utilizes a dual-band GPS receiver to estimate plasma density in the ionosphere. Explorative and exploitative channel selections are employed based on the nature of observed phenomena. The performance of DSA algorithms is evaluated in terms of optimal channel allocations and responsiveness to changes in observed features. The DSA Flight Software utilizes the Core Flight System (cFS) framework, ensuring compatibility with the Starling 1.0 flight mission software. DSA showcases results from RTI’s Connext DDS Micro communication middleware, enabling message routing over the Ad-Hoc Network of Starling 1.0. This paper provides a comprehensive overview of the DSA experiment's initial results, emphasizing the advancements in autonomy for Distributed Space Systems and the successful collaboration with the Starling 1.0 mission.

Caleb Ashmore Adams↗

The State of NOS3

The NASA Operational Simulator for Small Satellites (NOS3) showcases some of the Jon McBride Software Testing and Research (JSTAR) laboratories technologies on an open-source platform. NOS3 is a software digital twin providing a virtualized platform inside which you have your traditional flight software, ground software, environmental simulators, and middleware to keep all pieces in sync. NOS3 leverages the core Flight System (cFS), OpenC3 COSMOS, and NASA GSFC’s 42 software as the baseline to which additional research technologies can be developed. Current technologies to be demonstrated include NOS3 Igniter, constellation support, NASA JPL’s SYNOPSIS integration, and NASA GSFC’s OnAir. NOS3 Igniter is a GUI in which you can configure, build, and run your simulation. This along with improvements to the documentation and training available open source aims to reduce the ramp up time with new users and improve accessibility. As constellations introduce another level of complexity, it is important to ensure the baseline design reference mission covers all the basics required and allows users to experiment, understand, and test at all levels of the system. The Science Yield improvement via Onboard Prioritization and Summary of Information Systems (SYNOPSIS) is an open-source tool developed by NASA JPL to enable data prioritization and planning. GSFC’s Onboard Artificial Intelligence Research (OnAIR) enables custom algorithm development written in python to interface with the flight software allowing scientists to develop what they need for the next generation of missions and easily interface back to the traditional flight software. During the presentation, a review and demonstration of the above technologies is planned along with a roadmap.

NOS3↗

Overview of the ASDEX Upgrade results

After a 26-month vent ASDEX Upgrade (AUG) went back in operation with a newly designed upper W-divertor suitable for alternative divertor configurations (featuring in-vessel coils and cryo-pump). Parameter scans and an extensive set of measurements were obtained and their interpretation is ongoing. Prompted by the ITER wall change, dedicated experiments on non-boronized plasma startup were contrasted to that employing asymmetric and more symmetric boronizations. The asymmetric boronization proved to be as beneficial as the more symmetric one, which is in contrast to previous model calculations assuming perfect sticking of boron (measurements suggest sticking ≈ 0.3). In the startup phase also the impurity influxes at the outboard limiters were investigated contrasting the unboronized case featuring cold edges (low- Z radiation) to the boronized case, in which the lifetime of the boron layers could be estimated. Pedestal stability investigations revealed that the quasi-continuous exhaust (QCE) regime is obtained when ballooning modes are active in the vicinity of the separatrix and the global peeling-ballooning stability is high enough. Thus, at high enough shaping and high gas flux both can be achieved and QCE is a consequence. The closely related enhanced D-alpha (EDA) mode is not clearly distinguishable from QCE, e.g. the quasi-coherent mode characteristic for EDA also shows up in QCE. In QCE the impurity transport is behaving benign as could be measured for Ne with a novel analysis method making use of a comprehensive set of CXRS measurements. For high radiative fractions the regime of the X-point radiator (XPR) is accessible at AUG and the understanding of its access conditions and behaviour is further developed. Due to the localized radiative cooling at the X-point the XPR can be well diagnosed and thus controlled. For negative triangularity shapes, further experiments at increased shaping resulted in strongly heated L-mode plasmas avoiding ELMs. Two integrated modelling approaches towards ITER suggested that core W-accumulation will be no issue for ITER and that the fusion yield in ITER may be Q = 12 (i.e. ITPA20-IL scaling is too pessimistic). Further, investigations of the ITER ramp-down in AUG provide insights into maintaining position control. Various aspects of shattered pellet injection were investigated in AUG and one of the results show that with increasing Ne fraction the radiation during the current quench increases and the current decay becomes faster.

ASDEX Upgrade↗

Progress and innovations in the TCV tokamak research programme

Research on the Tokamak à Configuration Variable addresses a wide range of key questions relevant to ITER and future fusion power plants. Over the past two years, highly productive experimental campaigns have led to major advances across several areas: the ITER baseline scenario; pedestal properties in low-collisionality, peeling-limited conditions; and the development of high- β N , non-inductive regimes. Alternative high-confinement scenarios have likewise received significant attention, with remarkable progress in quasi-continuous exhaust operation, X-point radiator plasmas, and negative triangularity configurations. Substantial achievements were also made in the mitigation or benign termination of runaway electron beams, in elucidating fast-ion loss mechanisms, and in improving exhaust behaviour in both conventional and alternative divertor geometries. These experimental results have been strongly supported by advances in modelling and their direct application to the experiment, ranging from gyrokinetic simulations of core and pedestal turbulence to fluid-based studies of scrape-off layer and divertor physics in diverse geometries. Plasma control has taken on an increasingly important role, with model-based and data-driven approaches now closely intertwined with physics studies. This article provides a overview of these recent activities, together with a brief outlook on forthcoming upgrades and next steps.

EPFL↗

Application of the Core Flight System to a Lunar Rover

Resource Prospector (RP) is a lunar mission sponsored by NASAs Advanced Exploration Systems (AES) division, that aims to study in-situ resource utilization (ISRU) feasibility and technologies on the surface of the moon. The RP missions lunar surface segment includes a rover equipped with with a suite of instruments specifically designed to measure and map volatiles both at the surface and in the subsurface. Of particular interest is the quantity and state of volatiles in permanently shadowed regions. To conduct the mission, ground system operators will remotely drive the rover, directing it to waypoints along the surface in order to achieve measurement objectives. At selected locations, an onboard drill will be deployed to collect material and obtain direct measurements of the subsurface constituents. RP is currently planned for launch in 2022. RP is managed at NASA Ames Research Center. The RP Rover is being designed and developed by NASA Johnson Space Center (JSC) in partnership with NASA Ames. NASA Kennedy Space Center (KSC) is responsible for the Honeybee drilling system and science payload.In order to better understand the technical challenges and demonstrate capability, in 2015 the RP project developed a rover testbed (known as RP15). In this mission in a year, a rover was designed, developed, and outfitted with science instruments and a drill. The rover was operated from a remote operations center, and operated in an outdoor lunar rock yard at Johnson space center. The study was a resounding success meeting all objectives. The RP Rover software architecture and development processes were based on the successful Lunar Atmosphere and Dust Environment Explorer spacecraft. This architecture is built on the Core Flight System software and an interface to MatlabSimulink auto-generated software components known as the Simulink Interface Layer (SIL). The application of this lunar satellite inspired framework worked well for the rover application, and is currently being planned for the mission. This presentation provides an overview of the architecture and processes, and describes some of the changes and challenges for the rover application.

CFS↗

Orion Backup Flight Software (BFS)

Orion Backup Flight Software (BFS) is a joint NASA/Lockheed Martin effort designed to prevent the loss of the Orion crew. BFS will only take over in the event the primary flight software (PFSW) fails to operate properly due to either hardware or software failures. Since the PFSW runs identical software on identical hardware, it is conceivable that a single issue could simultaneously bring down all the PFSW. To minimize the likelihood BFS would be affected by the same issue, BFS was specifically designed to be as different as possible from PFSW: BFS runs on different hardware, a separate operating system, a different compiler, does not share software libraries, and is written by a different team of programmers. This presentation will provide a high-level overview of the Artemis missions and the Orion vehicle, as well as provide additional details of the BFS system (including how BFS is different than the PFSW). The overall BFS capability evolution and timeline (milestones reached as well as work remaining) through the Artemis III mission will be discussed. Additionally, the verification and validation plans for BFS will be presented, describing how we ensure that only validated configuration data is loaded onto the flight vehicle. Finally, the presentation will close with lessons learned and future plans for Orion BFS.

CFS↗

The Troupe System: an Autonomous Multi-Agent Rover Swarm

Autonomous cooperative robotic systems are the future of space exploration. The complexity of such systems makes their development, verification and assurance challenging. The Robust Software Engineering group at NASA Ames has developed the Troupe project that aims to explore the design and development of a swarm of autonomous rovers tasked to perform autonomous exploration and mapping of an unknown terrain. In this paper, we showcase the system design, and accompanying verification and validation tools integrated in the Troupe system development life-cycle.

TROUPE↗

Preliminary Design of Robotic Control Software for Mars Sample Return - Capture, Containment, and Return System

The Mars Sample Return (MSR) campaign aims to acquire and return to Earth a set of Mars samples for investigation in terrestrial laboratories. Mars 2020 has collected an adequate number of samples and deposited them in sealed sample tubes at a designated Martian depot. Sample tubes will be placed in cylindrical containers called Orbiting Samples (OS) by the Perseverance Rover, and later brought to Earth by the Earth Return Orbiter (ERO) and the MSR - Capture, Containment, and Return System (CCRS). Robot Software (RSW) is a set of software processes for commanding and monitoring the avionics that controls robotic mechanisms designed to sterilize and install OS into Earth Entry System (EES) for return to Earth. This paper describes a preliminary design of RSW including motion modes, architecture, and finite state machine. Additionally, software engineering procedures and testing of RSW is provided. A preliminary performance analysis is presented and the paper concludes with future work and a discussion of design decisions.

MSR↗