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NASA NTRS1992

Cardiovascular physiology - Effects of microgravity

Experiments during spaceflight and its groundbase analog, bedrest, provide consistent data which demonstrate that numerous changes in cardiovascular function occur as part of the physiological adaptation process to the microgravity environment. These include elevated heart rate and venous compliance, lowered blood volume, central venous pressure and stroke volume, and attenuated autonomic reflex functions. Although most of these adaptations are not functionally apparent during microgravity exposure, they manifest themselves during the return to the gravitational challenge of earth's terrestrial environment as orthostatic hypotension and instability, a condition which could compromise safety, health and productivity. Development and application of effective and efficient countermeasures such as saline "loading," intermittent venous pooling, pharmacological treatments, and exercise have become primary emphases of the space life sciences research effort with only limited success. Successful development of countermeasures will require knowledge of the physiological mechanisms underlying cardiovascular adaptation to microgravity which can be obtained only through controlled, parallel groundbased research to complement carefully designed flight experiments. Continued research will provide benefits for both space and clinical applications as well as enhance the basic understanding of cardiovascular homeostasis in humans.

Convertino, V.↗

NASA NTRS2003

Microgravity alters respiratory sinus arrhythmia and short-term heart rate variability in humans

We studied heart rate (HR), heart rate variability (HRV), and respiratory sinus arrhythmia (RSA) in four male subjects before, during, and after 16 days of spaceflight. The electrocardiogram and respiration were recorded during two periods of 4 min controlled breathing at 7.5 and 15 breaths/min in standing and supine postures on the ground and in microgravity. Low (LF)- and high (HF)-frequency components of the short-term HRV (< or =3 min) were computed through Fourier spectral analysis of the R-R intervals. Early in microgravity, HR was decreased compared with both standing and supine positions and had returned to the supine value by the end of the flight. In microgravity, overall variability, the LF-to-HF ratio, and RSA amplitude and phase were similar to preflight supine values. Immediately postflight, HR increased by approximately 15% and remained elevated 15 days after landing. LF/HF was increased, suggesting an increased sympathetic control of HR standing. The overall variability and RSA amplitude in supine decreased postflight, suggesting that vagal tone decreased, which coupled with the decrease in RSA phase shift suggests that this was the result of an adaptation of autonomic control of HR to microgravity. In addition, these alterations persisted for at least 15 days after return to normal gravity (1G).

Clinical Trial↗

NASA NTRS2017

Quantifying Pilot Contribution to Flight Safety during Drive Shaft Failure

Accident statistics cite the flight crew as a causal factor in over 60% of large transport aircraft fatal accidents. Yet, a well-trained and well-qualified pilot is acknowledged as the critical center point of aircraft systems safety and an integral safety component of the entire commercial aviation system. The latter statement, while generally accepted, cannot be verified because little or no quantitative data exists on how and how many accidents/incidents are averted by crew actions. A joint NASA/FAA high-fidelity motion-base simulation experiment specifically addressed this void by collecting data to quantify the human (pilot) contribution to safety-of-flight and the methods they use in today's National Airspace System. A human-in-the-loop test was conducted using the FAA's Oklahoma City Flight Simulation Branch Level D-certified B-737-800 simulator to evaluate the pilot's contribution to safety-of-flight during routine air carrier flight operations and in response to aircraft system failures. These data are fundamental to and critical for the design and development of future increasingly autonomous systems that can better support the human in the cockpit. Eighteen U.S. airline crews flew various normal and non-normal procedures over a two-day period and their actions were recorded in response to failures. To quantify the human's contribution to safety of flight, crew complement was used as the experiment independent variable in a between-subjects design. Pilot actions and performance during single pilot and reduced crew operations were measured for comparison against the normal two-crew complement during normal and non-normal situations. This paper details the crew's actions, including decision-making, and responses while dealing with a drive shaft failure - one of 6 non-normal events that were simulated in this experiment.

Kramer, Lynda J.↗

NASA NTRS2003

Autonomous Telemetry Collection for Single-Processor Small Satellites

For the Space Technology 5 mission, which is being developed under NASA's New Millennium Program, a single spacecraft processor will be required to do on-board real-time computations and operations associated with attitude control, up-link and down-link communications, science data processing, solid-state recorder management, power switching and battery charge management, experiment data collection, health and status data collection, etc. Much of the health and status information is in analog form, and each of the analog signals must be routed to the input of an analog-to-digital converter, converted to digital form, and then stored in memory. If the micro-operations of the analog data collection process are implemented in software, the processor may use up a lot of time either waiting for the analog signal to settle, waiting for the analog-to-digital conversion to complete, or servicing a large number of high frequency interrupts. In order to off-load a very busy processor, the collection and digitization of all analog spacecraft health and status data will be done autonomously by a field-programmable gate array that can configure the analog signal chain, control the analog-to-digital converter, and store the converted data in memory.

Speer, Dave↗

NASA NTRS2013

Autonomous Vision-Based Tethered-Assisted Rover Docking

Many intriguing science discoveries on planetary surfaces, such as the seasonal flows on crater walls and skylight entrances to lava tubes, are at sites that are currently inaccessible to state-of-the-art rovers. The in situ exploration of such sites is likely to require a tethered platform both for mechanical support and for providing power and communication. Mother/daughter architectures have been investigated where a mother deploys a tethered daughter into extreme terrains. Deploying and retracting a tethered daughter requires undocking and re-docking of the daughter to the mother, with the latter being the challenging part. In this paper, we describe a vision-based tether-assisted algorithm for the autonomous re-docking of a daughter to its mother following an extreme terrain excursion. The algorithm uses fiducials mounted on the mother to improve the reliability and accuracy of estimating the pose of the mother relative to the daughter. The tether that is anchored by the mother helps the docking process and increases the system's tolerance to pose uncertainties by mechanically aligning the mating parts in the final docking phase. A preliminary version of the algorithm was developed and field-tested on the Axel rover in the JPL Mars Yard. The algorithm achieved an 80% success rate in 40 experiments in both firm and loose soils and starting from up to 6 m away at up to 40 deg radial angle and 20 deg relative heading. The algorithm does not rely on an initial estimate of the relative pose. The preliminary results are promising and help retire the risk associated with the autonomous docking process enabling consideration in future martian and lunar missions.

Axel docking↗

NASA NTRS2003

Reinforcement Learning for Weakly-Coupled MDPs and an Application to Planetary Rover Control

Weakly-coupled Markov decision processes can be decomposed into subprocesses that interact only through a small set of bottleneck states. We study a hierarchical reinforcement learning algorithm designed to take advantage of this particular type of decomposability. To test our algorithm, we use a decision-making problem faced by autonomous planetary rovers. In this problem, a Mars rover must decide which activities to perform and when to traverse between science sites in order to make the best use of its limited resources. In our experiments, the hierarchical algorithm performs better than Q-learning in the early stages of learning, but unlike Q-learning it converges to a suboptimal policy. This suggests that it may be advantageous to use the hierarchical algorithm when training time is limited.

Bernstein, Daniel S.↗

NASA NTRS2016

Conceptual Drivers for an Exploration Medical System

Interplanetary spaceflight provides unique challenges that have not been encountered in prior spaceflight experience. Extended distance and timeframes introduce new challenges such as an inability to resupply medications and consumables, inability to evacuate injured or ill crew, and communication delays that introduce a requirement for some level of autonomous medical capability. Because of these challenges the approaches used in prior programs have limited application to a proposed three year Mars mission. This paper proposes a paradigm shift in the approach to medical risk mitigation for crew health and mission objectives threatened by inadequate medical capabilities in the setting of severely limited resources. A conceptual approach is outlined to derive medical system and vehicle needs from an integrated vision of how medical care will be provided within this new paradigm. Using NASA Design Reference Missions this process assesses each mission phase to deconstruct medical needs at any point during a mission. Two operational categories are proposed, nominal operations (pre-planned activities) and contingency operations (medical conditions requiring evaluation) that meld clinical needs and research needs into a single system. These definitions are used to derive a task level analysis to support quantifiable studies into a medical capabilities trade. This trade allows system design to proceed from both a mission centric and ethics-based approach to medical limitations in an exploration class mission.

Antonsen, E.↗

NASA NTRS2019

Mitigations to Reduce the Law of Unintended Consequences for Autonomy and Other Technological Advances

The United Nations states that Earth’s population is expected to reach just under 10 billion people (9.7) by the year 2050. To meet the demands of 10 billion people, governments, multinational corporations and global leaders are relying on autonomy and technological advances to augment and/or accommodate human efforts to meet the required needs of daily living. Genetically modified organisms (GMOs), Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) gene-edited plants and cloning will be utilized to expand human food supply. Biomimetic implants are expected to improve life expectancy with 3D printed body parts. Human functioning will be extended with wearables and cybernetic implants continuing humanity’s path toward transhumanism. Families will be strengthened with 3 parent households. Disease will surely be eradicated using the CRISPR-CAS9 genetic engineering revolution to design out undesirable human traits and to design in new capabilities. With autonomous cars, trucks and buses on our roads and on-demand autonomous aircraft delivering pizzas, medical prescriptions and groceries in the air and multi-planet vehicles traversing space, utopia will finally arrive! Or will it? All of these powerful, man-made, technological systems will experience unintended consequences with certainty. Instead of over-reacting with hysteria and fear, we should be seeking answers to the following questions - “What skills are required to architect socially-healthy technological systems for 2050?” “What mindsets should we embody to ameliorate hubris syndrome and to build our future technological systems with deliberation, soberness and social responsibility?”

Morris, A. Terry↗

NASA NTRSDate not supplied

Biospecimen and Data Sharing: NASA Institutional Scientific Collection at Ames Research Center (ISC-ARC), and the Ames Life Sciences Data Archive (ALSDA)

For decades, NASA and international partners have conducted biological experiments in space to understand effects of spaceflight and address potential hazards. To enable spaceflight back to the Moon, and then to Mars and beyond, it is imperative to further understand basic science and health risks associated with spaceflight, along with developing countermeasures. The sending of experiments and organisms into space is a costly endeavor. To maximize scientific return, sharing with the scientific community both space-flown biospecimens and data from completed experiments is essential. New fundamental, applied, and bioinformatic science insights can be gained from specimen and data sharing efforts. Data reuse enables spaceflight health risk modeling, analyzing adverse outcomes across spaceflight hazards, and deep space autonomous support for the flight medical officer.

Data↗

NASA NTRS1994

A Space Station robot walker and its shared control software

In this paper, we first briefly overview the update of the self-mobile space manipulator (SMSM) configuration and testbed. The new robot is capable of projecting cameras anywhere interior or exterior of the Space Station Freedom (SSF), and will be an ideal tool for inspecting connectors, structures, and other facilities on SSF. Experiments have been performed under two gravity compensation systems and a full-scale model of a segment of SSF. This paper presents a real-time shared control architecture that enables the robot to coordinate autonomous locomotion and teleoperation input for reliable walking on SSF. Autonomous locomotion can be executed based on a CAD model and off-line trajectory planning, or can be guided by a vision system with neural network identification. Teleoperation control can be specified by a real-time graphical interface and a free-flying hand controller. SMSM will be a valuable assistant for astronauts in inspection and other EVA missions.

Xu, Yangsheng↗

NASA NTRS1991

Intelligent computer-aided training and tutoring

Specific autonomous training systems based on artificial intelligence technology for use by NASA astronauts, flight controllers, and ground-based support personnel that demonstrate an alternative to current training systems are described. In addition to these specific systems, the evolution of a general architecture for autonomous intelligent training systems that integrates many of the features of traditional training programs with artificial intelligence techniques is presented. These Intelligent Computer-Aided Training (ICAT) systems would provide, for the trainee, much of the same experience that could be gained from the best on-the-job training. By integrating domain expertise with a knowledge of appropriate training methods, an ICAT session should duplicate, as closely as possible, the trainee undergoing on-the-job training in the task environment, benefitting from the full attention of a task expert who is also an expert trainer. Thus, the philosophy of the ICAT system is to emulate the behavior of an experienced individual devoting his full time and attention to the training of a novice - proposing challenging training scenarios, monitoring and evaluating the actions of the trainee, providing meaningful comments in response to trainee errors, responding to trainee requests for information, giving hints (if appropriate), and remembering the strengths and weaknesses displayed by the trainee so that appropriate future exercises can be designed.

Loftin, R. Bowen↗

NASA NTRS2001

Collaboration Between NASA Centers of Excellence on Autonomous System Software Development

Software for space systems flight operations has its roots in the early days of the space program when computer systems were incapable of supporting highly complex and flexible control logic. Control systems relied on fast data acquisition and supervisory control from a roomful of systems engineers on the ground. Even though computer hardware and software has become many orders of magnitude more capable, space systems have largely adhered to this original paradigm In an effort to break this mold, Kennedy Space Center (KSC) has invested in the development of model-based diagnosis and control applications for ten years having broad experience in both ground and spacecraft systems and software. KSC has now partnered with Ames Research Center (ARC), NASA's Center of Excellence in Information Technology, to create a new paradigm for the control of dynamic space systems. ARC has developed model-based diagnosis and intelligent planning software that enables spacecraft to handle most routine problems automatically and allocate resources in a flexible way to realize mission objectives. ARC demonstrated the utility of onboard diagnosis and planning with an experiment aboard Deep Space I in 1999. This paper highlights the software control system collaboration between KSC and ARC. KSC has developed a Mars In-situ Resource Utilization testbed based on the Reverse Water Gas Shift (RWGS) reaction. This plant, built in KSC's Applied Chemistry Laboratory, is capable of producing the large amount of Oxygen that would be needed to support a Human Mars Mission. KSC and ARC are cooperating to develop an autonomous, fault-tolerant control system for RWGS to meet the need for autonomy on deep space missions. The paper will also describe how the new system software paradigm will be applied to Vehicle Health Monitoring, tested on the new X vehicles and integrated into future launch processing systems.

Goodrich, Charles H.↗

NASA NTRS1997

Error Analysis System for Spacecraft Navigation Using the Global Positioning System (GPS)

The Flight Dynamics Division (FDD) at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) is currently developing improved space-navigation filtering algorithms to use the Global Positioning System (GPS) for autonomous real-time onboard orbit determination. In connection with a GPS technology demonstration on the Small Satellite Technology Initiative (SSTI)/Lewis spacecraft, FDD analysts and programmers have teamed with the GSFC Guidance, Navigation, and Control Branch to develop the GPS Enhanced Orbit Determination Experiment (GEODE) system. The GEODE system consists of a Kalman filter operating as a navigation tool for estimating the position, velocity, and additional states required to accurately navigate the orbiting Lewis spacecraft by using astrodynamic modeling and GPS measurements from the receiver. A parallel effort at the FDD is the development of a GPS Error Analysis System (GEAS) that will be used to analyze and improve navigation filtering algorithms during development phases and during in-flight calibration. For GEAS, the Kalman filter theory is extended to estimate the errors in position, velocity, and other error states of interest. The estimation of errors in physical variables at regular intervals will allow the time, cause, and effect of navigation system weaknesses to be identified. In addition, by modeling a sufficient set of navigation system errors, a system failure that causes an observed error anomaly can be traced and accounted for. The GEAS software is formulated using Object Oriented Design (OOD) techniques implemented in the C++ programming language on a Sun SPARC workstation. The Phase 1 of this effort is the development of a basic system to be used to evaluate navigation algorithms implemented in the GEODE system. This paper presents the GEAS mathematical methodology, systems and operations concepts, and software design and implementation. Results from the use of the basic system to evaluate navigation algorithms implemented on GEODE are also discussed. In addition, recommendations for generalization of GEAS functions and for new techniques to optimize the accuracy and control of the GPS autonomous onboard navigation are presented.

Truong, S. H.↗

NASA NTRS2004

Advanced Life Support Project: Crop Experiments at Kennedy Space Center

Crop production systems provide bioregenerative technologies to complement human crew life support requirements on long duration space missions. Kennedy Space Center has lead NASA's research on crop production systems that produce high value fresh foods, provide atmospheric regeneration, and perform water processing. As the emphasis on early missions to Mars has developed, our research focused on modular, scalable systems for transit missions, which can be developed into larger autonomous, bioregenerative systems for subsequent surface missions. Components of these scalable systems will include development of efficient light generating or collecting technologies, low mass plant growth chambers, and capability to operate in the high energy background radiation and reduced atmospheric pressures of space. These systems will be integrated with air, water, and thermal subsystems in an operational system. Extensive crop testing has been done for both staple and salad crops, but limited data is available on specific cultivar selection and breadboard testing to meet nominal Mars mission profiles of a 500-600 day surface mission. The recent research emphasis at Kennedy Space Center has shifted from staple crops, such as wheat, soybean and rice, toward short cycle salad crops such as lettuce, onion, radish, tomato, pepper, and strawberry. This paper will review the results of crop experiments to support the Exploration Initiative and the ongoing development of supporting technologies, and give an overview of capabilities of the newly opened Space Life Science (SLS) Lab at Kennedy Space Center. The 9662 square m (104,000 square ft) SLS Lab was built by the State of Florida and supports all NASA research that had been performed in Hanger-L. In addition to NASA research, the SLS Lab houses the Florida Space Research Institute (FSRI), responsible for co-managing the facility, and the University of Florida (UF) has established the Space Agriculture and Biotechnology Research and Education (SABRE) Center with several faculty.

Sager, John C.↗

NASA NTRS2022

Space Applications of a Trusted AI Framework: Experiences and Lessons Learned

Artificial intelligence (AI), which encompasses machine learning (ML), has become a critical technology due to its well-established success in a wide array of applications. However, the proper application of AI remains a central topic of discussion in many safety-critical fields. This has limited its success in autonomous systems due to the difficulty of ensuring AI algorithms will perform as desired and that users will understand and trust how they operate. In response, there is growing demand for trustability in AI to address both the expectations and concerns regarding its use. The Aerospace Corporation (Aerospace) developed a Framework for Trusted AI (henceforth referred to as the framework) to encourage best practices for the implementation, assessment, and control of AI-based applications. It is generally applicable, being based on terms and definitions that cut across AI domains, and thus is a starting point for practitioners to tailor to their particular application. To help demonstrate how the framework can be tailored into mission assurance guidance for the space domain, Aerospace sought the involvement of the Jet Propulsion Laboratory (JPL) to engage with actual examples of AI-based space autonomy.

Kaufman, James↗

NASA NTRS1998

Information Systems for NASA's Aeronautics and Space Enterprises

The aerospace industry is being challenged to reduce costs and development time as well as utilize new technologies to improve product performance. Information technology (IT) is the key to providing revolutionary solutions to the challenges posed by the increasing complexity of NASA's aeronautics and space missions and the sophisticated nature of the systems that enable them. The NASA Ames vision is to develop technologies enabling the information age, expanding the frontiers of knowledge for aeronautics and space, improving America's competitive position, and inspiring future generations. Ames' missions to accomplish that vision include: 1) performing research to support the American aviation community through the unique integration of computation, experimentation, simulation and flight testing, 2) studying the health of our planet, understanding living systems in space and the origins of the universe, developing technologies for space flight, and 3) to research, develop and deliver information technologies and applications. Information technology may be defined as the use of advance computing systems to generate data, analyze data, transform data into knowledge and to use as an aid in the decision-making process. The knowledge from transformed data can be displayed in visual, virtual and multimedia environments. The decision-making process can be fully autonomous or aided by a cognitive processes, i.e., computational aids designed to leverage human capacities. IT Systems can learn as they go, developing the capability to make decisions or aid the decision making process on the basis of experiences gained using limited data inputs. In the future, information systems will be used to aid space mission synthesis, virtual aerospace system design, aid damaged aircraft during landing, perform robotic surgery, and monitor the health and status of spacecraft and planetary probes. NASA Ames through the Center of Excellence for Information Technology Office is leading the effort in pursuit of revolutionary, IT-based approaches to satisfying NASA's aeronautics and space requirements. The objective of the effort is to incorporate information technologies within each of the Agency's four Enterprises, i.e., Aeronautics and Space Transportation Technology, Earth, Science, Human Exploration and Development of Space and Space Sciences. The end results of these efforts for Enterprise programs and projects should be reduced cost, enhanced mission capability and expedited mission completion.

Kutler, Paul↗

NASA NTRS2007

Anti-Collision Function Design and Performances of the CNES Formation Flying Experiment on the PRISMA Mission

Within the framework of a partnership agreement, EADS ASTRIUM has worked since June 2006 for the CNES formation flying experiment on the PRISMA mission. EADS ASTRIUM is responsible for the anti-collision function. This responsibility covers the design and the development of the function as a Matlab/Simulink library, as well as its functional validation and performance assessment. PRISMA is a technology in-orbit testbed mission from the Swedish National Space Board, mainly devoted to formation flying demonstration. PRISMA is made of two micro-satellites that will be launched in 2009 on a quasi-circular SSO at about 700 km of altitude. The CNES FFIORD experiment embedded on PRISMA aims at flight validating an FFRF sensor designed for formation control, and assessing its performances, in preparation to future formation flying missions such as Simbol X; FFIORD aims as well at validating various typical autonomous rendezvous and formation guidance and control algorithms. This paper presents the principles of the collision avoidance function developed by EADS ASTRIUM for FFIORD; three kinds of maneuvers were implemented and are presented in this paper with their performances.

Cayeux, P.↗

NASA NTRS2008

Pattern-Recognition System for Approaching a Known Target

A closed-loop pattern-recognition system is designed to provide guidance for maneuvering a small exploratory robotic vehicle (rover) on Mars to return to a landed spacecraft to deliver soil and rock samples that the spacecraft would subsequently bring back to Earth. The system could be adapted to terrestrial use in guiding mobile robots to approach known structures that humans could not approach safely, for such purposes as reconnaissance in military or law-enforcement applications, terrestrial scientific exploration, and removal of explosive or other hazardous items. The system has been demonstrated in experiments in which the Field Integrated Design and Operations (FIDO) rover (a prototype Mars rover equipped with a video camera for guidance) is made to return to a mockup of Mars-lander spacecraft. The FIDO rover camera autonomously acquires an image of the lander from a distance of 125 m in an outdoor environment. Then under guidance by an algorithm that performs fusion of multiple line and texture features in digitized images acquired by the camera, the rover traverses the intervening terrain, using features derived from images of the lander truss structure. Then by use of precise pattern matching for determining the position and orientation of the rover relative to the lander, the rover aligns itself with the bottom of ramps extending from the lander, in preparation for climbing the ramps to deliver samples to the lander. The most innovative aspect of the system is a set of pattern-recognition algorithms that govern a three-phase visual-guidance sequence for approaching the lander. During the first phase, a multifeature fusion algorithm integrates the outputs of a horizontal-line-detection algorithm and a wavelet-transform-based visual-area-of-interest algorithm for detecting the lander from a significant distance. The horizontal-line-detection algorithm is used to determine candidate lander locations based on detection of a horizontal deck that is part of the lander.

Huntsberger, Terrance↗