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The Curiosity Rover, currently operating on Mars, contains flight software onboard to autonomously handle aspects of system fault protection. Over 1000 monitors and 39 responses are present in the flight software. Orchestrating these behaviors is the flight software's fault protection engine. In this paper, we discuss the engine's design, responsibilities, and present some lessons learned for future missions.
Since 1984 Marshall Space Flight Center was actively engaged in research and development concerning autonomous power systems. Much of the work in this domain has dealt with the development and application of knowledge-based or expert systems to perform tasks previously accomplished only through intensive human involvement. One such task is the health status monitoring of electrical power systems. Such monitoring is a manpower intensive task which is vital to mission success. The Hubble Space Telescope testbed and its associated Nickel Cadmium Battery Expert System (NICBES) were designated as the system on which the initial proof of concept for intelligent power system monitoing will be established. The key function performed by an engineer engaged in system monitoring is to analyze the raw telemetry data and identify from the whole only those elements which can be considered significant. This function requires engineering expertise on the functionality of the system, the mode of operation and the efficient and effective reading of the telemetry data. Application of this expertise to extract the significant components of the data is referred to as data reduction. Such a function possesses characteristics which make it a prime candidate for the application of knowledge-based systems' technologies. Such applications are investigated and recommendations are offered for the development of intelligent data reduction systems.
An ammonia arcjet capable of throttling between 3 and 10 kW and producing a specific impulse of 600 s is required for the SSTAR flight experiment. Testing was performed to evaluate the performance of two nozzle configurations on ammonia arcjet performance over this power range. One of the objectives of these tests was to quantify the effect small nozzle changes have on performance. The smaller constrictor engine (2.54 mm diameter) produced a specific impulse of about 650 s over the range of 3 to 10 kW at a specific power of 60 kJ/g exceeding the 500-600 s requirement for the SSTAR flight experiment.
Under the Orbital Space Plane Program, NASA is currently pursuing the maturation of technologies via three flight demonstrators - DART (Demonstration of Autonomous Rendezvous Technology), X-37, and PAD (Pad Abort Demonstrator). Flight demonstrators provide the opportunity to test key technologies in their actual working environment. These flight demonstrators are required at this stage to mature technologies needed to support full-scale development design of a future competitively selected Orbital Space.
The amount of autonomy in software engineering tools is increasing as developers build increasingly complex systems. Research in other domains shows that too much or too little trust in autonomous tools can have negative consequences, but we are not aware of any study that has investigated trust in autonomous tools in the highly interactive context of a software engineering workplace. We present the results of a ten week ethnographic case study of engineers collaborating with autonomous tools to write flight software at a large national space exploration organization to support high stakes missions. We find that trust in an autonomous software engineering tool in this setting was influenced by four main factors: the tool’s transparency, social context, an organization’s associated processes, and its usability. We outline theoretical implications for future research into trust in autonomous software engineering tools, and practical implications for tool designers and organizations conducting high stakes work with autonomous tools.
NASA's first autonomous formation flying mission completed its primary goal of demonstrating an advanced technology called enhanced formation flying. To enable this technology, the Flight Dynamics Analysis Branch at the Goddard Space Flight Center implemented a universal 3-axis formation flying algorithm in an autonomous executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm, the onboard flight design and the validation results of this unique system. Results from fully autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon, its ground-based predecessor used in operations, and the original standalone algorithm. Maneuvers discussed encompass reactionary, routine formation maintenance, and inclination control. Orbital data is also examined to verify that all formation flying requirements were met.
VML (Virtual Machine Language) has been used as the sequencing flight software on over a dozen JPL deep-space missions, most recently flying on GRAIL and JUNO. In conjunction with the NASA SBIR entitled "Reactive Rendezvous and Docking Sequencer", VML version 3.0 has been enhanced to include object-oriented element organization, built-in queuing operations, and sophisticated matrix / vector operations. These improvements allow VML scripts to easily perform much of the work that formerly would have required a great deal of expensive flight software development to realize. Autonomous turning and tracking makes considerable use of new VML features. Profiles generated by flight software are managed using object-oriented VML data constructs executed in discrete time by the VML flight software. VML vector and matrix operations provide the ability to calculate and supply quaternions to the attitude controller flight software which produces torque requests. Using VML-based attitude planning components eliminates flight software development effort, and reduces corresponding costs. In addition, the direct management of the quaternions allows turning and tracking to be tied in with sophisticated high-level VML state machines. These state machines provide autonomous management of spacecraft operations during critical tasks like a hypothetic Mars sample return rendezvous and docking. State machines created for autonomous science observations can also use this sort of attitude planning system, allowing heightened autonomy levels to reduce operations costs. VML state machines cannot be considered merely sequences - they are reactive logic constructs capable of autonomous decision making within a well-defined domain. The state machine approach enabled by VML 3.0 is progressing toward flight capability with a wide array of applicable mission activities.
Repeated exposure to +Gz enhances human baroreflex responsiveness and improves tolerance to cardiovascular stress. However, both sustained exposure to +Gx and changes in otolith function resulting from the gravitational changes of space flight and parabolic flight may adversely affect autonomic cardiovascular function and orthostatic tolerance. HYPOTHESES: Baroreflex function and orthostatic tolerance are acutely improved by a single sustained (30 min) exposure to +3Gz but not +3Gx. Moreover, after 30 min of +3Gx, any changes that occur in autonomic cardiovascular function will relate commensurately to changes in otolith function. METHODS: Twenty-two healthy human subjects were first exposed to 5 min of +3 Gz centrifugation and then subsequently up to a total of30 min of either +3Gz (n = 15) or +3Gx (n = 7) centrifugation. Tests of autonomic cardiovascular function both before and after both types of centrifugation included: (a) power spectral determinations of beat-to-beat R-R intervals and arterial pressures; (b) carotid-cardiac baroreflex tests; ( c) Valsalva tests; and (d) 30-min head-up tilt (HUT) tests. Otolith function was assessed during centrifugation by the linear vestibulo-ocular reflex and both before and after centrifugation by measurements of ocular counter-rolling and dynamic posturography. RESULTS: All four +3Gz subjects who were intolerant to HUT before centrifugation became tolerant to HUT after centrifugation. The operational point of the carotid-cardiac baroreflex and the Valsalva-related baroreflex were also enhanced in the +3Gz group but not in the +3Gx group. No significant vestibular-autonomic relationships were detected, other than a significant vestibular-cerebrovascular interaction reported previously. CONCLUSIONS: A single, sustained exposure to +3 Gz centrifugation acutely improves baroreflex function and orthostatic tolerance whereas a similar exposure to +3 Gx centrifugation appears to have less effect.
The COBALT (CoOperative Blending of Autonomous Landing Technology) payload is being developed within NASA as a risk reduction activity to mature, integrate and test ALHAT (Autonomous precision Landing and Hazard Avoidance Technology) systems targeted for infusion into near-term robotic and future human space flight missions. The initial COBALT payload instantiation is integrating the third-generation ALHAT Navigation Doppler Lidar (NDL) sensor, for ultra high-precision velocity plus range measurements, with the passive-optical Lander Vision System (LVS) that provides Terrain Relative Navigation (TRN) global-position estimates. The COBALT payload will be integrated onboard a rocket-propulsive terrestrial testbed and will provide precise navigation estimates and guidance planning during two flight test campaigns in 2017 (one open-loop and closed- loop). The NDL is targeting performance capabilities desired for future Mars and Moon Entry, Descent and Landing (EDL). The LVS is already baselined for TRN on the Mars 2020 robotic lander mission. The COBALT platform will provide NASA with a new risk-reduction capability to test integrated EDL Guidance, Navigation and Control (GN&C) components in closed-loop flight demonstrations prior to the actual mission EDL.
Most navigation systems currently operated by NASA are ground-based, and require extensive support to produce accurate results. Recently developed systems that use Kalman Filter and Global Positioning System (GPS) data for orbit determination greatly reduce dependency on ground support, and have potential to provide significant economies for NASA spacecraft navigation. Current techniques of Kalman filtering, however, still rely on manual tuning from analysts, and cannot help in optimizing autonomy without compromising accuracy and performance. This paper presents an approach to produce a high accuracy autonomous navigation system fully integrated with the flight system. The resulting system performs real-time state estimation by using an Extended Kalman Filter (EKF) implemented with high-fidelity state dynamics model, as does the GPS Enhanced Orbit Determination Experiment (GEODE) system developed by the NASA Goddard Space Flight Center. Augmented to the EKF is a sophisticated neural-fuzzy system, which combines the explicit knowledge representation of fuzzy logic with the learning power of neural networks. The fuzzy-neural system performs most of the self-tuning capability and helps the navigation system recover from estimation errors. The core requirement is a method of state estimation that handles uncertainties robustly, capable of identifying estimation problems, flexible enough to make decisions and adjustments to recover from these problems, and compact enough to run on flight hardware. The resulting system can be extended to support geosynchronous spacecraft and high-eccentricity orbits. Mathematical methodology, systems and operations concepts, and implementation of a system prototype are presented in this paper. Results from the use of the prototype to evaluate optimal control algorithms implemented are discussed. Test data and major control issues (e.g., how to define specific roles for fuzzy logic to support the self-learning capability) are also discussed. In addition, architecture of a complete end-to-end candidate flight system that provides navigation with highly autonomous control using data from GPS is presented.
A document presents a summary of an onboard estimation algorithm now being used to calibrate the alignment of the Spitzer Space Telescope (formerly known as the Space Infrared Telescope Facility). The algorithm, denoted the S2P calibration filter, recursively generates estimates of the alignment angles between a telescope reference frame and a star-tracker reference frame. At several discrete times during the day, the filter accepts, as input, attitude estimates from the star tracker and observations taken by the Pointing Control Reference Sensor (a sensor in the field of view of the telescope). The output of the filter is a calibrated quaternion that represents the best current mean-square estimate of the alignment angles between the telescope and the star tracker. The S2P calibration filter incorporates a Kalman filter that tracks six states - two for each of three orthogonal coordinate axes. Although, in principle, one state per axis is sufficient, the use of two states per axis makes it possible to model both short- and long-term behaviors. Specifically, the filter properly models transient learning, characteristic times and bounds of thermomechanical drift, and long-term steady-state statistics, whether calibration measurements are taken frequently or infrequently. These properties ensure that the S2P filter performance is optimal over a broad range of flight conditions, and can be confidently run autonomously over several years of in-flight operation without human intervention.
Next generation aviation flight control concepts require autonomous and intelligent control system architectures that close control loops directly around payload sensors in manner more integrated and cohesive that in traditional autopilot designs. Research into payload directed flight control at NASA Ames Research Center is investigating new and novel architectures that can satisfy the requirements for next generation control and automation concepts for aviation. Tighter integration between sensor and machine requires definition of specific sensor-directed control modes to tie the sensor data directly into a vehicle control structures throughout the entire control architecture, from low-level stability- and control loops, to higher level mission planning and scheduling reasoning systems. Payload directed flight systems can thus provide guidance, navigation, and control for vehicle platforms hosting a suite of onboard payload sensors. This paper outlines related research into the field of payload directed flight; and outlines requirements and operating concepts for payload directed flight systems based on identified needs from the scientific literature.'
NASA's first autonomous formation flying mission completed its primary goal of demonstrating an advanced technology called Enhanced Formation Flying. To enable this technology, a team at the Goddard Space Flight Center implemented a universal 3-axis formation flying algorithm in an autonomous executive flight code onboard the New Millennium Program's (NMP) Earth Observing-1 (EO-1) spacecraft. This paper describes the mathematical background of the autonomous formation flying algorithm, the onboard flight design and the validation results of this unique system. Results from fully autonomous maneuver control are presented as comparisons between the onboard EO-1 operational autonomous control system called AutoCon(trademark), its ground-based predecessor used in operations, and the original standalone algorithm. Maneuvers discussed encompass reactionary, routine formation maintenance, and inclination control. Orbital data is also examined to verify that all formation flying requirements were met.
NASA, in partnership with AeroVironment and Aerostar, recently demonstrated a first-of-its-kind air traffic management concept that could pave the way for aircraft to safely operate at higher altitudes. This work seeks to open the door for increased internet coverage, improved disaster response, expanded scientific missions, and even supersonic flight. The concept is referred to as an Upper-Class E traffic management, or ETM. NASA and its partners have developed an ETM traffic management system that allows aircraft to autonomously share location and flight plans, enabling aircraft to stay safely separated. This concept was demonstrated during the recent traffic management simulation in the Airspace Operations Laboratory at Ames, data from multiple air vehicles was displayed across dozens of traffic control monitors and shared with partner computers off site. The study details and the initial results are presented at a regular, informal ETM industry meetings held virtually.
As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight frameworks is paramount for establishing an effective architecture for autonomous systems. Hardware test flights are time-consuming and cost prohibitive during early system design and development. Simulation environments can be useful tools to accelerate algorithm development and testing. However, transitions from simulation to flight (sim-to-flight) can be challenging, unless systems are designed with this transition in mind and with the necessary capabilities built into the architecture and framework. One of the objectives of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. ATTRACTOR’s objective was to construct computational concepts of trustworthiness and justifiable trust in multi-agent autonomous teams, to inform future certification of safety-critical and time-critical autonomous systems in aviation. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation (ModSim) environment for test and evaluation of autonomous systems. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single-and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. The Autonomous Entity Operational Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications, enabling sim-to-flight with minimal configuration changes. Using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.
A second generation, compact, real-time, air-cooled 3-D imaging Flash Lidar sensor system, developed from a number of cutting-edge components from industry and NASA, is lab characterized and helicopter flight tested under the Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT) project. The ALHAT project is seeking to develop a guidance, navigation, and control (GN&C) and sensing system based on lidar technology capable of enabling safe, precise crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The Flash Lidar incorporates a 3-D imaging video camera based on Indium-Gallium-Arsenide Avalanche Photo Diode and novel micro-electronic technology for a 128 x 128 pixel array operating at a video rate of 20 Hz, a high pulse-energy 1.06 μm Neodymium-doped: Yttrium Aluminum Garnet (Nd:YAG) laser, a remote laser safety termination system, high performance transmitter and receiver optics with one and five degrees field-of-view (FOV), enhanced onboard thermal control, as well as a compact and self-contained suite of support electronics housed in a single box and built around a PC-104 architecture to enable autonomous operations. The Flash Lidar was developed and then characterized at two NASA-Langley Research Center (LaRC) outdoor laser test range facilities both statically and dynamically, integrated with other ALHAT GN&C subsystems from partner organizations, and installed onto a Bell UH-1H Iroquois "Huey" helicopter at LaRC. The integrated system was flight tested at the NASA-Kennedy Space Center (KSC) on simulated lunar approach to a custom hazard field consisting of rocks, craters, hazardous slopes, and safe-sites near the Shuttle Landing Facility runway starting at slant ranges of 750 m. In order to evaluate different methods of achieving hazard detection, the lidar, in conjunction with the ALHAT hazard detection and GN&C system, operates in both a narrow 1deg FOV raster-scanning mode in which successive, gimbaled images of the hazard field are mosaicked together as well as in a wider, 4.85deg FOV staring mode in which digital magnification, via a novel 3-D superresolution technique, is used to effectively achieve the same spatial precision attained with the more narrow FOV optics. The lidar generates calibrated and corrected 3-D range images of the hazard field in real-time and passes them to the ALHAT Hazard Detection System (HDS) which stitches the images together to generate on-the-fly Digital Elevation Maps (DEM's) and identifies hazards and safe-landing sites which the ALHAT GN&C system can then use to guide the host vehicle to a safe landing on the selected site. Results indicate that, for the KSC hazard field, the lidar operational range extends from 100m to 1.35 km for a 30 degree line-of-sight angle and a range precision as low as 8 cm which permits hazards as small as 25 cm to be identified. Based on the Flash Lidar images, the HDS correctly found and reported safe sites in near-real-time during several of the flights. A follow-on field test, planned for 2013, seeks to complete the closing of the GN&C loop for fully-autonomous operations on-board the Morpheus robotic, rocket-powered, free-flyer test bed in which the ALHAT system would scan the KSC hazard field (which was vetted during the present testing) and command the vehicle to landing on one of the selected safe sites.
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The NASA Goddard Space Flight Center is working to develop a revolutionary new system architecture concept in support of fully autonomous missions. As part of GSFC's contribution to the New Millenium Program (NMP) Space Technology 7 Autonomy and on-Board Processing (ST7-A) Concept Definition Study, the system incorporates the latest commercial Internet and software development ideas and extends them into NASA ground and space segment architectures. The unique challenges facing the exploration of remote and inaccessible locales and the need to incorporate corresponding autonomy technologies within reasonable cost necessitate the re-thinking of traditional mission architectures. A measure of the resiliency of this architecture in its application to a broad range of future autonomy missions will depend on its effectiveness in leveraging from commercial tools developed for the personal computer and Internet markets. Specialized test stations and supporting software come to past as spacecraft take advantage of the extensive tools and research investments of billion-dollar commercial ventures. The projected improvements of the Internet and supporting infrastructure go hand-in-hand with market pressures that provide continuity in research. By taking advantage of consumer-oriented methods and processes, space-flight missions will continue to leverage on investments tailored to provide better services at reduced cost. The application of ground and space segment architectures each based on Local Area Networks (LAN), the use of personal computer-based operating systems, and the execution of activities and operations through a Wide Area Network (Internet) enable a revolution in spacecraft mission formulation, implementation, and flight operations. Hardware and software design, development, integration, test, and flight operations are all tied-in closely to a common thread that enables the smooth transitioning between program phases. The application of commercial software development techniques lays the foundation for delivery of product-oriented flight software modules and models. Software can then be readily applied to support the on-board autonomy required for mission self-management. An on-board intelligent system, based on advanced scripting languages, facilitates the mission autonomy required to offload ground system resources, and enables the spacecraft to manage itself safely through an efficient and effective process of reactive planning, science data acquisition, synthesis, and transmission to the ground. Autonomous ground systems in turn coordinate and support schedule contact times with the spacecraft. Specific autonomy software modules on-board include mission and science planners, instrument and subsystem control, and fault tolerance response software, all residing within a distributed computing environment supported through the flight LAN. Autonomy also requires the minimization of human intervention between users on the ground and the spacecraft, and hence calls for the elimination of the traditional operations control center as a funnel for data manipulation. Basic goal-oriented commands are sent directly from the user to the spacecraft through a distributed internet-based payload operations "center". The ensuing architecture calls for the use of spacecraft as point extensions on the Internet. This paper will detail the system architecture implementation chosen to enable cost-effective autonomous missions with applicability to a broad range of conditions. It will define the structure needed for implementation of such missions, including software and hardware infrastructures. The overall architecture is then laid out as a common thread in the mission life cycle from formulation through implementation and flight operations.