Fault Protection
Fault protection is the onboard logic that detects an anomalous condition and puts the vehicle into a state from which the ground can recover it.
The problem
Section titled “The problem”Fault protection has to act without the ground, because light time is often longer than the time to criticality on a deep space mission, and because safe mode is not a usable response during orbit insertion or landing, where entering it forfeits the event [17]. On a rover the cost of a false trip is measured in sols of lost driving, and the cost of a missed detection is the vehicle [4][2]. The environment adds constraints: the rovers must hold thermal stability and energy balance between once-per-sol command opportunities [2], and Curiosity is power-negative whenever its prime computer is awake, so a safe state has to be a schedule of sleep and communication rather than a quiescent configuration [3].
The vocabulary comes from the dependability literature: a fault is the cause, an error the corrupted state it produces, and a failure the deviation of delivered service, and fault tolerance divides into error detection and recovery [18]. The lineage of the flown approach starts with the JPL-STAR computer of the 1960s, a laboratory breadboard that contrasted massive redundancy with selective, replacement redundancy and defined detection, isolation and recovery as separate functions; it was never flown [19]. Growth in flight software size is the pressure behind the designs that followed. The NASA study of flight software complexity found that fault protection and autonomy received little attention in education and recommended treating them as architectural rather than add-on concerns [20].
What has flown
Section titled “What has flown”Monitor and response engines: MER, MSL, Mars 2020
Section titled “Monitor and response engines: MER, MSL, Mars 2020”Distributed monitors report to a central engine that activates hard-coded responses by priority. MER put autonomous behaviors into flight software logic rather than command sequences, which removed the separation between nominal operation and fault protection [10]. MSL and Mars 2020 flew the engine pattern [1][9], and Psyche inherits it from Soil Moisture Active Passive with one nominal mode and three tiers of safe mode, where fault protection may demote modes and only the ground may promote them [12]. It is the only family with surface flight history on a rover.
The MSL implementation separates detection from action [1]. A monitor carries a persistence count, so a single erroneous reading does not provoke a response, and passes through four telemetered states: black for no data yet, green for good data, yellow for erroneous data persisting long enough to run a local response, and red for erroneous data persisting long enough that the system engine must act. Once red, a monitor latches red until it is reset, even if good data arrives. The engine polls once per second: it checks which monitors have just turned red, looks up the associated responses in a hard-coded table, runs the highest priority one (aborting a lower priority response at a step boundary), and on completion clears every monitor associated with that response [1].
Latching is what makes polling sound: a monitor that could move between red and green on its own would let a fast transient slip between polls [1]. The cost is that the engine acts on the first highest priority response it examines, not the monitor that tripped first chronologically, which is more likely to be the root cause. Priority is hard-coded and ordered by hardware dependency, with flight software examination order as the implicit tiebreak, and aborts are allowed at any step boundary, accepting that the full space of abort locations cannot be tested [1]. The ground can disable the response tied to a specific monitor, but cannot disable a response outright, and responses can dead-end themselves after a set number of runs [1]. MER responses likewise drove the vehicle to a single safe configuration rather than a per-fault state [2].
Safe state design
Section titled “Safe state design”MER autonomous shutdown puts the CPU to sleep when no communication window is active and the solar array cannot support the load. Wakeup comes from the alarm clock in the always-powered FPGA, or from solar wakeup declared after array current exceeds 2.0 A for more than 10 minutes and at least 16 hours have passed since the last one [2]. Resets, thermal faults, power faults and loss of uplink all use this path, and the flight software arbitrates between them: a low battery event shuts the rover down immediately, and uplink loss begins executing UHF windows only after several days without ground contact [2].
Curiosity’s safing interleaves sleep that recharges the batteries with communication windows timed to orbiter overflights, stored in non-volatile memory on both computers so safing survives an autonomous computer swap, plus a hail mode in which the Electra-Lite radio stays powered and wakes the rover on an orbiter hail [31]. In safe mode the rover follows system fault protection windows, a preset schedule of antenna, telecommunication configuration and solar time [3]. X-band windows are receive-only through the low gain antenna at 7.8125 bps, chosen because it works with corrupted mechanism position knowledge; UHF windows through the relay orbiters are the only source of actionable telemetry [3]. The design was optimized for landing-day conditions and needs periodic manual adjustment as Earth rise drifts, and at the time of its publication flight experience was two safing events in 342 sols [31].
Mobility faults
Section titled “Mobility faults”Curiosity’s drive faults are threshold-plus-persistence tests on quantities that visual odometry supplies. Excessive slip faults when a slow limit is exceeded on a set number of contiguous updates [5]. On sol 2434 the visual odometry failure ceiling was set to 10 in anticipation of feature-poor terrain, and the eleventh failure stopped the drive 2.82 m short of predicted odometry. Suspension angle limits fault independently, with an 18 degree limit on the right bogie [6], and on sol 1789 78.3 percent wheel slip in cohesionless sand drove the heading past the yaw limit and stopped the drive early [5]. Traction control introduced exactly one new fault type, a per-drive-step timeout, and one of the first 146 nominal-use drives ended on it: sol 1786 faulted after 15.86 m of a planned 27.9 m when a 32.77 s timeout expired with the right rear wheel on a large rock [6].
Operators trade fault protection against progress when the failure is understood. On Perseverance sol 1347, after 34 visual odometry failures over three drives at Lookout Hill, rover planners disabled the standard visual odometry failure fault protection and hand-sequenced a slip check requiring visual odometry to succeed only once every 20 m, justified by the mechanical specification that the vehicle can extract itself after 20 m of motion and by firm terrain [7].
Flight case histories
Section titled “Flight case histories”Spirit flash memory, sol 18. A flash file system table of contents retained entries for every file that had ever existed and grew unbounded until it consumed all available RAM. The out-of-memory condition silently suspended a critical task, which blocked the shutdown algorithm from powering off the CPU, so the system reset on the delayed reset timer and again on every reboot. Crippled mode, which does not mount flash, stopped the loop. Two weeks after the first symptoms the anomaly team reformatted flash, and a new flight software load fixed the deleted-file representation [2].
Cruise solar flare, 28 October 2003. Both rovers lost attitude knowledge and dropped out of nominal attitude control [2]; Mars Odyssey detected corrupted RAM from the same storm. The alarm clock triggered wakeup and operations commanded both spacecraft back to three-axis control [2].
Opportunity stuck-on heater. A failed-on heater switch on an instrument deployment device joint drew 0.5 A overnight, costing 180 Wh per night [2]. The fix was deep sleep, a flight software change that removes the batteries from the power bus at night [2]. Deep sleep later thermally cycled the miniTES below its allowable limit, which led to a software change that introduced the vulnerability behind miniTES resets, and on sol 628 a dust storm delayed the battery charge board wakeup past a scheduled alarm [4].
Curiosity sol 200. The anomaly cost 16 hours from first notification to recovery of the shutdown capability by hardware commands swapping to the backup computer; a hang prevented autonomous safe mode entry [3].
Perseverance sol 390. A flight software fatal put the rover in safe mode on the first sol of a three-sol weekend plan, precluding drives on sols 391 and 392, with sol 393 spent on recovery and sol 394 on imagery to plan the next drive [8].
Cassini, 2012. The original attitude-control logic could swap thruster branches only once, so a leak on the B branch in a mixed A and B configuration would never be isolated [30]. Version A8.9.0 allows a second swap at tier 7, chosen over two more capable options because it needed the least code change and testing; ground testing found two defects that were accepted rather than fixed, and the software was uplinked in December 2012 with no on-orbit behavior reported [30].
Curiosity drill feed, sol 1536, and InSight mole. The drill feed motor stalled at current limit with no encoder motion. Eighteen months of flight diagnostics and bench work localized a high-friction zone about one third of a motor revolution wide, no root cause was established, and the project drove the feed to full extension while semi-operable, with feed-extended drilling collecting its first sample on sol 2057, 521 sols after the stall [25]. For the InSight HP3 mole stall, a testbed campaign ran from the sol 87 frangibolt firing to the end of recovery at sol 754, with simulant results that the authors state do not replicate Martian regolith [32].
Cost of anomalies
Section titled “Cost of anomalies”On MER, anomaly recovery consumed less than 5 percent of surface time, about 30 sols out of 700 per vehicle, which the authors attribute to the same operational design that lets a driving error be recovered in a single day [4]. A catalog of 48 major anomalies (four or more consecutive sols of lost progress) across Spirit, Opportunity, Phoenix, Curiosity, InSight and Perseverance puts the average loss at 11 percent of prime mission duration, 6.6 percent over the full mission, with an average anomaly of 15 sols and a P95 of 45 sols [24]. Not every fault reaches the engine: the ordinary MER case is a sequence that did not produce the intended result, handled by replanning in the next tactical plan [4].
What is being tried now
Section titled “What is being tried now”Verification campaigns (ground-tested, applied to flight projects). Exhaustive testing is impossible, so campaigns bound the problem. Mars 2020 derived more than 400 scenario-based test cases from thousands of analyzed faults, prioritized a minimal set of 150, and executed 265 across all test venues using a shared fault injection library and a catalog of expected event records per response [11]. Psyche scoped a few thousand failure modes, about 650 monitors and 185 responses against 176 end-to-end test cases, of which 76 had run when the launch slipped [13]. The extra year found attitude and rate monitors whose thresholds, sized to tolerate slews, were also active during static pointing, and an engine hang during a compute element swap [13]. A parallel failure modes analysis found 147 unrecorded failure modes and flagged about 33 percent of roughly 140 GNC monitors for possible update [12]. Psyche’s payload design is constrained by spacecraft responses limited to power off and wait for the ground; the imager has no internal fault detection, and the DSOC terminal’s FMECA produced about ten monitors that are mostly masked during operations [27].
Plan-level validation (prototype). ARTcritic validates Europa Clipper’s nominal command sequence jointly with its Activity Restart Timeline against injected processor-reset faults, and found latent sensitivities in two scenarios that were fixed by shifting restart transitions. It ran on an excerpt of the spacecraft model with exaggerated resource limits, so no result reflects flight margins [29].
Goal-based and model-based control. The Mission Data System architecture commands goals, constraints on a state over an interval, so a failed goal is contained by the module that owns the parent goal and fault protection is not a separate system [14]. Rasmussen argues the same case from control fundamentals [15]. Model-based diagnosis reasons from explicit component models, with Mars Polar Lander’s premature engine shutdown at about 40 m after a latched leg-sensor transient as the standard motivating case [16]. Remote Agent, which flew on Deep Space 1, carried a mode identification and recovery module in this family [21]. A 2017 JPL panel described system-wide model-based reasoning as the intended successor to symptom-to-suspect rules, with two SBIR tool efforts still in development [22]. For assurance, a JPL task ran over 7 million archived ASTERIA CubeSat telemetry points through the MONSID diagnostic engine, finding no false detections on the star tracker model and false positives on the coarse sun sensor traced to tuned parameters and an incomplete model; the flight demonstration was a plan, not a result [28]. None of the sources in this family reports a rover flight [14][15][16][22].
Learned anomaly detection (flight data, offline). Undercomplete autoencoders flagged Curiosity straight-drive anomalies from 8 Hz mobility telemetry on sols 3815 to 3934 over 850 m, with 6 and 11 flags for the two variants, none judged hazardous by the mobility team [26]. It runs on downlinked data and is not part of the onboard engine.
Autonomy risk. A risk paper on autonomy software argues that added autonomy brings state-space discontinuity and reduced situational awareness, and proposes a risk identification table without implementation or flight data [23].
The numbers
Section titled “The numbers”| Element | Definition | Count on MSL |
|---|---|---|
| Monitor | software that detects an anomalous situation, sited near the module that knows the device | over 1000 [1] |
| Local response | code inside the monitor’s module, correcting the issue with a small part of the system | not enumerated [1] |
| System response | code invoked by the engine, typically calling multiple modules | 39 [1] |
| Epoch | Safe mode communication per sol | State of charge gain per sol |
|---|---|---|
| At landing | 9 Martian hours [3] | 22 percent [3] |
| As of 2023 | 6.6 hours [3] | 5.5 percent [3] |
| Campaign or catalog | Figure |
|---|---|
| Mars 2020 test cases identified, minimal set, executed | over 400, 150, 265 [11] |
| Psyche end-to-end test cases, run at launch slip | 176, 76 [13] |
| MER time in anomaly recovery | under 5 percent, about 30 of 700 sols [4] |
| Major Mars surface anomalies, mean and P95 duration | 48, 15 sols and 45 sols [24] |
| Time lost, prime mission and full mission | 11 percent and 6.6 percent [24] |
| Curiosity sol 200 recovery of shutdown capability | 16 hours [3] |
| Drill feed stall to first feed-extended sample | 521 sols [25] |
What is not established
Section titled “What is not established”The rover engine papers are design descriptions. The MSL paper gives no count of monitors that tripped in flight, no response statistics and no CPU cost for polling over more than 1000 monitors, and its claim that the engine is reusable with table changes is an assertion [1]. The MER fault protection paper gives no verification data, monitor count or detection latency [9]. The 5 percent recovery figure for MER is one aggregate with no definition of a recovery sol, reported by the team it measures [4]. The 48-anomaly catalog is a linear fit through six heterogeneous missions dominated by MSL, with no uncertainty on any rate [24].
The validation papers report effort, not adequacy: no coverage fraction against the fault population exists for Mars 2020 or Psyche [11][12][13], and Psyche’s payload paper reports no latency, test counts or defect counts [27]. The drill feed root cause was never established [25]. No source compares a goal-based or model-based design against a monitor and response design on the same anomaly, and neither has a rover flight record [14][15][16]. Fault detection coverage, false trip rates and time to criticality for any flown rover are not published in the sources cited here.
References
- Benowitz, E. (2015). The Curiosity Mars Rover's Fault Protection Engine
. IEEE International Conference on Space Mission Challenges for Information Technology. Source
BibTeX
@inproceedings{benowitz2015curiosity, title = {The Curiosity Mars Rover's Fault Protection Engine}, author = {Benowitz, Ed}, booktitle = {IEEE International Conference on Space Mission Challenges for Information Technology}, volume = {111}, pages = {62-66}, address = {Big Sky, Montana}, year = {2015}, doi = {10.1109/smc-it.2014.16}, abstract = {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 behaviorsis 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.} } - Neilson, T. (2005). Mars Exploration Rovers Surface Fault Protection
. IEEE International Conference on Systems, Man and Cybernetics. Source
BibTeX
@inproceedings{neilson2005mars, title = {Mars Exploration Rovers Surface Fault Protection}, author = {Neilson, Tracy}, booktitle = {IEEE International Conference on Systems, Man and Cybernetics}, volume = {1}, pages = {14-19}, address = {Big Sky, Montana}, year = {2005}, doi = {10.1109/icsmc.2005.1571115}, abstract = {The Mars exploration rovers surface fault protection design was influenced by the need for the solar powered rovers to recharge their batteries during the day to survive the night. The rovers were required to autonomously maintain thermal stability, and initiate reliable communication with orbiting assets or directly to Earth, while maintaining their energy balance. This paper describes the system fault protection design for the surface phase of the mission, including hardware descriptions and software algorithms. Additionally, a few in-flight experiences are described, including the Spirit flash memory anomaly and the Opportunity "stuck-on" heater failure.} } - Rink, K., Boehmer, R., Kaplan, K., Larsen, R., Clark, J. and Neilson, T. (2023). Martian Mayday: The Evolution of Curiosity's Safe Mode Communication Over Ten Years
. IEEE Aerospace Conference. Source
BibTeX
@inproceedings{rink2023martian, title = {Martian Mayday: The Evolution of Curiosity's Safe Mode Communication Over Ten Years}, author = {Rink, Kimberly and Boehmer, Rudy and Kaplan, Kyle and Larsen, Reidar and Clark, Jessica and Neilson, Tracy}, booktitle = {IEEE Aerospace Conference}, pages = {1-12}, address = {Big Sky, Montana}, year = {2023}, doi = {10.1109/aero58975.2024.10521326}, abstract = {When the Curiosity Mars rover encounters a serious fault, it enters a configuration called safe mode. Curiosity’s autonomous safe mode behavior must keep the rover communicative and stable until the operations team can triage the issue and send recovery commands. In safe mode, Curiosity follows a preset schedule of windows that specify the antenna, telemetry for transmission, and solar time of each communication opportunity. The timing of these windows, called system fault protection (SFP) windows, is crucial for Curiosity to maintain both communication and power-positivity, or generating more energy that consumed. Not only do SFP windows dictate when Curiosity attempts to communicate over its ultra-high frequency and X-band radios, they also largely control the rover’s power consumption by dictating when its primary computer powers on and off, known as awake and sleep states. Because Curiosity is power-negative when awake, sleep time is necessary to charge its batteries to a higher state of charge than the previous sol, or Martian day.During Curiosity’s prime mission, fault protection engineers regularly updated SFP windows to accommodate changing Mars relay orbits and relative geometry of Earth and Mars. The initial SFP windows at landing directed Curiosity to stay awake for nine Martian hours of communication each sol. This design allowed enough sleep time for Curiosity to increase the state of charge of its batteries by 22% over a single sol in safe mode. But as the mission progressed, updates to SFP windows were additionally driven by Curiosity’s aging power source, which continuously requires increased sleep time to maintain power-positivity. As of 2023, 6.6 hours of safe mode communication per sol will only increase the battery state of charge by 5.5%. Secondary factors that were not present during Curiosity’s prime mission—including changing uplink strategies and Mars relay infrastructure—have introduced new challenges to updating SFP windows. The process of selecting SFP window times has evolved into an iterative analysis that must consider several dynamic operational factors to achieve a balance of communication time and power consumption. By using this analysis to converge on a design that satisfies energy requirements and desired communication opportunities, fault protection engineers ensure Curiosity’s safe mode configuration in its extended mission remains truly safe. This paper discusses how Curiosity uses SFP windows to communicate in safe mode, the factors that influence how SFP windows are designed, and how both the design process and the windows themselves have changed over ten years of surface operations.} } - Matijevic, J. and Dewell, E. (2005). Anomaly Recovery and the Mars Exploration Rovers
. SpaceOps Conference. Source
BibTeX
@inproceedings{matijevic2005anomaly, title = {Anomaly Recovery and the Mars Exploration Rovers}, author = {Matijevic, Jacob and Dewell, Emily}, booktitle = {SpaceOps Conference}, year = {2005}, doi = {10.2514/6.2006-5957}, abstract = {The premise of the design of operations for the Mars Exploration Rovers (MER) is that the vehicles will drive each day. As a result, they will encounter some aspect of the terrain environment that cannot be anticipated or otherwise accommodated by the sequences linked onboard that day. The operations team then must correct the problem by planning then commanding the execution of a different drive the next day. Often other aspects of the operation on the surface of Mars: environmental changes, component degradation, errors in sequence design or execution, etc., lead to anomalies which must be addressed before normal operations can resume. The operational design that makes it possible to recover from a driving error each day also reduces the time needed to recover from anomalies. As an example of the efficiency achieved, less than 5% (about 30 sols out of 700 sols of operations) of the time on the surface has been devoted to recovery from anomalies for each vehicle. In this paper the major anomalies experienced by the MER rovers will be recounted and the streamlined approaches to addressing these problems described. The operational flexibility developed for these missions is also a function of the system design that anticipated a number of likely faults and conditions arising from uncertainty in sequence execution and environmental change. This design will be described as well as the considerations in operation that motivated this design. These considerations will likely be present in any future surface mission.} } - Rankin, A., Maimone, M., Biesiadecki, J., Patel, N., Levine, D. and Toupet, O. (2021). Mars Curiosity Rover Mobility Trends During the First Seven Years
. Journal of Field Robotics, 5. Source
BibTeX
@article{rankin2021mars, title = {Mars Curiosity Rover Mobility Trends During the First Seven Years}, author = {Rankin, Arturo and Maimone, Mark and Biesiadecki, Jeffrey and Patel, Nikunj and Levine, Dan and Toupet, Olivier}, journal = {Journal of Field Robotics}, volume = {38}, number = {5}, pages = {759--800}, year = {2021}, doi = {10.1002/rob.22011}, abstract = {Abstract NASA's Mars Science Laboratory (MSL) Curiosity rover landed on Mars on August 6, 2012. In the 7 years between landing and August 6, 2019 (sol 2488), Curiosity has driven 21,318.5 m over a variety of terrain types and slopes, employing multiple drive modes with varying amounts of onboard autonomy. Curiosity's drive distances each sol have ranged from its shortest drive of 2.6 cm to its longest drive of 142.5 m, with an average drive distance of 28.9 m. Real‐time human intervention is not possible during Curiosity's drives due to the latency in uplinking commands and downlinking telemetry. Instead, the operations team relies on Curiosity's fault protection, autonomous navigation, and visual odometry software to keep the rover safe during drives. During its first 7 years on Mars, Curiosity has attempted 738 drives. While 622 drives ran to completion, 116 drives were prevented or stopped early by Curiosity's fault protection software. The primary risks to mobility success have been wheel damage, wheel entrapment, progressive wheel sinkage, and the potential for hardware or cable failures that result in an inability to command one or more steer or drive actuators. In this paper, we describe Curiosity's mobility subsystem, mobility trends over the first 21.3 km of the mission, operational aspects of mobility fault protection, risks to continued mobility success, and risk mitigation strategies.} } - Toupet, O., Biesiadecki, J., Rankin, A., Steffy, A., Meirion-Griffith, G., Levine, D., Schadegg, M. and Maimone, M. (2020). Traction Control on the Curiosity Mars Rover: Algorithm and Flight Results
. Journal of Field Robotics. Source
BibTeX
@article{toupet2020traction, title = {Traction Control on the Curiosity Mars Rover: Algorithm and Flight Results}, author = {Toupet, Olivier and Biesiadecki, Jeffrey and Rankin, Arturo and Steffy, Amanda and Meirion-Griffith, Gareth and Levine, Dan and Schadegg, Maximilian and Maimone, Mark}, journal = {Journal of Field Robotics}, year = {2020}, doi = {10.48577/jpl.hkzuqs}, abstract = {No abstract available.} } - Maimone, M., Verma, V., Rankin, A., Kaplan, K., Carsten, J., Schaler, E., Boroson, E., Graser, E., Srinivasan, T., Nash, J. and Chiu, D. (2026). Roving on the Edge: Robotic Operations Power Perseverance's Ascent of Jezero Crater Rim
. Annual AAS Guidance, Navigation and Control Conference. Source
BibTeX
@inproceedings{maimone2026roving, title = {Roving on the Edge: Robotic Operations Power Perseverance's Ascent of Jezero Crater Rim}, author = {Maimone, Mark and Verma, Vandi and Rankin, Arturo and Kaplan, Kyle and Carsten, Joseph and Schaler, Ethan and Boroson, Elizabeth and Graser, Evan and Srinivasan, Thirupathi and Nash, Jeremy and Chiu, Darwin}, booktitle = {Annual AAS Guidance, Navigation and Control Conference}, year = {2026}, url = {https://www-robotics.jpl.nasa.gov/media/documents/2026_RO_AAS_final.pdf} } - Rankin, A., Del Sesto, T., Hwang, P., Justice, H., Maimone, M., Verma, V. and Graser, E. (2023). Perseverance Rapid Traverse Campaign
. IEEE Aerospace Conference. Source
BibTeX
@inproceedings{rankin2023perseverance, title = {Perseverance Rapid Traverse Campaign}, author = {Rankin, Arturo and Del Sesto, Tyler and Hwang, Pauline and Justice, Heather and Maimone, Mark and Verma, Vandi and Graser, Evan}, booktitle = {IEEE Aerospace Conference}, pages = {1-16}, address = {Big Sky, Montana}, year = {2023}, doi = {10.1109/aero55745.2023.10115835}, abstract = {Over the first 13 months of the Mars 2020 mission, the Perseverance rover traversed nearly 5 km along the Jezero Crater floor. Near the end of that period, the Science team was anxious to relocate to the ancient Delta region near the crater rim, over 5 km away. A Rapid Traverse Campaign was planned that would prioritize use of Perseverance's autonomous navigation software to drive at an unprecedented high pace and minimize science activities. The Rapid Traverse Campaign started in March 2022 and lasted 31 Martian days. During the campaign, Perseverance drove over 5 km in 24 drives, during which its autonomy software planned 94.8% of its overall driving, enabling it to set several new planetary rover driving records. Perseverance exceeded the longest daily drive distance record achieved by a previous planetary rover (219 meters) 11 times and set new records for the longest multi-sol drive distance in a single plan (528.7 meters) and the longest continuation drive (699.9 meters) by operating without human drive path input during 3 sols of driving. This paper details the planning and execution of the Rapid Traverse Campaign.} } - Neilson, T. (2005). MER on-board surface fault protection
. IEEE Aerospace Conference. Source
BibTeX
@inproceedings{neilson2005mer, title = {MER on-board surface fault protection}, author = {Neilson, Tracy}, booktitle = {IEEE Aerospace Conference}, publisher = {JPL Open Repository}, year = {2005}, url = {https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=hdl:2014/38695} } - Reeves, G. E. (2005). An Overview of the Mars Exploration Rovers Flight Software
. IEEE International Conference on Systems, Man and Cybernetics. Source
BibTeX
@inproceedings{reeves2005overview, title = {An Overview of the Mars Exploration Rovers Flight Software}, author = {Reeves, Glenn E.}, booktitle = {IEEE International Conference on Systems, Man and Cybernetics}, volume = {1}, pages = {1-7}, address = {Waikoloa, Hawaii}, year = {2005}, doi = {10.1109/icsmc.2005.1571113}, abstract = {The Mars exploration rovers (MER) flight software (FSW) is possibly the most complex software implementation to be deployed on another planet. The requirements dictated a software system that addressed four distinct mission phases (cruise, landing, egress, and surface) and the mission demanded a system with significant autonomy. The structure of the MER flight software reflects its object-oriented beginnings and the overall function reflects the requirements of the MER mission and spacecraft. This paper provides an overview of the function and structure of the MER flight software. The MER mission and spacecraft are briefly discussed to provide context for the flight software decomposition and the discussion of the software execution model.} } - Clark, J. J., Lam, M., DuCharme, L., Lumnah, A. and Morantz, C. (2022). Validation of the Mars 2020 Fault Protection Design: Navigating the Infinity of the Off-Nominal
. IEEE Aerospace Conference. Source
BibTeX
@inproceedings{clark2022validation, title = {Validation of the Mars 2020 Fault Protection Design: Navigating the Infinity of the Off-Nominal}, author = {Clark, Jessica J and Lam, Mary and DuCharme, Lauren and Lumnah, Alex and Morantz, Chaz}, booktitle = {IEEE Aerospace Conference}, pages = {1-8}, publisher = {IEEE}, year = {2022}, doi = {10.1109/aero53065.2022.9843661}, abstract = {On July 30th 2020, the Mars 2020 mission successfully launched out of Cape Canaveral, Florida, passed through the Earth's shadow, and began its short cruise to Mars. Less than seven months later, the Perseverance rover touched down safely in Jezero Crater to begin its ambitious mission that includes looking for signs of ancient life and collecting samples for future return to Earth. Getting to the successful landing, or “Tango Delta Nominal,” could not have been achieved without also considering the off-nominal. One of the teams supporting this ambitious mission is the fault protection (FP) team. This team is tasked with assessing the various failures, or faults, that could prevent mission success and with ensuring that the autonomous behaviors built into the software and hardware can detect faults and recover the vehicle to a safe state. As part of its charter, the FP team designed a test campaign to provide confidence in the system's robustness to off-nominal scenarios across all of Mars 2020's mission phases. The greatest challenge associated with designing such a validation campaign was reducing the infinite number of anomalous scenarios into a finite test suite. In addition, the tests needed to be executed efficiently in order to utilize the team's limited test venue access, but still needed to maintain a level of rigor that guaranteed confidence in the test outcomes. Given that each test scenario generated massive amounts of data, the team also developed methods for quickly ascertaining whether the autonomous fault protection behaviors maintained vehicle safety in the presence of an anomaly. This paper summarizes the processes that the Mars 2020 fault protection team employed to execute its off-nominal validation campaign. It captures both the methods of generating a suite of off-nominal tests, as well as reducing it to a subset that can be realistically executed within schedule and resource constraints. It also describes the various processes and philosophies that the team utilized to execute the tests efficiently, including creating a standardized procedure template, keeping the test cases modular so that they could be easily interchanged, and capturing common fault injections in a change-controlled database. Finally, it will describe the tools and processes for assessing the test data, focusing in particular on a tool that evaluated vehicle state using “secondary” sources of data to validate that the software had truly configured the spacecraft to the expected safe state.} } - Lumnah, A., Pujari, S. and Sereno, V. (2024). Driving Down Risk in the Psyche Fault Protection Design Post Launch Slip
. International Symposium on Experimental Robotics. Source
BibTeX
@inproceedings{lumnah2024driving, title = {Driving Down Risk in the Psyche Fault Protection Design Post Launch Slip}, author = {Lumnah, Alexander and Pujari, Swapnil and Sereno, Virginia}, booktitle = {International Symposium on Experimental Robotics}, publisher = {JPL Open Repository}, year = {2024}, doi = {10.48577/jpl.wdvmh8}, abstract = {The Psyche Mission is a NASA Discovery-class Mission to explore (16) Psyche, a large metallic asteroid that orbits the sun between 2.5 and 3.3 au. The spacecraft bus is a repurposed earth-orbiting telecommunication satellite bus developed by Maxar, combined with Avionics and software developed by JPL. To ensure this earth-orbiting spacecraft bus can survive the lengthy journey into deep space, a robust fault protection function was designed, implemented, and tested. Originally scheduled for July 2022, the launch date was postponed to October 2023 due to delays during system-level testing of the spacecraft. By the time the launch slip was announced, the fault protection design was fully implemented in software, and the V&V program was nearly complete. Consequently, the team found themselves with an additional year of unplanned development time, which provided the unique opportunity to revisit parts of the fault protection design, implementation, and V&V strategy prior to launch, while incorporating lessons learned from the previous year of testing.This paper provides an overview of the efforts taken to drive down risk in the Psyche fault protection design after the launch slip. These efforts can be split into three categories: additional “deep dive” analyses targeting higher risk areas of the design, improvements to the design and implementation that resulted in software changes, and the development of a rich set of high-fidelity risk reduction test cases meant to validate the fault protection function. This paper discusses the motivating concerns that drove each of these efforts and explains how lessons learned were incorporated into the post-launch slip development work. It summarizes the analyses that were spawned and explains the methods that were used to constrain and complete each analysis. It captures the trades made when deciding which design changes and software bug fixes to implement, and describes the processes used to implement and verify those changes in an agile manner. Finally, the paper captures the brainstorming process for devising a set of risk reduction tests used to improve confidence in the fault protection design, and validate its performance over a wide range of scenarios.} } - Pujari, S., Summer, J., Sereno, V. and Lumnah, A. (2024). Two Steps Forward: Evolving Psyche's Fault Protection Validation Post-Launch Slip
. IEEE Aerospace Conference. Source
BibTeX
@inproceedings{pujari2024two, title = {Two Steps Forward: Evolving Psyche's Fault Protection Validation Post-Launch Slip}, author = {Pujari, Swapnil and Summer, Jonathan and Sereno, Virginia and Lumnah, Alexander}, booktitle = {IEEE Aerospace Conference}, publisher = {JPL Open Repository}, year = {2024}, doi = {10.48577/jpl.grmhhb}, abstract = {On October 5th, 2023, the Psyche Mission is targeted to launch to the large metallic asteroid (16) Psyche that will be exploring the exposed core material of a differentiated planetesimal-class asteroid. This unique NASA Discovery-class Mission combines a Solar Electric Propulsion (SEP) Chassis from Maxar Technologies with JPL’s contribution of avionics, flight software, and fault protection design. The Psyche Fault Protection (FP), implemented as autonomous algorithms, can detect, isolate, respond to, and recover from off-nominal conditions that may prevent mission success.The FP Verification and Validation (V&V) campaign involved numerous types of testing including FP infrastructure, monitor & response end-to-end (E2E) functionality, scenario testing, and stress and robustness testing across both high and low-fidelity venues. Due to delays in system level software testing, Psyche had to reschedule its original launch window from July 2022 to October 2023. This paper focuses on how the V&V campaign was scoped and executed prior to the launch slip and then improved after the launch slip. Adaptations included testing a comprehensive E2E regression test suite by targeting updates made to the GNC FP design, a streamlined data execution that employed variance of initial conditions and a consistent test procedure, and a robust and efficient data review strategy including tooling to automate checks. By capitalizing on the additional time, resources, and insights gained from Psyche’s launch slip, the Fault Protection V&V campaign benefited from a more comprehensive and rigorous validation process. This paper captures the knowledge and processes employed to validating Psyche’s Fault Protection design such that future FP V&V campaigns can benefit from more robust testing.} } - Gat, E. (2000). The MDS autonomous control architecture
. World Automation Congress. Source
BibTeX
@inproceedings{gat2000mds, title = {The MDS autonomous control architecture}, author = {Gat, Erann}, booktitle = {World Automation Congress}, publisher = {JPL Open Repository}, year = {2000}, url = {https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=hdl:2014/15927} } - Rasmussen, R. D. (2008). GN&C Fault Protection Fundamentals, 20100020171. ntrs.nasa.gov/citations/20100020171
BibTeX
@misc{rasmussen2008gnc, title = {{GN\&C} Fault Protection Fundamentals}, author = {Rasmussen, Robert D.}, howpublished = {Presentation at the Jet Propulsion Laboratory, California Institute of Technology}, number = {20100020171}, year = {2008}, url = {https://ntrs.nasa.gov/citations/20100020171}, abstract = {This is a companion presentation for a paper by the same name for the same conference. The objective of this paper is to shed some light on the fundamentals of fault tolerant design for GN&C. The common heritage of ideas behind both faulted and normal operation is explored, as is the increasingly indistinct line between these realms in complex missions. Techniques in common practice are then evaluated in this light to suggest a better direction for future efforts.} } - Ingham, M. and Robertson, P. (2005). Model-based autonomy
. IEEE Systems, Man, and Cybernetics Conference. Source
BibTeX
@inproceedings{ingham2005model, title = {Model-based autonomy}, author = {Ingham, Michel and Robertson, Paul}, booktitle = {IEEE Systems, Man, and Cybernetics Conference}, year = {2005}, url = {https://ntrs.nasa.gov/citations/20060043275} } - Fesq, L. M. and Jacome, R. W. (2015). Developing a fault management guidebook for NASA's deep space robotic missions
. AIAA Infotech @ Aerospace. Source
BibTeX
@inproceedings{fesq2015developing, title = {Developing a fault management guidebook for NASA's deep space robotic missions}, author = {Fesq, Lorraine M. and Jacome, Raquel W.}, booktitle = {AIAA Infotech @ Aerospace}, publisher = {American Institute of Aeronautics and Astronautics}, year = {2015}, doi = {10.2514/6.2015-1795}, abstract = {NASA designs and builds systems that achieve incredibly ambitious goals, as evidenced by the Curiosity rover traversing on Mars, the highly complex International Space Station orbiting our Earth, and the compelling plans for capturing, retrieving and redirecting an asteroid into a lunar orbit to create a nearby a target to be investigated by astronauts. In order to accomplish these feats, the missions must be imbued with sufficient knowledge and capability not only to realize the goals, but also to identify and respond to off-nominal conditions. Fault Management (FM) is the discipline of establishing how a system will respond to preserve its ability to function even in the presence of faults. In 2012, NASA released a draft FM Handbook in an attempt to coalesce the field by establishing a unified terminology and a common process for designing FM mechanisms. However, FM approaches are very diverse across NASA, especially between the different mission types such as Earth orbiters, launch vehicles, deep space robotic vehicles and human spaceflight missions, and the authors were challenged to capture and represent all of these views. The authors recognized that a necessary precursor step is for each sub-community to codify its FM policies, practices and approaches in individual, focused guidebooks. Then, the sub-communities can look across NASA to better understand the different ways off-nominal conditions are addressed, and to seek commonality or at least an understanding of the multitude of FM approaches. This paper describes the development of the Space Robotic Fault Management Guidebook, which is intended to be the first of NASA's FM guidebooks. Its purpose is to be a field-guide for FM practitioners working on deep space robotic missions, as well as a planning tool for project managers. Publication of this Deep Space Robotic FM Guidebook is expected in early 2015. The guidebook will be posted on NASA's Engineering Network on the FM Community of Practice website so that it will be available to all NASA projects. Future plans for subsequent guidebooks for the other NASA sub-communities are proposed.} } - Avizienis, A., Laprie, J.-C., Randell, B. and Landwehr, C. (2004). Basic Concepts and Taxonomy of Dependable and Secure Computing
. IEEE Transactions on Dependable and Secure Computing, 1. Source
BibTeX
@article{avizienis2004basic, title = {Basic Concepts and Taxonomy of Dependable and Secure Computing}, author = {Avizienis, Algirdas and Laprie, Jean-Claude and Randell, Brian and Landwehr, Carl}, journal = {IEEE Transactions on Dependable and Secure Computing}, volume = {1}, number = {1}, pages = {11--33}, year = {2004}, doi = {10.1109/tdsc.2004.2}, abstract = {This paper gives the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc. Security brings in concerns for confidentiality, in addition to availability and integrity. Basic definitions are given first. They are then commented upon, and supplemented by additional definitions, which address the threats to dependability and security (faults, errors, failures), their attributes, and the means for their achievement (fault prevention, fault tolerance, fault removal, fault forecasting). The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of system failures.} } - Avizienis, A. (1967). Design of Fault-Tolerant Computers
. November 14-16, Fall Joint Computer Conference. Source
BibTeX
@inproceedings{avizienis1967design, title = {Design of Fault-Tolerant Computers}, author = {Avizienis, Algirdas}, booktitle = {November 14-16, Fall Joint Computer Conference}, pages = {733}, year = {1967}, doi = {10.1145/1465611.1465708}, abstract = {Reliable performance of hardware has been a requirement for digital systems since the construction of the first digital computer. Improper functioning of the logic circuits in a digital system is manifested by logic faults, which are defined for this paper as "permanent or transient deviations of logic variables from the values specified in design."} } - Dvorak, D. (2009). NASA Study on Flight Software Complexity
. AIAA Infotech@Aerospace Conference. Source
BibTeX
@inproceedings{dvorak2009nasa, title = {NASA Study on Flight Software Complexity}, author = {Dvorak, Daniel}, booktitle = {AIAA Infotech@Aerospace Conference}, year = {2009}, doi = {10.2514/6.2009-1882}, abstract = {In 2007 the NASA Office of Chief Engineer commissioned a multi-center study to bring forth technical and managerial strategies to address risks from growth in size and complexity of flight software in NASA’s space missions. The motivation for the study grew from problems attributed to flight software in a variety of missions—in both pre-launch and post-launch activities—and concerns that such problems were growing with the expanding role of flight software. The study was tasked to examine the growth in flight software size and complexity, recommend ways to reduce and better manage complexity, and identify methods of testing complex logic. This report examines complexity throughout the engineering lifecycle—from requirements definition through design, development, verification, and operations—and presents sixteen findings and associated recommendations.} } - Fesq, L., Aljabri, A., Anderson, C., Connerton, R., Doyle, R., Hoffman, M. and Man, G. (1996). Spacecraft Autonomy in the New Millenium. ntrs.nasa.gov/citations/20210004993
BibTeX
@misc{fesq1996spacecraft, title = {Spacecraft Autonomy in the New Millenium}, author = {Fesq, Lorraine and Aljabri, Abdullah and Anderson, Christine and Connerton, Robert and Doyle, Richard and Hoffman, Mark and Man, Guy}, year = {1996}, url = {https://ntrs.nasa.gov/citations/20210004993}, abstract = {NASA's New Millenium Program (NMP) is designed to dramatically reduce mission costs and enable new and more frequent exploration missons.} } - Fesq, L. (2017). New developments in ISHM for NASA robotic flight systems. dataverse.jpl.nasa.gov/dataset.xhtml
BibTeX
@misc{fesq2017new, title = {New developments in ISHM for NASA robotic flight systems}, author = {Fesq, Lorraine}, year = {2017}, url = {https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=hdl:2014/47330} } - Meshkat, L. (2020). Risk considerations for autonomy software
. Annual Reliability and Maintainability Symposium. Source
BibTeX
@inproceedings{meshkat2020risk, title = {Risk considerations for autonomy software}, author = {Meshkat, Leila}, booktitle = {Annual Reliability and Maintainability Symposium}, volume = {28}, pages = {1-6}, year = {2020}, doi = {10.1109/rams48030.2020.9153722}, abstract = {The application of increasingly higher level of autonomy for safety critical systems is inevitable. Ensuring the reliability of such systems requires managing the uncertainties that occur due to the increased autonomy. Our research indicates the increased uncertainty in autonomous software is due to increased discontinuities in the state space and inadequate situational awareness.} } - Heverly, M. and Bareh, M. (2026). The Impact of Major Anomalies of Robotic Mars Surface Missions on Mission Timeline
. IEEE Aerospace Conference. Source
BibTeX
@inproceedings{heverly2026impact, title = {The Impact of Major Anomalies of Robotic Mars Surface Missions on Mission Timeline}, author = {Heverly, Matt and Bareh, Magdy}, booktitle = {IEEE Aerospace Conference}, publisher = {JPL Open Repository}, year = {2026}, doi = {10.48577/jpl.zlcejq} } - Kinnett, R., Green, T., Klein, D. and Lin, M. R. (2022). Remote Diagnosis and Operational Response to an In-Flight Failure of the Drill Feed Mechanism Onboard the Mars Science Laboratory Rover
. Aerospace Mechanisms Symposium. Source
BibTeX
@inproceedings{kinnett2022remote, title = {Remote Diagnosis and Operational Response to an In-Flight Failure of the Drill Feed Mechanism Onboard the Mars Science Laboratory Rover}, author = {Kinnett, Ryan and Green, Thomas and Klein, Douglas and Lin, Megan Richardson}, booktitle = {Aerospace Mechanisms Symposium}, publisher = {JPL Open Repository}, year = {2022}, url = {https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=hdl:2014/56163} } - Sabzehi, M. (2024). Enhancing Rover Mobility Monitoring: Autoencoder-driven Anomaly Detection for the Mars Science Laboratory
. Root. doi.org/10.48577/jpl.m6mi5n
BibTeX
@misc{sabzehi2024benhancing, title = {Enhancing Rover Mobility Monitoring: Autoencoder-driven Anomaly Detection for the Mars Science Laboratory}, author = {Sabzehi, Mielad}, journal = {Root}, year = {2024}, doi = {10.48577/jpl.m6mi5n}, abstract = {Over eleven years into its mission, the Mars ScienceLaboratory remains vital to NASA’s Mars exploration. Safe-guarding the rover’s long-term functionality is a top mission pri-ority. In this study, we introduce and test undercomplete autoen-coder models for detecting drive anomalies, using telemetry datafrom wheel actuators, the Rover Inertial Measurement Unit(RIMU), and the suspension system. Our approach enhancespost-drive data analysis during tactical downlink sessions. Weexplore various model architectures and input features to un-derstand their impact on performance. Evaluating the mod-els involves testing them on unseen data to mimic real-worldscenarios. Our experiments demonstrate the undercompleteautoencoder model’s effectiveness in detecting drive anomalieswithin the Curiosity rover dataset. Remarkably, the modeleven identifies subtle anomalous telemetry patterns missed byhuman operators. Additionally, we provide insights into optimaldesign choices by comparing different model architectures andinput features. This research significantly advances anomalydetection in space flight operations, potentially enhancing thereliability and safety of future planetary exploration missionsthrough early anomaly detection and proactive maintenance.The model’s ability to capture subtle anomalies, potentiallyindicating early-stage failures, holds promise for the field.} } - Srivastava, P., Bates-Tarasewicz, H. A., Cloutier, K. D., De Soria-Santacruz Pich, M., Lumnah, A. J. and Wilkerson, M. (2024). Psyche's Payload Fault Protection Design and Strategy for Launch Readiness
. IEEE Aerospace Conference. Source
BibTeX
@inproceedings{srivastava2024psyche, title = {Psyche's Payload Fault Protection Design and Strategy for Launch Readiness}, author = {Srivastava, Priyanka and Bates-Tarasewicz, Haley A. and Cloutier, Kyle D. and De Soria-Santacruz Pich, Maria and Lumnah, Alexander J. and Wilkerson, Marcus}, booktitle = {IEEE Aerospace Conference}, publisher = {JPL Open Repository}, year = {2024}, doi = {10.48577/jpl.ivff4w}, abstract = {NASA's Psyche mission is a journey to the unique metal-rich (16) Psyche asteroid orbiting the Sun between Mars and Jupiter to get a better insight into the Earth's core and the core of other terrestrial planets. The mission will offer a unique scientific value by mapping the asteroid and studying its properties with the help of a robust Spacecraft that carries a highly capable Payload suite onboard. Psyche's Payload suite is a novel collection of heritage and technology demonstration instruments. Heritage instruments include a Multispectral Imager, a Magnetometer, and a Gamma Ray and Neutron Spectrometer. The Deep Space Optical Communications (DSOC) instrument is a Class D technology demonstration that will perform optical communications at AU-magnitude distances. The Spacecraft will need to survive in vaguely known environments and with a wide range of uncertainties from the time of Launch to the Psyche Science Orbital Operations period. Most of these instruments will be functioning at the same time in conjunction with the rest of the subsystems, and with limited contact with the ground operations team on Earth. To ensure that the Spacecraft and instruments are robust to possible anomalies and can remain healthy and functional to meet the science goals and overall mission success criteria, Psyche's Fault Protection (FP) and Payload teams designed and implemented an autonomous onboard fault management architecture and engine. This Flight Software-based autonomy will execute fault detection, isolation and perform health recovery actions to prevent propagation of anomalous behavior between the instruments and the rest of the Spacecraft. This paper details the history of how Psyche’s Payload Fault Protection design evolved and was fine-tuned through a rigorous testing and analysis campaign to address the needs and challenges of the diverse set of instruments. It describes the key lessons learned, including the ones that emerged post launch-slip in the year 2022, and how a shift in the FP Verification and Validation (V&V) strategy helped the team gain increased confidence in the instruments for Launch readiness in 2023.} } - Nikora, A., Aleem, M., Mackey, R., Fesq, L., Chung, S., Kolcio, K., Prather, M. and Matthew, L. (2020). Demonstrating Assurance of Model-Based Fault Diagnosis Systems on an Operational Mission
. IEEE Aerospace Conference. Source
BibTeX
@inproceedings{nikora2020demonstrating, title = {Demonstrating Assurance of Model-Based Fault Diagnosis Systems on an Operational Mission}, author = {Nikora, Allen and Aleem, Mishaal and Mackey, Ryan and Fesq, Lorraine and Chung, Seung and Kolcio, Ksenia and Prather, Maurice and Matthew, Litke}, booktitle = {IEEE Aerospace Conference}, pages = {1-16}, publisher = {IEEE}, year = {2020}, doi = {10.1109/aero47225.2020.9172282}, abstract = {Developers of robotic scientific and commercial spacecraft are trending towards use of onboard autonomous capabilities for responding quickly to dynamic environments and rapidly changing situations. These capabilities need to know the state of the spacecraft's health. Model-based fault diagnosis (MBFD) is an approach to estimating health by continuously verifying accurate behavior and diagnosing off-nominal behavior. Proper functioning of MBFD depends on 1) the quality of the diagnostic system model that is analyzed and compared to commands and onboard measurements to estimate a system's health state, and 2) the correct functionality of the diagnosis engine interrogating the model and comparing its analyses to observed system behavior. Our goal is to develop Verification and Validation (V&V) techniques for MBFD to provide future missions sufficient confidence in its functionality and performance to deploy it on the systems they develop. Our work has been focused on infusing the techniques we developed earlier to an operational mission. First, we are constructing diagnostic models of a spacecraft attitude control system and updating our diagnostic engine so they can be demonstrated aboard the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, an operational spacecraft for which experiments in autonomy are being planned and executed, using the V&V techniques we have previously developed to assure they are both correct and complete. Since it is nearing the end of its life, ASTERIA provides a unique opportunity to demonstrate MBFD since the monitored components are expected to fail. Our demonstration will give system developers additional confidence to make timely, informed MBFD deployment decisions. Second, we will be completing performance assessments of the diagnostic engine/diagnostic model ensemble both on the flight system and ground-based testbeds to gain confidence in MBFD's ability to run successfully in a spacecraft's resource-constrained environment without adversely affecting other on-board activities. Finally, we are capturing our experience in preparing this demonstration in a set of checklists and guidance documents. Current practice includes high-level institutional guidance documents and standards, but at a high level of abstraction that does not necessarily address specific MBFD concerns. The purpose of the new checklists is to provide future mission developers clear, unambiguous, procedure-oriented guidance on assuring MBFD. This paper describes our work in these areas. For the first area, we describe the diagnostic models and updated diagnostic engine that will be used for the on-board demonstration. We describe how the V&V techniques we developed earlier are used to assure model and engine correctness and completeness. For the second area, we identify the performance measurement and assessment techniques used to characterize the diagnostic engine and diagnostic models, and discuss the effect of measured performance on overall mission operation. Finally, we present the checklist and guidance documents and describe how they meet the goals of providing system developers with clear, unambiguous, procedure-oriented guidance on MBFD assurance. We show how the techniques we have developed map into those artifacts.} } - Schaffer, S., Chien, S. and Ferguson, E. (2018). Validation of Fault-Tolerant Plans for Europa Clipper. ntrs.nasa.gov/citations/20210008437
BibTeX
@misc{schaffer2018validation, title = {Validation of Fault-Tolerant Plans for Europa Clipper}, author = {Schaffer, Steve and Chien, Steve and Ferguson, Eric}, year = {2018}, url = {https://ntrs.nasa.gov/citations/20210008437}, abstract = {The Europa Clipper mission will explore that icy moon in a series of brief flybys through the Jovian radiation belts. A single event upset in the spacecraft flight computer during these critical scientific periods could jeopardize the success of the mission. Rather than safing and awaiting operator intervention, the Clipper mission envisions limited onboard autonomy that can restore spacecraft state sufficiently to resume the encounter observation plan as rapidly as possible. The contingency plan is contained in an Activity Restart Timeline (ART) that is transmitted in parallel with the nominal plan, which must be co-validated jointly against all spacecraft state and resource constraints amid unpredictable fault timing. A prototype validation tool was built that leverages declarative spacecraft models and automated search techniques to find such potential inconsistencies in the unified contingent mission plan. Early validation results within motivating scenarios are presented.} } - Bates, D., Lee, A., Meakin, P. and Weitl, R. (2013). Fault protection design and testing for the Cassini spacecraft in a "mixed" thruster configuration
. AIAA Guidance, Navigation, and Control Conference. Source
BibTeX
@inproceedings{bates2013fault, title = {Fault protection design and testing for the Cassini spacecraft in a "mixed" thruster configuration}, author = {Bates, David and Lee, Allan and Meakin, Peter and Weitl, Raquel}, booktitle = {AIAA Guidance, Navigation, and Control Conference}, publisher = {American Institute of Aeronautics and Astronautics}, year = {2013}, doi = {10.2514/6.2013-4632} } - Neilson, T. A. and Manning, R. M. (2013). Curiosity's autonomous surface safing behavior design
. AIAA SPACE Conference. Source
BibTeX
@inproceedings{neilson2013curiosity, title = {Curiosity's autonomous surface safing behavior design}, author = {Neilson, Tracy A. and Manning, Robert M.}, booktitle = {AIAA SPACE Conference}, publisher = {JPL Open Repository}, year = {2013}, url = {https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=hdl:2014/44367} } - Sorice, C., Ali, K. S., Trebi-Ollennu, A., Mishra, P., Lim, G., Bailey, P., Hudson, T. L., Marteau, E. and Kim, J. (2021). InSight Robotic Arm Testing Activities for HP3 Mole Anomaly Recovery on Mars
. LDEF Post-Retrieval Symposium. Source
BibTeX
@inproceedings{sorice2021insight, title = {InSight Robotic Arm Testing Activities for HP3 Mole Anomaly Recovery on Mars}, author = {Sorice, Cristina and Ali, Khaled S. and Trebi-Ollennu, Ashitey and Mishra, Pranay and Lim, Grace and Bailey, Philip and Hudson, Troy Lee and Marteau, Eloise and Kim, Junggon}, booktitle = {LDEF Post-Retrieval Symposium}, pages = {1-19}, publisher = {IEEE}, year = {2021}, doi = {10.1109/aero50100.2021.9438334} }