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NASA NTRS2024

Autonomous Medical Officer Support (AMOS) Software Technology Demonstrations on the International Space Station (ISS)

Performance of medical procedures in spaceflight beyond low Earth orbit (LEO) requires novel solutions to replace real-time ground support because as distance from Earth increases, communication latencies increase, hampering remote guidance. The Autonomous Medical Officer Support Software (AMOS) Technology Demonstrations on the International Space Station (ISS) trialed a novel software tool that shifts the emphasis from preflight training and real-time remote guidance (current ISS paradigm) to a new standard of multi-dimensional in-flight just-in-time (JIT) instruction. The AMOS platform is a skill management tool for all mission phases and currently features comprehensive training and guidance modules for urinary bladder and renal ultrasound examinations. Variability in Subject anatomy, Operator experience, and Operator receptiveness to instruction during autonomous exams are persistent but manageable limitations. Here we report the first successful demonstrations of autonomous imaging activities in the operational setting of spaceflight, validating this autonomous guidance proof of concept.

Douglas Ebert↗
NASA NTRSDate not supplied

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).

dynamic assurance case↗
NASA NTRS2008

A Testbed for Evaluating Lunar Habitat Autonomy Architectures

A lunar outpost will involve a habitat with an integrated set of hardware and software that will maintain a safe environment for human activities. There is a desire for a paradigm shift whereby crew will be the primary mission operators, not ground controllers. There will also be significant periods when the outpost is uncrewed. This will require that significant automation software be resident in the habitat to maintain all system functions and respond to faults. JSC is developing a testbed to allow for early testing and evaluation of different autonomy architectures. This will allow evaluation of different software configurations in order to: 1) understand different operational concepts; 2) assess the impact of failures and perturbations on the system; and 3) mitigate software and hardware integration risks. The testbed will provide an environment in which habitat hardware simulations can interact with autonomous control software. Faults can be injected into the simulations and different mission scenarios can be scripted. The testbed allows for logging, replaying and re-initializing mission scenarios. An initial testbed configuration has been developed by combining an existing life support simulation and an existing simulation of the space station power distribution system. Results from this initial configuration will be presented along with suggested requirements and designs for the incremental development of a more sophisticated lunar habitat testbed.

Lawler, Dennis G.↗
NASA NTRS2007

Implementation of a Point Algorithm for Real-Time Convex Optimization

The primal-dual interior-point algorithm implemented in G-OPT is a relatively new and efficient way of solving convex optimization problems. Given a prescribed level of accuracy, the convergence to the optimal solution is guaranteed in a predetermined, finite number of iterations. G-OPT Version 1.0 is a flight software implementation written in C. Onboard application of the software enables autonomous, real-time guidance and control that explicitly incorporates mission constraints such as control authority (e.g. maximum thrust limits), hazard avoidance, and fuel limitations. This software can be used in planetary landing missions (Mars pinpoint landing and lunar landing), as well as in proximity operations around small celestial bodies (moons, asteroids, and comets). It also can be used in any spacecraft mission for thrust allocation in six-degrees-of-freedom control.

Acikmese, Behcet↗
NASA NTRS2003

Working and Learning with Knowledge in the Lobes of a Humanoid's Mind

Humanoid class robots must have sufficient dexterity to assist people and work in an environment designed for human comfort and productivity. This dexterity, in particular the ability to use tools, requires a cognitive understanding of self and the world that exceeds contemporary robotics. Our hypothesis is that the sense-think-act paradigm that has proven so successful for autonomous robots is missing one or more key elements that will be needed for humanoids to meet their full potential as autonomous human assistants. This key ingredient is knowledge. The presented work includes experiments conducted on the Robonaut system, a NASA and the Defense Advanced research Projects Agency (DARPA) joint project, and includes collaborative efforts with a DARPA Mobile Autonomous Robot Software technical program team of researchers at NASA, MIT, USC, NRL, UMass and Vanderbilt. The paper reports on results in the areas of human-robot interaction (human tracking, gesture recognition, natural language, supervised control), perception (stereo vision, object identification, object pose estimation), autonomous grasping (tactile sensing, grasp reflex, grasp stability) and learning (human instruction, task level sequences, and sensorimotor association).

Ambrose, Robert↗
NASA NTRSDate not supplied

Automated Software for Manned Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C Dempsey↗
NASA NTRSDate not supplied

Automated Software for Manned Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C. Dempsey↗
NASA NTRSDate not supplied

Automated Software for Crewed Spacecraft - Bridging the Gap from Sci Fi to Reality

With a voice command or a few taps on the console, the spacecraft pivots on a dime at high velocity and gently docks to an orbiting space platform. This is the image most people have of the complex software computations and integrated hardware performance necessary for a spacecraft to successfully perform an automated launch, rendezvous, and docking. Today’s reality is that while computer operations are advancing rapidly, science fiction over-simplifies and over-sells current capabilities. This paper discusses the integration of spacecraft computer automation into the operation of one of the United States’ new Commercial Crew vehicles - the Boeing CST-100 Starliner. Lessons learned by the Boeing Mission Operations team, a private-public partnership with NASA, from conceptual design through real-time operation of the first test flight will be discussed. Focus will center on how operations has learned to use the automated software to their advantage while also knowing how to adjust the automation in response to spacecraft or mission anomalies. One goal of advanced spacecraft automation is the ability to reduce both the crew workload and the ground control footprint while at the same time increasing spacecraft and mission flexibility. Historically, crewed spacecraft required a large number of operators on the ground to use a plethora of tools to compute nominal and contingency mission trajectories. Moving those sophisticated software tools to being onboard the vehicle can reduce the need for such complex ground support. Given that today’s spacecraft software is not yet as capable or as flexible in all circumstances as the computers depicted in movies, there is usually a trade-off between software automation cost and the flexibility of that software resulting in a trade-off between what is performed on the spacecraft and what is left to onboard crew or ground control. For missions that go beyond the Moon, software that autonomously controls nearly every aspect of a crewed mission will become a necessity given the long time delays between the spacecraft and Earth’s ground control teams. The lessons learned by Boeing and its Mission Operations team, through the design and implementation of Starliner’s hardware and software automation, will be able to inform future public and private spacecraft design. As the technologies and capabilities evolve, incorporating lessons learned in successful low Earth orbit commercial crew vehicle missions, spacecraft designs will continue to improve and be able to better enable safe execution of human missions to the Moon and beyond.

Robert C Dempsey↗
NASA NTRS2006

Methodology for Designing Fault-Protection Software

A document describes a methodology for designing fault-protection (FP) software for autonomous spacecraft. The methodology embodies and extends established engineering practices in the technical discipline of Fault Detection, Diagnosis, Mitigation, and Recovery; and has been successfully implemented in the Deep Impact Spacecraft, a NASA Discovery mission. Based on established concepts of Fault Monitors and Responses, this FP methodology extends the notion of Opinion, Symptom, Alarm (aka Fault), and Response with numerous new notions, sub-notions, software constructs, and logic and timing gates. For example, Monitor generates a RawOpinion, which graduates into Opinion, categorized into no-opinion, acceptable, or unacceptable opinion. RaiseSymptom, ForceSymptom, and ClearSymptom govern the establishment and then mapping to an Alarm (aka Fault). Local Response is distinguished from FP System Response. A 1-to-n and n-to- 1 mapping is established among Monitors, Symptoms, and Responses. Responses are categorized by device versus by function. Responses operate in tiers, where the early tiers attempt to resolve the Fault in a localized step-by-step fashion, relegating more system-level response to later tier(s). Recovery actions are gated by epoch recovery timing, enabling strategy, urgency, MaxRetry gate, hardware availability, hazardous versus ordinary fault, and many other priority gates. This methodology is systematic, logical, and uses multiple linked tables, parameter files, and recovery command sequences. The credibility of the FP design is proven via a fault-tree analysis "top-down" approach, and a functional fault-mode-effects-and-analysis via "bottoms-up" approach. Via this process, the mitigation and recovery strategy(s) per Fault Containment Region scope (width versus depth) the FP architecture.

Barltrop, Kevin↗
NASA NTRS1996

SEDSAT 1 Technologies

The original goals of this project were to support the development of SEDSAT 1 for a tethered launch in July of 1997. This specifically required: (1) Monitoring development progress against a comprehensive delivery plan; (2) Incremental development and release of CDS and SEASIS software; (3) Supporting the integration of version 1.0 SEASIS software that will allow minimal autonomous operation without a software reload. These algorithms would include image quality evaluation, attitude determination, and autonomous earth imaging; and (4) Developing software requirements and design for ground segment software, concentrating on command and data download capability; and interface to external development efforts for a more comprehensive software suite to be used after the initial mission. Because of an unfavorable space shuttle safety review of the SEDS-3 tether deployer, and cost and schedule problems in upgrading the deployer, the mission was changed to an independent launch of SEDSAT. The original plan was to do a tether-less deployment from the space shuttle. Since this would have resulted in an unacceptable orbital lifetime, the mission was changed again to a tethered launch from a Delta II in June 1998. As a result of Marshall Space Flight Center's redirection of the SEDS-3 mission away from a tether launch, the whole question of a tether endmass had to be reconsidered. The net result of these multiple changes was twofold. First, we completed work needed to define some aspects of ground software on SEDSAT 1 that would remain constant no matter the launch mode. Second, we developed a set of concepts for using SEDSAT 1 technology to support alternative endmass missions on SEDS-3. Both of these are included.

Maier, Mark W.↗
NASA NTRS2007

Hybrid Automated Diagnosis of Discrete/Continuous Systems

A recently conceived method of automated diagnosis of a complex electromechanical system affords a complete set of capabilities for hybrid diagnosis in the case in which the state of the electromechanical system is characterized by both continuous and discrete values (as represented by analog and digital signals, respectively). The method is an integration of two complementary diagnostic systems: (1) beacon-based exception analysis for multi-missions (BEAM), which is primarily useful in the continuous domain and easily performs diagnoses in the presence of transients; and (2) Livingstone, which is primarily useful in the discrete domain and is typically restricted to quasi-steady conditions. BEAM has been described in several prior NASA Tech Briefs articles: "Software for Autonomous Diagnosis of Complex Systems" (NPO-20803), Vol. 26, No. 3 (March 2002), page 33; "Beacon-Based Exception Analysis for Multimissions" (NPO-20827), Vol. 26, No. 9 (September 2002), page 32; "Wavelet-Based Real-Time Diagnosis of Complex Systems" (NPO-20830), Vol. 27, No. 1 (January 2003), page 67; and "Integrated Formulation of Beacon-Based Exception Analysis for Multimissions" (NPO-21126), Vol. 27, No. 3 (March 2003), page 74. Briefly, BEAM is a complete data-analysis method, implemented in software, for real-time or off-line detection and characterization of faults. The basic premise of BEAM is to characterize a system from all available observations and train the characterization with respect to normal phases of operation. The observations are primarily continuous in nature. BEAM isolates anomalies by analyzing the deviations from nominal for each phase of operation. Livingstone is a model-based reasoner that uses a model of a system, controller commands, and sensor observations to track the system s state, and detect and diagnose faults. Livingstone models a system within the discrete domain. Therefore, continuous sensor readings, as well as time, must be discretized. To reason about continuous systems, Livingstone uses monitors that discretize the sensor readings using trending and thresholding techniques. In development of the a hybrid method, BEAM results were sent to Livingstone to serve as an independent source of evidence that is in addition to the evidence gathered by Livingstone standard monitors. The figure depicts the flow of data in an early version of a hybrid system dedicated to diagnosing a simulated electromechanical system. In effect, BEAM served as a "smart" monitor for Livingstone. BEAM read the simulation data, processed the data to form observations, and stored the observations in a file. A monitor stub synchronized the events recorded by BEAM with the output of the Livingstone standard monitors according to time tags. This information was fed to a real-time interface, which buffered and fed the information to Livingstone, and requested diagnoses at the appropriate times. In a test, the hybrid system was found to correctly identify a failed component in an electromechanical system for which neither BEAM nor Livingstone alone yielded the correct diagnosis.

Park, Han↗
NASA NTRS2005

Virtual Machine Language

Virtual Machine Language (VML) is a mission-independent, reusable software system for programming for spacecraft operations. Features of VML include a rich set of data types, named functions, parameters, IF and WHILE control structures, polymorphism, and on-the-fly creation of spacecraft commands from calculated values. Spacecraft functions can be abstracted into named blocks that reside in files aboard the spacecraft. These named blocks accept parameters and execute in a repeatable fashion. The sizes of uplink products are minimized by the ability to call blocks that implement most of the command steps. This block approach also enables some autonomous operations aboard the spacecraft, such as aerobraking, telemetry conditional monitoring, and anomaly response, without developing autonomous flight software. Operators on the ground write blocks and command sequences in a concise, high-level, human-readable programming language (also called VML ). A compiler translates the human-readable blocks and command sequences into binary files (the operations products). The flight portion of VML interprets the uplinked binary files. The ground subsystem of VML also includes an interactive sequence- execution tool hosted on workstations, which runs sequences at several thousand times real-time speed, affords debugging, and generates reports. This tool enables iterative development of blocks and sequences within times of the order of seconds.

Grasso, Christopher↗
NASA NTRSDate not supplied

Flow Boiling and Condensation Experiment: Flow Boiling in a Rectangular Channel with Subcooled Inlet Conditions in Microgravity

Two-phase thermal management subsystems that take advantage of both the sensible and latent heat of a working fluid can potentially yield significant enhancements in overall performance by adopting heat transfer processes that are based on phase transition like boiling and condensation. Performance of terrestrial two-phase flow systems may be predictable because the hydrodynamic and body forces are understood, however, in microgravity, which is predominant during planetary space travel, forces that are masked by the strong body force on Earth (gravitational or buoyancy force) reappear with different magnitude and influence. The need arose for a facility that provides for two-phase flow with phase transition testing in microgravity. The Flow Boiling and Condensation Experiment (FBCE) is a facility that was launched to the International Space Station in August of 2021 and is in operation since February of 2022. This facility enables investigators to perform two-phase flow and phase transition research in flow boiling and condensation. Along with the test module that is experiment specific, the FBCE system consists of the fluid, avionics, and software subsystems. Currently two test modules, namely, the Flow Boiling Module (FBM) and the Condensation Module for Heat Transfer (CM-HT) are available. A third module, the Transfer Line test Module (TL) is being developed. The fluid subsystem conditions and delivers the fluid at the desired thermodynamic state to the test module. It consists of two fluid modules and a heater module that are connected by flex hoses for fluid circulation and by data and electrical cables for control and data acquisition. Two avionics modules acquire pressure and temperature data from various sensors in the flow loop. For FBM, a high-speed camera is available to acquire images of the boiling process. Experiments are operated autonomously by software and are based on an Experiment Parameters Master Table (EPMT) that is uploaded to ISS and is executed by the FBCE flight software. This presentation briefly introduces the objectives of FBCE and provides a system description of the experiment onboard of the ISS/Fluid Integrated Rack (FIR). Results of the test campaign carried out using the FBM are presented. Specifically, microgravity flow boiling of n-perfluorohexane (test fluid) is discussed with subcooled inlet conditions in a single-side-heated rectangular channel of dimensions 114.6-mm heated length, 2.5-mm heated width, and 5.0-mm height. Key operating parameters investigated are mass velocity (199.90 – 3200.13 kg/m2s), inlet subcooling (0.10 – 45.76°C), and inlet pressure (113.30 – 164.29 kPa). Image sequences acquired via high-speed-video are shown to elucidate the interfacial flow physics. The effects of various parameters on flow boiling heat transfer in microgravity, from the onset of boiling to the critical heat flux are discussed. Heat transfer results are presented in terms of flow boiling curves, streamwise profiles of wall temperature and heat transfer coefficient, and parametric trends of local and averaged heat transfer coefficient, and the critical heat flux.

Two-phase flow and phase transition↗
NASA NTRS2012

Modular, Autonomous Command and Data Handling Software with Built-In Simulation and Test

The spacecraft system that plays the greatest role throughout the program lifecycle is the Command and Data Handling System (C&DH), along with the associated algorithms and software. The C&DH takes on this role as cost driver because it is the brains of the spacecraft and is the element of the system that is primarily responsible for the integration and interoperability of all spacecraft subsystems. During design and development, many activities associated with mission design, system engineering, and subsystem development result in products that are directly supported by the C&DH, such as interfaces, algorithms, flight software (FSW), and parameter sets. A modular system architecture has been developed that provides a means for rapid spacecraft assembly, test, and integration. This modular C&DH software architecture, which can be targeted and adapted to a wide variety of spacecraft architectures, payloads, and mission requirements, eliminates the current practice of rewriting the spacecraft software and test environment for every mission. This software allows missionspecific software and algorithms to be rapidly integrated and tested, significantly decreasing time involved in the software development cycle. Additionally, the FSW includes an Onboard Dynamic Simulation System (ODySSy) that allows the C&DH software to support rapid integration and test. With this solution, the C&DH software capabilities will encompass all phases of the spacecraft lifecycle. ODySSy is an on-board simulation capability built directly into the FSW that provides dynamic built-in test capabilities as soon as the FSW image is loaded onto the processor. It includes a six-degrees- of-freedom, high-fidelity simulation that allows complete closed-loop and hardware-in-the-loop testing of a spacecraft in a ground processing environment without any additional external stimuli. ODySSy can intercept and modify sensor inputs using mathematical sensor models, and can intercept and respond to actuator commands. ODySSy integration is unique in that it allows testing of actual mission sequences on the flight vehicle while the spacecraft is in various stages of assembly, test, and launch operations all without any external support equipment or simulators. The ODySSy component of the FSW significantly decreases the time required for integration and test by providing an automated, standardized, and modular approach to integrated avionics and component interface and functional verification. ODySSy further provides the capability for on-orbit support in the form of autonomous mission planning and fault protection.

Cuseo, John↗
NASA NTRS2013

Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles

This software implements a motion-planning module for a maritime autonomous surface vehicle (ASV). The module trails a given target while also avoiding static and dynamic surface hazards. When surface hazards are other moving boats, the motion planner must apply International Regulations for Avoiding Collisions at Sea (COLREGS). A key subset of these rules has been implemented in the software. In case contact with the target is lost, the software can receive and follow a "reacquisition route," provided by a complementary system, until the target is reacquired. The programmatic intention is that the trailed target is a submarine, although any mobile naval platform could serve as the target. The algorithmic approach to combining motion with a (possibly moving) goal location, while avoiding local hazards, may be applicable to robotic rovers, automated landing systems, and autonomous airships. The software operates in JPL s CARACaS (Control Architecture for Robotic Agent Command and Sensing) software architecture and relies on other modules for environmental perception data and information on the predicted detectability of the target, as well as the low-level interface to the boat controls.

Wolf, Michael↗
NASA NTRS1991

Higher-order neural network software for distortion invariant object recognition

The state-of-the-art in pattern recognition for such applications as automatic target recognition and industrial robotic vision relies on digital image processing. We present a higher-order neural network model and software which performs the complete feature extraction-pattern classification paradigm required for automatic pattern recognition. Using a third-order neural network, we demonstrate complete, 100 percent accurate invariance to distortions of scale, position, and in-plate rotation. In a higher-order neural network, feature extraction is built into the network, and does not have to be learned. Only the relatively simple classification step must be learned. This is key to achieving very rapid training. The training set is much smaller than with standard neural network software because the higher-order network only has to be shown one view of each object to be learned, not every possible view. The software and graphical user interface run on any Sun workstation. Results of the use of the neural software in autonomous robotic vision systems are presented. Such a system could have extensive application in robotic manufacturing.

Reid, Max B.↗