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A chronology of the requirements for various missions for which attitude support has been provided at the NASA Goddard Space Flight Center is presented. The support provided for a conventional mission and a semi-autonomous mission are compared.
The Earth Observing One Spacecraft is currently flying The Autonomous Sciencecraft Experiment (ASE) - onboard autonomy software to improve science return. The ASE software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. ASE includes software systems that perform science data analysis, mission planning, and run-time robust execution. In this article we describe the autonomy flight software and how it enables a new paradigm of autonomous science and mission operations.
The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) has spent several years developing operational onboard navigation systems (ONS's) to provide real time autonomous, highly accurate navigation products for spacecraft using NASA's space and ground communication systems. The highly successful Tracking and Data Relay Satellite (TDRSS) ONS (TONS) experiment on the Explorer Platform/Extreme Ultraviolet (EP/EUV) spacecraft, launched on June 7, 1992, flight demonstrated the ONS for high accuracy navigation using TDRSS forward link communication services. In late 1994, a similar ONS experiment was performed using EP/EUV flight hardware (the ultrastable oscillator and Doppler extractor card in one of the TDRSS transponders) and ground system software to demonstrate the feasibility of using an ONS with ground station forward link communication services. This paper provides a detailed evaluation of ground station-based ONS performance of data collected over a 20 day period. The ground station ONS (GONS) experiment results are used to project the expected performance of an operational system. The GONS processes Doppler data derived from scheduled ground station forward link services using a sequential estimation algorithm enhanced by a sophisticated process noise model to provide onboard orbit and frequency determination. Analysis of the GONS experiment performance indicates that real time onboard position accuracies of better than 125 meters (1 sigma) are achievable with two or more 5-minute contacts per day for the EP/EUV 525 kilometer altitude, 28.5 degree inclination orbit. GONS accuracy is shown to be a function of the fidelity of the onboard propagation model, the frequency/geometry of the tracking contacts, and the quality of the tracking measurements. GONS provides a viable option for using autonomous navigation to reduce operational costs for upcoming spacecraft missions with moderate position accuracy requirements.
NASA plans to send humans to Mars in about 20 years. The NASA Human Research Program supports research to mitigate the major risks to human health and performance on extended missions. However, there will undoubtedly be unforeseen events on any mission of this nature - thus mitigation of known risks alone is not sufficient to ensure optimal crew health and performance. Research should be directed not only to mitigating known risks, but also to providing crews with the tools to assess and enhance resilience, as a group and individually. We can draw on ideas from complexity theory and network theory to assess crew and individual resilience. The entire crew or the individual crewmember can be viewed as a complex system that is composed of subsystems (individual crewmembers or physiological subsystems), and the interactions between subsystems are of crucial importance for overall health and performance. An understanding of the structure of the interactions can provide important information even in the absence of complete information on the component subsystems. This is critical in human spaceflight, since insufficient flight opportunities exist to elucidate the details of each subsystem. Enabled by recent advances in noninvasive measurement of physiological and behavioral parameters, subsystem monitoring can be implemented within a mission and also during preflight training to establish baseline values and ranges. Coupled with appropriate mathematical modeling, this can provide real-time assessment of health and function, and detect early indications of imminent breakdown. Since the interconnected web of physiological systems (and crewmembers) can be interpreted as a network in mathematical terms, we can draw on recent work that relates the structure of such networks to their resilience (ability to self-organize in the face of perturbation). There are many parameters and interactions to choose from. Normal variability is an established characteristic of a healthy physiological response. Healthy coupling has been investigated less extensively, but there are cases in which too tight or too loose coupling can be problematic. This might be in inter-individual behaviors, such as sleep cycles, coordination of work and meal times, and coupled motions during communication. Less apparent are couplings of physiological systems, nevertheless examples abound of coupled systems which might be monitored: cardio-respiratory rhythms; circadian rhythms, body temperature, and sleep; stress markers and cognition, sleep, and performance; profiles of biochemical markers related to immune function and nutritional status; sensorimotor aspects such as motion sickness, ataxia, reaction time, and manual control. Tools for resilience are then the means to measure and analyze these parameters, incorporate them into appropriate models of normal variability and interconnectedness, and recognize when parameters or their couplings are outside of normal limits. What to do when a problem is identified depends on its nature. Changes can be made to crew procedures, work pacing, interpersonal interactions, sleep cycles, meal timing and content, as guided by the model. Use and continued development of these methods could not only provide tools for resilience, but also meaningful autonomous work for the crew on an extended flight.
Autonomic computing for spacecraft ground systems increases the system reliability and reduces the cost of spacecraft operations and software maintenance. In this paper, we present an autonomic computing solution for spacecraft ground systems at NASA Goddard Space Flight Center (GSFC), which consists of an open standard for a message oriented architecture referred to as the GMSEC architecture (Goddard Mission Services Evolution Center), and an autonomic computing tool, the Criteria Action Table (CAT). This solution has been used in many upgraded ground systems for NASA 's missions, and provides a framework for developing solutions with higher autonomic maturity.
The presentation will provide an overview of the Advanced Air Mobility efforts that are currently underway at NASA across a number of projects. The focus of the presentation is on key partnerships with industry and the associated flight tests that have been conducted under the Pathfinding for Airspace with Autonomous Vehicles subproejct and the National Campaign.
The Exploration Medical Capability (ExMC) element aims to provide astronauts with the means for their own health monitoring, diagnosis, and treatment during exploration missions. As space flight ventures further from earth, the need for autonomous medical care increases under greater constraints on size, mass, and resources. One pillar for diagnosis that crew would be separated from is laboratory analysis. Even now on ISS, blood samples must be collected and returned to earth for testing. In response, ExMC is assessing how assays for hematology, bone health, radiation exposure etc. could be addressed through commercial-off-the-shelf (COTS) and Small Business Innovation Research (SBIR) funded bioanalyzers that are miniaturizing lab technology. Since missions will reach distances where there are no timely replacements, validation on the International Space Station (ISS) is a necessary part of that assessment. In partnership with NASA Johnson Space Center (JSC) Immunology Lab and the Research Operations and Integration (ROI) element, ExMC conducted a technology demonstration on ISS of the rHEALTH ONE, a flow cytometry based bioanalyzer, to assess future devices based on this design. In flow cytometry, there are predominantly three ways to focus the cells (or particles) into a single file stream: hydrodynamic focusing, microcapillary, and acoustic focusing. The rHEALTH ONE utilizes the commercial standard, sheath-based hydrodynamic focusing. rHEALTH itself represents both a company and a suite of medical tools NASA has funded through SBIR grants towards the development of a promising diagnosis instrument for exploration missions. rHEALTH ONE is the interim version of the technology, functional as a benchtop analyzer and test bed for the next generation of rHEALTH in development. Several modifications were made to the rHEALTH ONE analyzer for operation in microgravity. For function, fluid management was key. A sheath-based analyzer uses sheath fluid to flow the sample, cleaning fluid to prevent biological contamination, and a reservoir to collect the liquid waste. The rHEALTH ONE analyzer uses bottles dependent on gravity to separate the air and liquid pathways and keep the liquids contained. It uses only 1 psig of air pressure to directly push the liquid through the device, requiring little-to-no resistance at inlet and outlet. A microtubing assembly with self-sealing luer connectors was designed – featuring 0.014 mm thick durable medical balloons to hold water inside the supply bottles – to create safe containment and easy access for the crew while maintaining the analyzer’s function. For safety, copper tape was added to the interior of the plastic housing to reduce electromagnetic interference, fluid and electrical connections were secured against vibration and leaks, and gaps were further sealed to ensure containment of the optical block and lasers. Water as the sheath and cleaning fluid and TOX 0 samples were used to reduce the biohazard risk to the crew. In May 2022, European Space Agency astronaut Samantha Cristoforetti demonstrated the rHEALTH ONE aboard ISS for its sample loading, flow cytometry, and data collection capability in microgravity. The JSC Immunology Lab provided flow cytometry expertise, designed the sample test protocol, and manufactured and benchmarked the flight samples on a ‘gold-standard’ flow cytometer. The analyzer was primed with water, purged of air, and four calibration solutions of polystyrene microparticles were tested to characterize its performance. Tightly controlled procedures and excellent execution prevented air bubble interference during air/water separation, fluid transfer, sample mixing and loading. Data showed a slight increase in signal noise on 3 of 5 channels and an anomaly of fluorophores migrating in one sample (confirmed by JSC post-flight). Flight results correctly detected the change in sample, matched the analyzer’s ground performance, and were consistent with the gold-standard’s ground results. Although areas were noted for improvement, these outcomes signified complete mission success.
The Autonomous Exploration for Gathering Increased Science System (AEGIS) provides automated targeting for remote sensing instruments on the Mars Exploration Rover (MER) mission, which at the time of this reporting has had two rovers exploring the surface of Mars (see figure). Currently, targets for rover remote-sensing instruments must be selected manually based on imagery already on the ground with the operations team. AEGIS enables the rover flight software to analyze imagery onboard in order to autonomously select and sequence targeted remote-sensing observations in an opportunistic fashion. In particular, this technology will be used to automatically acquire sub-framed, high-resolution, targeted images taken with the MER panoramic cameras. This software provides: 1) Automatic detection of terrain features in rover camera images, 2) Feature extraction for detected terrain targets, 3) Prioritization of terrain targets based on a scientist target feature set, and 4) Automated re-targeting of rover remote-sensing instruments at the highest priority target.
The paper discusses the implementation of fault tolerant digital flight control and navigation systems for rotorcraft application. It is shown that in implementing fault tolerance at the systems level using advanced LSI/VLSI technology, aircraft physical layout and flight systems requirements tend to define a system architecture of distributed, asynchronous microprocessors in which fault tolerance can be achieved locally through hardware redundancy and/or globally through application of analytical redundancy. The effects of asynchronism on the execution of dynamic flight software is discussed. It is shown that if the asynchronous microprocessors have knowledge of time, these errors can be significantly reduced through appropiate modifications of the flight software. Finally, the papear extends previous work to show that through the combined use of time referencing and stable flight algorithms, individual microprocessors can be configured to autonomously tolerate intermittent faults.
Viewgraphs are presented on earth to orbit propulsion, booster technology, an aeroassist flight experiment, robotics, remote sensing of Earth, and autonomous systems.
The Systems Autonomy Demonstration Program (SADP) represents NASA's major effort to demonstrate, through a series of complex ground experiments, the application and benefits of applying advanced automation technologies to the Space Station project. Lewis Research Center (LeRC) and Marshall Space Flight Center (MSFC) will first jointly develop an autonomous power system using existing Space Station testbed facilities at each center. The subsequent 1990 power-thermal demonstration will then involve the cooperative operation of the LeRC/MSFC power system with the Johnson Space Center (JSC's) thermal control and DMS/OMS testbed facilities. The testbeds and expert systems at each of the NASA centers will be interconnected via communication links. The appropriate knowledge-based technology will be developed for each testbed and applied to problems requiring intersystem cooperation. Primary emphasis will be focused on failure detection and classification, system reconfiguration, planning and scheduling of electrical power resources, and integration of knowledge-based and conventional control system software into the design and operation of Space Station testbeds.
A preliminary design for performing on orbit, autonomous research on microorganisms and cultured cells/tissues is presented. An understanding of gravity and its effects on cells is crucial for space exploration as well as for terrestrial applications. The payload is designed to be compatible with the Commercial Experiment Transporter (COMET) launch vehicle, an orbiter middeck locker interface, and with Space Station Freedom. Uplink/downlink capabilities and sample return through controlled reentry are available for all carriers. Autonomous testing activities are preprogrammed with in-flight reprogrammability. Sensors for monitoring temperature, pH, light, gravity levels, vibrations, and radiation are provided for environmental regulation and experimental data collection. Additional experimental data acquisition includes optical density measurement, microscopy, video, and film photography. On-board full data storage capabilities are provided. A fluid transfer mechanism is utilized for inoculation, sampling, and nutrient replenishment of experiment cultures. In addition to payload design, representative experiments were developed to ensure scientific objectives remained compatible with hardware capabilities. The project is defined to provide biological data pertinent to extended duration crewed space flight including crew health issues and development of a Controlled Ecological Life Support System (CELSS). In addition, opportunities are opened for investigations leading to commercial applications of space, such as pharmaceutical development, modeling of terrestrial diseases, and material processing.
This paper documents the transformation of NASA s Space Launch Initiative (SLI) Second Generation Reusable Launch Vehicle Program under the revised Integrated Space Transportation Plan, announced November 2002. Outlining the technology development approach followed by the original SLI, this paper gives insight into the current risk-reduction strategy that will enable confident development of the Nation s first orbital space plane (OSP). The OSP will perform an astronaut and contingency cargo transportation function, with an early crew rescue capability, thus enabling increased crew size and enhanced science operations aboard the International Space Station. The OSP design chosen for full-scale development will take advantage of the latest innovations American industry has to offer. The OSP Program identifies critical technologies that must be advanced to field a safe, reliable, affordable space transportation system for U.S. access to the Station and low-Earth orbit. OSP flight demonstrators will test crew safety features, validate autonomous operations, and mature thermal protection systems. Additional enabling technologies may be identified during the OSP design process as part of an overall risk-management strategy. The OSP Program uses a comprehensive and evolutionary systems acquisition approach, while applying appropriate lessons learned.
The testing and demonstrations are necessary for both parties to further development and certification of the technology in three key areas; flights beyond line of sight, collision avoidance, and autonomous operations.
The Traveler-Resilient Autonomy team (RA) at NASA Armstrong Flight Research Center (AFRC) is developing a hierarchical autonomous system framework called EVAA– Expandable Variable-Autonomy Architecture which is a reference implementation of a Run-Time Assurance (RTA) architecture, that is seen as a likely path to the certification of autonomous Unmanned Aerial Systems (UAS).
Artemis is NASA’s campaign to explore the Moon and beyond. Artemis I, the un-crewed exoLEO test flight, was completed in 2022. This paper will summarize the performance of the onboard targeting algorithm, the two-level targeter (TLT), during the flight. The function of the TLT is to autonomously recompute the burn targets for the upcoming burn (or multiple burns) in response to navigation and vehicle dispersions, providing a solution that meets all of the trajectory constraints. Although the TLT has been utilized previously as a ground-based planning tool, the Artemis I mission is the first time it has been flown onboard. The lessons learned from TLT performance during Artemis I will help to inform the further development of the algorithm for future Artemis missions.
This slide presentation reviews the concerns surrounding the automation of information handling. There are two types of decision support software that supports most Space Station Flight Controllers. one is very simple, and the other is very complex. A middle ground is sought. This is the reason for the Human Centered Autonomous and Assistant Systems Testbed (HCAAST) Project. The aim is to study flight controllers at work, and in the bigger picture, with particular attention to how they handle information and how coordination of multiple teams is performed. The focus of the project is on intelligent assistants to assist in handling information for the flight controllers.