Skip to content
Space Robotics

Processors

Flight processors selected by flown planetary and orbital robotics programs, with the flight or ground result that establishes each one.

The governing tradeoff for the class is throughput against upset behavior, and it shows up in the duty cycle of autonomy rather than in a datasheet. On the Mars Exploration Rovers a single visual odometry step took an average of nearly three minutes on the 20 MHz RAD6000, so the technique was commanded only on short drives, on slopes above about 10 degrees, or when a wheel was being dragged [1].

Compute across the Mars rovers

Section titled “Compute across the Mars rovers”

The flown line is short and each step is a clock and memory increase on a hardened PowerPC lineage: a 2 MHz 80C85 on Sojourner, a 20 MHz RAD6000 on the Mars Exploration Rovers, a 133 MHz RAD750 on Curiosity, and two 133 MHz RAD750 units plus a Virtex-5QV FPGA on Perseverance, with RAM rising from 0.56 MB to 128 MB, then 128 plus 512 MB, then twice that pair [24]. On the MER the autonomy software could use at most 75 percent of the 20 MHz CPU, dynamic memory allocation was not permitted, and the descent image motion estimator took 40 percent of the CPU for 17 s of imaging during entry [23]. Autonomous terrain assessment covered about 25 percent of the distance driven by each rover, and visual odometry about 14 percent [23].

The FPGA is the change that removed the stop-and-think pause. AutoNav paused about 120 s per step on Spirit, Opportunity and Curiosity and typically 0 s on Perseverance when not steering, while the stereo workload per step rose from 10,000 to 50,000 pixels on the MER to 240,000 to 1,200,000 on Perseverance, processed on the FPGA at a rated 22 million disparities per second [24]. The consequence is operational: during the Rapid Traverse Campaign planners chose a 4.8 km route over a 2.4 km one because AutoNav could sustain 200 to 250 m/sol on it [24]. The compute figures in that comparison are rated values, not measurements of drive-time utilization.

Memory, not clock, was the binding constraint in the two best-documented MER software events. The rovers carried 128 MB DRAM, a 3 MB EEPROM bank on the CPU card, and two 4 MB EEPROM banks plus 256 MB flash on the non-volatile memory card, with the A and B software images each split between EEPROM and flash [25]. A full flight software load was about 8 MB of uplink and the February 2005 patch about 2 MB, delivered over X band direct from Earth and finished with a commanded cold boot and a 15 minute wake [25]. The Spirit sol 18 reset loop came from a file system library whose RAM data structure grew with the high water mark of files ever created; the 256 KB private area was allowed to expand into free memory, and an allocation failure suspended the requesting task silently [26]. Fault protection treated the CPU as the part that sleeps: the battery charge board and mission clock FPGA stay powered through the night while the processor does not, and solar wakeup is declared after array current exceeds 2.0 A for ten minutes [27].

Processor choice does not fix the part-level risk around it. Heavy ion screening of fourteen commercial parts for a JPL Class D payload found destructive latchup in four, including an Altera PowerSoC buck regulator at LET 42.8 MeV-cm2/mg, and non-destructive latchup in two MEMS accelerometers [28]. The screen covers single event latchup only, with no upset or total dose data, so a clean result there is not a qualification [28].

Flight processors selected and flown

Section titled “Flight processors selected and flown”
PartManufacturerUsed bySource
RAD6000BAE Systemsspirit, opportunity[1]
RAD750BAE Systemscuriosity, perseverance[2][3][4]
LEON3FTCobham Gaislerperseverance (SuperCam)[5]
TMS320C6701Texas Instrumentsspheres[6][7]
Snapdragon 801Qualcommingenuity[8][9]
80386SXIntelISS multiplexers[10]
ThinkPad 760XD, T61pIBM, LenovoISS crew laptops[10]

Ratings and qualification results

Section titled “Ratings and qualification results”
  • RAD6000, BAE Systems: a radiation-hardened 32-bit POWER single-board computer [1]. Ratings: 20 MHz as flown on MER; single CPU shared with the camera bus [1]. Qualification: Flown from January 2004. Each visual odometry step averaged nearly three minutes of computation, restricting the technique to drives typically under 15 m and to steps of no more than 75 cm or 18 degrees of turn [1].
  • RAD750, BAE Systems: a radiation-hardened PowerPC 750 single-board computer [2]. Ratings: MSL Rover Compute Element carries 512 MB RAM under VxWorks, two units in prime and hot backup [2][3]; measured 200 to 300 MIPS on the Mars 2020 vehicle, of which the onboard scheduler receives only a fraction [4]. Qualification: On Curiosity a failing region of RCE-A NAND flash forced a swap to RCE-B on sol 201. The RCE-B data product partition then failed to mount on sol 2173, forcing a return to RCE-A on sol 2188 until RCE-B was reformatted on sol 2342. RCE-B has carried 20,159.565 m of odometry against 1,158.793 m on RCE-A [2].
  • LEON3FT, Cobham Gaisler. Fault-tolerant SPARC V8 processor with SpaceWire, in the SuperCam Body Unit. The source names the core designer; the vendor of the flight part is not named [5]. Ratings: 50 MHz; four SpaceWire interfaces, one of them mapped to the Mast Unit at 30 MHz [5]. Qualification: Flown since February 2021. Paired with a Cobham Aeroflex start-up PROM that can accept a limited command set from the rover compute element and rewrite corrupt program memory on Mars, so a memory corruption is recoverable rather than terminal [5].
  • TMS320C6701, Texas Instruments, on a Sundance SMT375 carrier board. Floating-point DSP. Ratings: Carrier board also holds a Xilinx Spartan II XC2S200 and a MAX1294 converter [6]. Qualification: Three units launched to the ISS in 2006 and had conducted more than 70 test sessions by 2015 [7].
  • Snapdragon 801, Qualcomm: a commercial smartphone system on chip, not radiation hardened [9]. Ratings: Commercial part, no radiation qualification claimed [9]. Qualification: Completed 72 flights on Mars between April 2021 and January 2024 [8]. Obsolescence rather than radiation ended its use: the part is no longer available in the condition and quantity required, so the Sample Recovery Helicopter design moved to a newer Snapdragon [9]. On Perseverance the same part, as the Helicopter Base Station, was repurposed as a co-processor to the RAD750: onboard global localization ran in 32 s at 45 C on sol 914, about an order of magnitude faster than on the RAD750, while the fixed 10 KB/s serial link made image transfer take 30 minutes. The simulated upset rate for the Snapdragon 801 is 4313 per device per day uncorrected against 13 per day corrected for the RAD750, and it is a CREME-MC estimate, not a flight measurement [29].
  • 80386SX, Intel, in the Input/Output Control Unit card: a radiation-screened commercial microprocessor in an ISS Multiplexer/Demultiplexer, the command and data handling bus that hosts canadarm2 and dextre [10]. Ratings: Each IOCU card carries the processor, a 1553 bus interface and 33,554,432 bits of DRAM; Hamming single-error-correction double-error-detection runs inside the DRAM refresh cycle, holding bad-bit residence below 10 microseconds [10]. Qualification: Flown in a three-tier scheme: tier 1 two-fault tolerant on three identical computers, tier 2 one-fault tolerant on two, tier 3 zero-fault tolerant with redundancy obtained by allocating software across computers. Sixteen probable lock-up single event functional interrupts were logged across the fleet between 2001 and 2015, each costing ground controllers 12 to 24 hours to power cycle, reboot and resynchronize, and the rate per computer per year stayed well below the pre-flight prediction for the whole 14 years [10].
  • ThinkPad 760XD, T61p, IBM and Lenovo: unmodified commercial laptops flown as the ISS Portable Computer System, the crew and payload interface [10]. Ratings: No radiation hardening; screened by high-energy proton testing before flight [10]. Qualification: In-flight single event functional interrupt rate measured at 0.023 +/- 0.012 per day for three 760XDs over 2001, against 0.04 per day predicted from proton testing, and 0.013 +/- 0.004 per day for seven T61p units over 2011 to 2014 against 0.13 per day predicted. Proton-beam prediction overestimated the flight rate by a factor of about two and about ten respectively. Two of the seven T61p units suffered hard failures that may or may not be radiation induced [10].

Reading the clock and rate figures

Section titled “Reading the clock and rate figures”

The RAD750 row covers three programs, and no single clock is published across them. The Mars 2020 build was measured at 200 to 300 MIPS [4]. The part is a family, and a clock figure is only meaningful against a specific board.

The ISS laptop rows are the only entries in the class with a matched pre-flight prediction and an in-flight measurement of the same assembled hardware.

Article and unit countPeriod on orbitGround predictionFlight measurementRatio
IBM 760XD ThinkPad, 3 unitsMarch to December 20010.04 SEFI/day0.023 +/- 0.012 SEFI/day1.7x high
Lenovo T61p, 7 units2011 to 2014, 877 to 1088 days each0.13 SEFI/day0.013 +/- 0.004 SEFI/day10x high

Source: [10].

Both predictions came from 200 MeV proton testing of assembled articles [10]. Screening was conservative in both cases, and the two conservatism factors differ by a factor of six on the same method, so a redundancy scheme sized on a predicted rate is sized on an unknown margin. Non-radiation functional interrupts on the T61p campaign were comparable in number to the radiation ones and had to be screened out by judgment, and two of the seven units suffered hard failures of unknown cause [10]. The piece-part comparison from the same campaign, on DRAM, is on Memory and Storage, where the two predictions land within 2.7 and 2.9 times: predicting an assembled article buys coverage of the whole machine and costs the tightness the piece-part method keeps.

Multicore processors and software mitigation

Section titled “Multicore processors and software mitigation”

Two approaches to raising onboard throughput have been proposed for parts that no planetary robot has flown with a radiation guarantee. The first is a flight multicore. A Goddard and JPL position paper argued for commercial multicore processors over FPGAs and set requirements of at least 40 GOPS and 20 GFLOPS, power gating at individual core granularity, and hardware partitioning strong enough that a core can crash and restart without affecting its neighbors [31]. It is a proposal with no benchmark, port or radiation datum behind it [31]. A JPL paper on Terrain Relative Navigation carried the idea to design: software fault mitigation for the 64-core Tilera and its 49-core hardened counterpart Maestro, with triple modular redundancy across cores [32]. It reports no measured throughput, overhead or coverage, and the authors defer quantitative analysis to later implementation work [32].

The second is a commercial part flown with software mitigation. Perseverance runs global localization on the unhardened Snapdragon 801 in the Helicopter Base Station by executing the algorithm twice with a full co-processor reboot between runs, comparing the results, checksumming inputs, outputs and the binary at several stages, and adding Reed-Solomon coding over the vendor eMMC error correction [30]. The argument is qualitative: no upset rate was measured for the part, and localization runs once per sol after a drive, not in a real-time control loop [30]. Ingenuity used the same split in software: F Prime deployments on the Snapdragon navigation computer, a bare metal Texas Instruments automotive microcontroller flight computer running a 500 Hz motor and guidance cycle, and the base station, with component connections crossing processor boundaries over UART [33]. The source gives no CPU utilization or timing margin for any deployment [33].

Parts characterized but not yet flown on a planetary robot

Section titled “Parts characterized but not yet flown on a planetary robot”

Radiation characterization of commercial and radiation-tolerant processors published by the NASA Electronic Parts and Packaging program and by mission avionics teams. These are test results against a named beam and facility, not flight heritage.

PartManufacturerFacility and dateSource
RH-OBC-1Vorago TechnologiesMassachusetts General Hospital, June 2019[11]
Ryzen 7 1700, Ryzen 3 1200, Ryzen 3 2200GAMDMassachusetts General Hospital, June 2019[11]
Jetson TX2NVIDIAMassachusetts General Hospital, June 2019[11]
Jetson TX2iNVIDIAJohns Hopkins Applied Physics Laboratory, 2021[12]
MSP430Texas InstrumentsIn-house dose testing, 2021[12]
ISIS On-board ComputerInnovative Solutions in SpaceNo new testing[12]
Coral USB acceleratorGoogleNo radiation testing[13]

Ratings and campaign results

Section titled “Ratings and campaign results”
  • RH-OBC-1, Vorago Technologies. Radiation-hardened CubeSat Kit single-board computer built on the VA10820 ARM Cortex-M0 core, with regulators, ADC, watchdog and CAN controller. Tested at the Francis Burr Proton Therapy Center at Massachusetts General Hospital [11]. Ratings: Core memory carries EDAC; board carries two Cypress FRAM devices as boot and user memory. Qualification: 200 MeV proton testing at board and component level [11]. SRAM single-bit upset cross section 3e-8 cm2/device, ROM 1.3e-7 cm2/device, no multi-bit upsets. 3e11 p/cm2 and about 12.2 krad(Si) accumulated with no parametric degradation [11]. Both FRAM devices took functional interrupts, and the board has no way to gate their power, so a boot FRAM SEFI leaves the microcontroller unable to reload boot code until an external power cycle [11]. The failure was not visible in piece-part testing.
  • Ryzen 7 1700, Ryzen 3 1200, Ryzen 3 2200G, AMD: commercial multi-core x86 processors, the Ryzen 7 part tested being the YD1700BBM88AE [11]. Ratings: Not radiation hardened. Qualification: 200 MeV protons [11]. Single event functional interrupts and upsets observed with no failures to 1.55e11, 8.92e10 and 4.66e10 p/cm2 respectively; a power cycle recovered every event.
  • Jetson TX2, NVIDIA. Commercial GPU single-board computer. Ratings: Not radiation hardened. Qualification: 200 MeV protons, two devices [11]. One saw no failures to 1.89e9 p/cm2; the second failed at 1.61e9 p/cm2. A power cycle recovered every non-destructive event.
  • Jetson TX2i, NVIDIA, on a Connect Tech Spacely carrier. Commercial GPGPU carried as a rover central computer, proton and cobalt-60 tested. Ratings: Selected for MoonRanger, a mission of 6 to 9 days in transit and under 15 days on the surface, with avionics powered down through the Van Allen belts [12]. Qualification: Independent testing established survival to 45 krad(Si) unpowered and 10 krad(Si) powered, with proton testing giving at least 90 percent probability of survival at an average of 4 resets in a flux equivalent to a six month lunar mission [12]. Computer, cameras and interface board were also tested powered to 4 krad(Si) against a predicted mission dose under 1 krad(Si).
  • MSP430, Texas Instruments. Microcontroller used across the MoonRanger power, thermal and motor control boards. Ratings: Ferroelectric program memory, which is immune to the radiation effects that afflict flash program store. Qualification: CubeSat flight heritage on BasicLEO, RAX-1, RAX-2 and LMRSat [12]. In-house total ionizing dose testing was levied on the in-house boards that carry it.
  • ISIS On-board Computer, Innovative Solutions in Space. ARM9 CubeSat peripheral computer. Ratings: Carried as the MoonRanger peripheral computer on CubeSat space heritage rather than on a new campaign [12]. Qualification: No new testing performed; heritage accepted.
  • Coral USB accelerator, Google: a commercial edge TPU inference ASIC for 8-bit quantized neural networks [13]. Ratings: Paired with an ARM Cortex-A72 at 1.5 GHz and 4 GB of RAM as a candidate flight-representative host. Qualification: No radiation campaign published. Ground benchmark only: YOLOv3-tiny sample tube detection ran in 33.46 ms on the Cortex-A72 with the accelerator against 2808.62 ms without it, 84 times faster at lower power than the CPU alone [13].

A total ionizing dose or proton number is a screening result, not a qualification. None of the commercial parts above carries a latch-up immunity claim, and the Vorago board result shows that a part-level pass does not predict the board-level recovery path.

Compute benchmarked at one task

Section titled “Compute benchmarked at one task”

Four devices in seven configurations were run on the same workload, a Mars HiRISE image classifier over a 1793 image test set at 227x227 grayscale with an AlexNet transfer-learning model [14]:

Processor or unitInference timeEnergy per inference
Snapdragon 855 DSP7.6 ms0.016 J
Snapdragon 855 NPUnot given0.014 J
Snapdragon 855 GPU16.3 ms0.051 J
Intel Movidius Myriad X16.2 ms0.032 J
Snapdragon 855 CPU87.8 ms0.5 J
MacBook reference56.9 msnot given
Jetson Nano CPU1069 ms5.3 to 10.7 J

The Snapdragon 855 DSP was the fastest and near the lowest energy of the set, profiled with the Snapdragon Profiler as runtime times power; the NPU on the same part took the lowest energy per inference, with no inference time published; the GPU took three times the DSP energy at twice the time; and the CPU is the baseline those on-part accelerators were measured against [14]. The Intel Movidius Myriad X was compiled to 12 vector cores and metered over USB, so its time includes host transfer, and the MacBook is a laptop reference point for the same model and test set, with no energy published. The Jetson Nano was slowest by two orders of magnitude, and its energy is estimated from a 5 to 10 W device range rather than measured [14].

The energy spread runs over three orders of magnitude and does not track the time spread. Across the standard classifiers in the same study the DSP and NPU ran 3 to 48 times faster than the Snapdragon CPU, with the speedup rising with parameter count and single-pixel models running slower on the accelerators than on the CPU [14]. The RAD750 could not be entered at all: no common deep learning framework supports it, so the flight processor of curiosity and perseverance has no figure in this comparison [14]. These are performance numbers, not qualification results. No facility, beam or dose appears against any of them. The same two units were run on the ISS, where nine iterations of the classifier and a set of memory checks over 540 minutes returned no output difference from the ground runs and no memory error [14], but that exposure is too short to bound an upset rate and the study derives no cross section from it.

Processors and support chips in the radiation compendia

Section titled “Processors and support chips in the radiation compendia”

The NASA Electronic Parts and Packaging compendia carry heavy-ion and proton results for processors that no planetary robot has flown. In every commercial part below the unprotected cache sets the sensitivity [16][17].

PartManufacturerFacilitySource
UT699 LEON3FTCobham GaislerTexas A and M cyclotron[15]
MC7447A PowerPCFreescaleTexas A and M cyclotron[16]
P2020, P5020FreescaleTexas A and M cyclotron[17]
MV64460 bridge chipMarvellTexas A and M, Indiana[16]
Maestro many-coreBoeingTexas A and M cyclotron[17]
Radeon e9173 GPUAMDMassachusetts General Hospital[11]
GR740 LEON4GaislerNo radiation result published[18]
TILE64TileraNo radiation result published[19]
IFC6501 moduleInforceNo radiation result published[20]

Ratings and campaign results

Section titled “Ratings and campaign results”
  • UT699 LEON3FT, Cobham Gaisler. Radiation-hardened fault-tolerant SPARC V8 processor, the space-grade member of the core family flown in the SuperCam Body Unit [5]. Ratings: hardened by design rather than by shielding. Qualification: heavy ion over a 9 to 60 MeV-cm2/mg range at 0 and 60 degree incidence, giving an upset threshold of 8 MeV-cm2/mg in the internal SRAM cells against 54 MeV-cm2/mg in the flip flops [15]. The SRAM threshold is under a sixth of the flip-flop threshold on the same die, so the memory and not the logic sets the scrub requirement.
  • MC7447A PowerPC, Freescale. Commercial PowerPC G4 processor. Ratings: not radiation hardened. Qualification: upset threshold below 1.7 MeV-cm2/mg with no latchup observed under heavy ion at the Texas A and M cyclotron [16].
  • P2020, P5020, Freescale. Commercial dual-core Power Architecture communications processors. Ratings: no effects are expected below 100 krad(Si), which the guideline records as an engineering expectation and not a measured qualification [15]. Qualification: unprotected cache upset threshold below 1.8 MeV-cm2/mg on both parts, with a saturated cross section of about 2e-9 cm2 per bit on the P2020 and about 1e-10 on the P5020 [17]. The effective sensitivity of the P2020 test setup was limited to 1e-6 cm2/device by the fluence at which cores crashed from double-bit cache errors [15], so the reported floor belongs to the setup rather than to the part.
  • MV64460 bridge chip, Marvell. System bridge and memory controller, the part between a flight processor and its memory. Ratings: commercial. Qualification: upset threshold below 1.7 MeV-cm2/mg under heavy ion with high-current functional interrupts also observed, and a proton upset threshold below 21 MeV at the Indiana University Cyclotron Facility [16]. A bridge chip upsetting at the same threshold as the processor it serves removes the benefit of hardening only the processor.
  • Maestro many-core, Boeing. Radiation-hardened 49-core derivative of the Tilera architecture [19]. Ratings: projected at 300 MHz with an IEEE-754 floating point unit per core, in test at the time of the source and quoted as 2.5 times the TILE64 throughput [19]. Qualification: unprotected cache upset threshold below 2 MeV-cm2/mg, saturated cross section about 8e-8 cm2 per bit [17].
  • Radeon e9173 GPU, AMD. Commercial embedded GPU. Ratings: not radiation hardened. Qualification: non-destructive latchup at a 200 MeV proton fluence of 6.24e9 protons/cm2, cleared by a power cycle [11].
  • GR740 LEON4, Gaisler. Radiation-hardened quad-core SPARC V8. Ratings: 1836 DMIPS at 250 MHz over four cores, about 1.2 W, quoted as a reference value rather than measured by the citing work [18]. Qualification: no radiation campaign is published in the corpus for this part. A flight autonomy component scaled onto it meets the Enceladus orbiter and Europa Lander use cases and fails the terrestrial field case by an order of magnitude, which is a scaled projection and not a benchmark [21].
  • TILE64, Tilera. Commercial 64-core mesh processor at 750 MHz, three-way VLIW, with no floating point hardware [19]. Ratings: 8 kB of L1 instruction and data cache and 64 kB of L2 per core [19]. Qualification: no radiation campaign published. Rock detection over a 116-image MER navcam set ran in 2.9 s per image on one core and 0.3 s on 32, a 9.7-fold speedup that asymptotes near ten rather than scaling with core count [19]. Converting the same code from floating point to integer cut single-core runtime by a factor of five, because software floating point emulation had been taking nearly three quarters of it.
  • IFC6501 module, Inforce. Commercial Snapdragon 805 module carried as the Astrobee flight processor [20]. Ratings: four cores at 2.5 GHz, shared between autonomy software and concurrent processes [20]. Qualification: no radiation campaign published. Operated on the International Space Station, where a single core measures about ten times slower than a 2.4 GHz Intel i9-9980HK [22].

A compendium entry is two or three parts tested to a threshold, not a qualification. None of the commercial processors above carries a published upset rate for any orbit, and the three parts with no campaign at all are listed because they were selected and run, not because a beam was pointed at them.

What is not established

Section titled “What is not established”

No RAD750 clock is published across Curiosity, Perseverance and the other programs that fly it, so cross-mission throughput comparison rests on the rated figures in [24] and the 200 to 300 MIPS measurement in [4]. The ISS laptop and multiplexer upset rates come from a small count of events and the source says the SEFI statistics are too thin for rigorous bounds [10]. Commercial processors, GPUs and accelerators are characterized at 200 MeV protons or heavy ion beams, which gives thresholds and recovery behavior, not upset rates for any orbit or planetary surface [11][15][17]. The Coral accelerator, Snapdragon, TILE64 and GR740 entries are ground benchmarks or projections with no radiation campaign [13][14][18][19]. Part-level screening such as [28] omits upset and dose effects, and the board-level result in [11] shows that a part pass does not predict a board recovery path.

References

  1. Maimone, M., Cheng, Y. and Matthies, L. (2007). Two Years of Visual Odometry on the Mars Exploration Rovers . Journal of Field Robotics, 3. Source
    BibTeX
    @article{maimone2007two,
  title = {Two Years of Visual Odometry on the Mars Exploration Rovers},
  author = {Maimone, Mark and Cheng, Yang and Matthies, Larry},
  journal = {Journal of Field Robotics},
  volume = {24},
  number = {3},
  pages = {169--186},
  institution = {NASA Jet Propulsion Laboratory},
  year = {2007},
  doi = {10.1002/rob.20184},
  abstract = {Abstract NASA's two Mars Exploration Rovers (MER) have successfully demonstrated a robotic Visual Odometry capability on another world for the first time. This provides each rover with accurate knowledge of its position, allowing it to autonomously detect and compensate for any unforeseen slip encountered during a drive. It has enabled the rovers to drive safely and more effectively in highly sloped and sandy terrains and has resulted in increased mission science return by reducing the number of days required to drive into interesting areas. The MER Visual Odometry system comprises onboard software for comparing stereo pairs taken by the pointable mast‐mounted 45 deg FOV Navigation cameras (NAVCAMs). The system computes an update to the 6 degree of freedom rover pose ( x , y , z , roll, pitch, yaw) by tracking the motion of autonomously selected terrain features between two pairs of 256×256 stereo images. It has demonstrated good performance with high rates of successful convergence (97% on Spirit, 95% on Opportunity), successfully detected slip ratios as high as 125%, and measured changes as small as 2 mm, even while driving on slopes as high as 31 deg. Visual Odometry was used over 14% of the first 10.7 km driven by both rovers. During the first 2 years of operations, Visual Odometry evolved from an “extra credit” capability into a critical vehicle safety system. In this paper we describe our Visual Odometry algorithm, discuss several driving strategies that rely on it (including Slip Checks, Keep‐out Zones, and Wheel Dragging), and summarize its results from the first 2 years of operations on Mars. © 2006 Wiley Periodicals, Inc.}
}
  2. 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.}
}
  3. Makovsky, A., Ilott, P. and Taylor, J. (2009). Mars Science Laboratory Telecommunications System Design . Jet Propulsion Laboratory, California Institute of Technology, Article 14. Source
    BibTeX
    @techreport{makovsky2009mars,
  title = {Mars Science Laboratory Telecommunications System Design},
  author = {Makovsky, Andre and Ilott, Peter and Taylor, Jim},
  series = {DESCANSO Design and Performance Summary Series},
  number = {Article 14},
  institution = {Jet Propulsion Laboratory, California Institute of Technology},
  year = {2009},
  url = {https://descanso.jpl.nasa.gov/DPSummary/Descanso14_MSL_Telecom.pdf}
}
  4. Agrawal, J., Yelamanchili, A. and Chien, S. (2020). Using Explainable Scheduling for the Mars 2020 Rover Mission . arXiv preprint. Source
    BibTeX
    @article{agrawal2020explainable,
  title = {Using Explainable Scheduling for the Mars 2020 Rover Mission},
  author = {Agrawal, Jagriti and Yelamanchili, Amruta and Chien, Steve},
  journal = {arXiv preprint},
  year = {2020},
  doi = {10.48550/arxiv.2011.08733},
  abstract = {Understanding the reasoning behind the behavior of an automated scheduling system is essential to ensure that it will be trusted and consequently used to its full capabilities in critical applications. In cases where a scheduler schedules activities in an invalid location, it is usually easy for the user to infer the missing constraint by inspecting the schedule with the invalid activity to determine the missing constraint. If a scheduler fails to schedule activities because constraints could not be satisfied, determining the cause can be more challenging. In such cases it is important to understand which constraints caused the activities to fail to be scheduled and how to alter constraints to achieve the desired schedule. In this paper, we describe such a scheduling system for NASA's Mars 2020 Perseverance Rover, as well as Crosscheck, an explainable scheduling tool that explains the scheduler behavior. The scheduling system and Crosscheck are the baseline for operational use to schedule activities for the Mars 2020 rover. As we describe, the scheduler generates a schedule given a set of activities and their constraints and Crosscheck: (1) provides a visual representation of the generated schedule; (2) analyzes and explains why activities failed to schedule given the constraints provided; and (3) provides guidance on potential constraint relaxations to enable the activities to schedule in future scheduler runs.}
}
  5. Maurice, S., Wiens, R. C., Bernardi, P., Caïs, P., Robinson, S. H., Nelson, T., Gasnault, O., Reess, J.-M., Deleuze, M., Rull, F., Manrique, J. A., Abbaki, S., Anderson, R. B., André, Y., Angel, S., Arana, G., Battault, T., Beck, P., Benzerara, K., Bernard, S., Berthias, J.-P., Beyssac, O., Bonafous, M., Bousquet, B., Boutillier, M., Cadu, A., Castro, K., Chapron, F., Chide, B., Clark, K., Clavé, E., Clegg, S., Cloutis, E., Collin, C., Cordoba, E. C., Cousin, A., Dameury, J.-C., D'Anna, W., Daydou, Y., Debus, A., Deflores, L., Dehouck, E., Delapp, D., De Los Santos, G., Donny, C., Doressoundiram, A., Dromart, G., Dubois, B., Dufour, A., Dupieux, M., Egan, M., Ervin, J., Fabre, C., Fau, A., Fischer, W., Forni, O., Fouchet, T., Frydenvang, J., Gauffre, S., Gauthier, M., Gharakanian, V., Gilard, O., Gontijo, I., Gonzalez, R., Granena, D., Grotzinger, J., Hassen-Khodja, R., Heim, M., Hello, Y., Hervet, G., Humeau, O., Jacob, X., Jacquinod, S., Johnson, J. R., Kouach, D., Lacombe, G., Lanza, N., Lapauw, L., Laserna, J., Lasue, J., Le Deit, L., Le Mouélic, S., Le Comte, E., Lee, Q.-M., Legett, I. C., Leveille, R., Lewin, E., Leyrat, C., Lopez-Reyes, G., Lorenz, R., Lucero, B., Madariaga, J. M., Madsen, S., Madsen, M., Mangold, N., Manni, F., Mariscal, J.-F., Martinez-Frias, J., Mathieu, K., Mathon, R., McCabe, K. P., McConnochie, T., McLennan, S. M., Mekki, J., Melikechi, N., Meslin, P.-Y., Micheau, Y., Michel, Y., Michel, J. M., Mimoun, D., Misra, A., Montagnac, G., Montaron, C., Montmessin, F., Moros, J., Mousset, V., Morizet, Y., Murdoch, N., Newell, R. T., Newsom, H., Nguyen Tuong, N., Ollila, A. M., Orttner, G., Oudda, L., Pares, L., Parisot, J., Parot, Y., Pérez, R., Pheav, D., Picot, L., Pilleri, P., Pilorget, C., Pinet, P., Pont, G., Poulet, F., Quantin-Nataf, C., Quertier, B., Rambaud, D., Rapin, W., Romano, P., Roucayrol, L., Royer, C., Ruellan, M., Sandoval, B., Sautter, V., Schoppers, M. J., Schröder, S., Seran, H.-C., Sharma, S. K., Sobron, P., Sodki, M., Sournac, A., Sridhar, V., Standarovsky, D., Storms, S., Striebig, N., Tatat, M., Toplis, M., Torre-Fdez, I., Toulemont, N., Velasco, C., Veneranda, M., Venhaus, D., Virmontois, C., Viso, M., Willis, P. and Wong, K. (2021). The SuperCam Instrument Suite on the Mars 2020 Rover: Science Objectives and Mast-Unit Description . Space Science Reviews, 47. Source
    BibTeX
    @article{maurice2021supercam,
  title = {The SuperCam Instrument Suite on the Mars 2020 Rover: Science Objectives and Mast-Unit Description},
  author = {Maurice, Sylvestre and Wiens, Roger C. and Bernardi, Pernelle and Caïs, Phillippe and Robinson, Scott H. and Nelson, Tony and Gasnault, Olivier and Reess, Jean-Michel and Deleuze, Muriel and Rull, Fernando and Manrique, Jose Antonio and Abbaki, Sadok and Anderson, Ryan B. and André, Yves and Angel, S.M. and Arana, Gorka and Battault, T. and Beck, Pierre and Benzerara, Karim and Bernard, Sylvain and Berthias, J.-P. and Beyssac, Olivier and Bonafous, Marion and Bousquet, Bruno and Boutillier, M. and Cadu, A. and Castro, Kepa and Chapron, Frédéric and Chide, Baptiste and Clark, K. and Clavé, Elise and Clegg, S. and Cloutis, E. and Collin, Claude and Cordoba, Elizabeth C. and Cousin, A. and Dameury, J.-C. and D'Anna, W. and Daydou, Yves and Debus, Andre and Deflores, Lauren and Dehouck, Erwin and Delapp, Dorothea and De Los Santos, Greg and Donny, C. and Doressoundiram, Alain and Dromart, Gilles and Dubois, Bruno and Dufour, A. and Dupieux, M. and Egan, Miles and Ervin, Joan and Fabre, C. and Fau, Amaury and Fischer, Woodward and Forni, Olivier and Fouchet, Thierry and Frydenvang, Jens and Gauffre, S. and Gauthier, M. and Gharakanian, V. and Gilard, Olivier and Gontijo, Ivair and Gonzalez, R. and Granena, D. and Grotzinger, J. and Hassen-Khodja, Rafik and Heim, M. and Hello, Y. and Hervet, G. and Humeau, Olivier and Jacob, Xavier and Jacquinod, Sophie and Johnson, Jeffrey R. and Kouach, Driss and Lacombe, G. and Lanza, Nina and Lapauw, Laurent and Laserna, Javier and Lasue, J. and Le Deit, Laetitia and Le Mouélic, Stéphane and Le Comte, E. and Lee, Qiu-Mei and Legett, IV, C. and Leveille, Richard and Lewin, Eric and Leyrat, C. and Lopez-Reyes, Guillermo and Lorenz, R. and Lucero, Briana and Madariaga, Juan Manuel and Madsen, Soren and Madsen, M. and Mangold, N. and Manni, F. and Mariscal, J.-F. and Martinez-Frias, Jesus and Mathieu, K. and Mathon, R. and McCabe, Kevin P. and McConnochie, T. and McLennan, Scott M. and Mekki, J. and Melikechi, Noureddine and Meslin, Pierre-Yves and Micheau, Y. and Michel, Y. and Michel, John M. and Mimoun, David and Misra, A. and Montagnac, Gilles and Montaron, Christophe and Montmessin, Franck and Moros, J. and Mousset, V. and Morizet, Y. and Murdoch, Naomi and Newell, Raymond T. and Newsom, Horton and Nguyen Tuong, N. and Ollila, Ann M. and Orttner, G. and Oudda, L. and Pares, Laurent and Parisot, Jérôme and Parot, Yann and Pérez, René and Pheav, D. and Picot, L. and Pilleri, Paolo and Pilorget, C. and Pinet, P. and Pont, Gabriel and Poulet, F. and Quantin-Nataf, Cathy and Quertier, Benjamin and Rambaud, D. and Rapin, William and Romano, P. and Roucayrol, L. and Royer, C. and Ruellan, M. and Sandoval, B.F. and Sautter, Violaine and Schoppers, Marcel J. and Schröder, S. and Seran, H.-C. and Sharma, Shiv K. and Sobron, Pablo and Sodki, M. and Sournac, A. and Sridhar, Vishnu and Standarovsky, D. and Storms, Steven and Striebig, Nicolas and Tatat, M. and Toplis, M. and Torre-Fdez, Imanol and Toulemont, N. and Velasco, C. and Veneranda, Marco and Venhaus, Dawn and Virmontois, C. and Viso, M. and Willis, P. and Wong, K.W.},
  journal = {Space Science Reviews},
  volume = {217},
  number = {47},
  year = {2021},
  doi = {10.1007/s11214-021-00807-w},
  abstract = {Abstract On the NASA 2020 rover mission to Jezero crater, the remote determination of the texture, mineralogy and chemistry of rocks is essential to quickly and thoroughly characterize an area and to optimize the selection of samples for return to Earth. As part of the Perseverance payload, SuperCam is a suite of five techniques that provide critical and complementary observations via Laser-Induced Breakdown Spectroscopy (LIBS), Time-Resolved Raman and Luminescence (TRR/L), visible and near-infrared spectroscopy (VISIR), high-resolution color imaging (RMI), and acoustic recording (MIC). SuperCam operates at remote distances, primarily 2–7 m, while providing data at sub-mm to mm scales. We report on SuperCam’s science objectives in the context of the Mars 2020 mission goals and ways the different techniques can address these questions. The instrument is made up of three separate subsystems: the Mast Unit is designed and built in France; the Body Unit is provided by the United States; the calibration target holder is contributed by Spain, and the targets themselves by the entire science team. This publication focuses on the design, development, and tests of the Mast Unit; companion papers describe the other units. The goal of this work is to provide an understanding of the technical choices made, the constraints that were imposed, and ultimately the validated performance of the flight model as it leaves Earth, and it will serve as the foundation for Mars operations and future processing of the data.}
}
  6. Nolet, S. (2007). Development of a Guidance, Navigation and Control Architecture and Validation Process Enabling Autonomous Docking to a Tumbling Satellite. Source
    BibTeX
    @phdthesis{nolet2007development,
  title = {Development of a Guidance, Navigation and Control Architecture and Validation Process Enabling Autonomous Docking to a Tumbling Satellite},
  author = {Nolet, Simon},
  school = {Massachusetts Institute of Technology},
  type = {Ph.D. thesis},
  year = {2007},
  url = {https://dspace.mit.edu/handle/1721.1/38598}
}
  7. Miller, D. L. (2015). Development of Resource-Constrained Sensors and Actuators for In-Space Satellite Docking and Servicing. Source
    BibTeX
    @mastersthesis{miller2015development,
  title = {Development of Resource-Constrained Sensors and Actuators for In-Space Satellite Docking and Servicing},
  author = {Miller, Duncan L.},
  school = {Massachusetts Institute of Technology},
  type = {S.M. thesis},
  year = {2015},
  url = {https://dspace.mit.edu/handle/1721.1/98805}
}
  8. Aagren, T. S., Ruan, A. W., Malpica, C., Withrow-Maser, S. and Meyn, L. (2025). In-flight System Identification of the Ingenuity Mars Helicopter . AIAA SCITECH Forum, 20240014856. Source
    BibTeX
    @inproceedings{aagren2025flight,
  title = {In-flight System Identification of the Ingenuity Mars Helicopter},
  author = {Aagren, Tove S. and Ruan, Allen W. and Malpica, Carlos and Withrow-Maser, Shannah and Meyn, Larry},
  booktitle = {AIAA SCITECH Forum},
  number = {20240014856},
  institution = {NASA},
  year = {2025},
  doi = {10.2514/6.2025-0007},
  abstract = {The 68th and 69th flights of NASA’s Ingenuity Mars Helicopter marked the first dedicated system identification flights of an aerial vehicle on another planet. Chirp signals were injected into the swashplate cyclic controls for both legs of the two out-and-back flights. Frequency responses were computed from the flight data, using both the Direct Method (DM) and the Joint-Input-Output (JIO) approach, for the identification of stability and control derivatives in forward flight conditions. The resulting identified state-space models were compared against existing flight dynamics simulation models, showing excellent correlation in the higher frequency range. External disturbances were seen to introduce a bias in the identified lower frequency responses, which was partially mitigated using the JIO method. These findings will inform future modeling and flight testing efforts of Mars rotorcraft.}
}
  9. Withrow-Maser, S., Johnson, W., Tzanetos, T., Grip, H., Koning, W., Schatzman, N., Young, L., Chan, A., Ruan, A., Cummings, H., Allan, B., Malpica, C., Meyn, L., Pipenberg, B. and Keennon, M. (2023). Mars Sample Recovery Helicopter: Rotorcraft to Retrieve the First Samples from the Martian Surface . Vertical Flight Society Annual Forum and Technology Display, 20230005247. Source
    BibTeX
    @inproceedings{withrowmaser2023mars,
  title = {Mars Sample Recovery Helicopter: Rotorcraft to Retrieve the First Samples from the Martian Surface},
  author = {Withrow-Maser, Shannah and Johnson, Wayne and Tzanetos, Theodore and Grip, Havard and Koning, Witold and Schatzman, Natasha and Young, Larry and Chan, Athena and Ruan, Allen and Cummings, Haley and Allan, Brian and Malpica, Carlos and Meyn, Larry and Pipenberg, Benjamin and Keennon, Matthew},
  booktitle = {Vertical Flight Society Annual Forum and Technology Display},
  number = {20230005247},
  pages = {1-8},
  institution = {NASA Ames Research Center and Jet Propulsion Laboratory},
  year = {2023},
  doi = {10.4050/f-0079-2023-17969},
  abstract = {The Mars Sample Return Mission (MSR) will carry the next set of Mars helicopters, Sample Recovery Helicopters (SRHs), to the Martian surface. After successfully demonstrating extraterrestrial flight in 2021, Ingenuity has acted as a}
}
  10. Koontz, S. L., Suggs, R. M., Alred, J. W., Worthy, E. S., Boeder, P., Steagall, C. A., Hartman, W. A., Gingras, B. D. and Schmidl, W. D. (2018). The International Space Station Space Radiation Environment: Avionics Systems Performance in Low-Earth Orbit Single Event Effects (SEE) Environments . International Conference on Environmental Systems, ICES-2018-69. Source
    BibTeX
    @inproceedings{koontz2018international,
  title = {The International Space Station Space Radiation Environment: Avionics Systems Performance in Low-Earth Orbit Single Event Effects (SEE) Environments},
  author = {Koontz, Steven L. and Suggs, Robert M. and Alred, John W. and Worthy, Erica S. and Boeder, Paul and Steagall, Courtney A. and Hartman, William A. and Gingras, Benjamin D. and Schmidl, William D.},
  booktitle = {International Conference on Environmental Systems},
  number = {ICES-2018-69},
  address = {Albuquerque, New Mexico},
  year = {2018},
  url = {https://ttu-ir.tdl.org/items/7fb5d403-ad77-4f6b-9cff-c70af5c04802}
}
  11. Topper, A. D., Lauenstein, J.-M., Wilcox, E. P., Berg, M. D., Campola, M. J., Casey, M. C., Wyrwas, E. J., O'Bryan, M. V., Carstens, T. A., Fedele, C. M., Forney, J. D., Kim, H. S., Osheroff, J. M., Phan, A. M., Chaiken, M. F., Cochran, D. J., Pellish, J. A. and Majewicz, P. J. (2020). NASA Goddard Space Flight Center's Compendium of Radiation Effects Test Results . IEEE Radiation Effects Data Workshop. Source
    BibTeX
    @inproceedings{topper2020nasa,
  title = {NASA Goddard Space Flight Center's Compendium of Radiation Effects Test Results},
  author = {Topper, Alyson D. and Lauenstein, Jean-Marie and Wilcox, Edward P. and Berg, Melanie D. and Campola, Michael J. and Casey, Megan C. and Wyrwas, Edward J. and O'Bryan, Martha V. and Carstens, Thomas A. and Fedele, Caroline M. and Forney, James D. and Kim, Hak S. and Osheroff, Jason M. and Phan, Anthony M. and Chaiken, Max F. and Cochran, Donna J. and Pellish, Jonathan A. and Majewicz, Peter J.},
  booktitle = {IEEE Radiation Effects Data Workshop},
  pages = {1--12},
  year = {2020},
  doi = {10.1109/redw51883.2020.9325841},
  abstract = {Total ionizing dose, displacement damage dose, and single event effects testing were performed to characterize and determine the suitability of candidate electronics for NASA space utilization. Devices tested include FETs, flash memory, FPGAs, optoelectronics, digital, analog, and bipolar devices.}
}
  12. Whittaker, C. (2021). MR-AVI-0068 Radiation Survival Summary, Revision A . Carnegie Mellon University, MoonRanger Project. Source
    BibTeX
    @techreport{whittaker2021radiation,
  title = {MR-AVI-0068 Radiation Survival Summary, Revision A},
  author = {Whittaker, Chuck},
  institution = {Carnegie Mellon University, MoonRanger Project},
  month = {May},
  year = {2021},
  url = {https://labs.ri.cmu.edu/moonranger/wp-content/uploads/sites/24/2021/07/MR-AVI-0068_Radiation-Survival-Summary.pdf}
}
  13. Castilla-Arquillo, R., Perez-del-Pulgar, C. J., Paz-Delgado, G. J. and Gerdes, L. (2022). Hardware-accelerated Mars Sample Localization via deep transfer learning from photorealistic simulations . IEEE Robotics and Automation Letters, 4. Source
    BibTeX
    @article{castillaarquillo2022hardware,
  title = {Hardware-accelerated Mars Sample Localization via deep transfer learning from photorealistic simulations},
  author = {Castilla-Arquillo, Raul and Perez-del-Pulgar, Carlos J. and Paz-Delgado, Gonzalo J. and Gerdes, Levin},
  journal = {IEEE Robotics and Automation Letters},
  volume = {7},
  number = {4},
  pages = {12160--12167},
  year = {2022},
  doi = {10.1109/lra.2022.3219306},
  abstract = {The goal of the Mars Sample Return campaign is to collect soil samples from the surface of Mars and return them to Earth for further study. The samples will be acquired and stored in metal tubes by the Perseverance rover and deposited on the Martian surface. As part of this campaign, it is expected that the Sample Fetch Rover will be in charge of localizing and gathering up to 35 sample tubes over 150 Martian sols. Autonomous capabilities are critical for the success of the overall campaign and for the Sample Fetch Rover in particular. This work proposes a novel system architecture for the autonomous detection and pose estimation of the sample tubes. For the detection stage, a Deep Neural Network and transfer learning from a synthetic dataset are proposed. The dataset is created from photorealistic 3D simulations of Martian scenarios. Additionally, the sample tubes poses are estimated using Computer Vision techniques such as contour detection and line fitting on the detected area. Finally, laboratory tests of the Sample Localization procedure are performed using the ExoMars Testing Rover on a Mars-like testbed. These tests validate the proposed approach in different hardware architectures, providing promising results related to the sample detection and pose estimation.}
}
  14. Dunkel, E. R., Swope, J., Candela, A., West, L., Chien, S. A., Towfic, Z., Buckley, L., Romero-Cañas, J., Espinosa-Aranda, J. L., Hervas-Martin, E. and Fernandez, M. R. (2023). Benchmarking Deep Learning Models on Myriad and Snapdragon Processors Onboard the ISS . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{dunkel2023benchmarking,
  title = {Benchmarking Deep Learning Models on Myriad and Snapdragon Processors Onboard the ISS},
  author = {Dunkel, Emily R. and Swope, Jason and Candela, Alberto and West, Lauren and Chien, Steve A. and Towfic, Zaid and Buckley, Léonie and Romero-Cañas, Juan and Espinosa-Aranda, Jose Luis and Hervas-Martin, Elena and Fernandez, Mark R.},
  booktitle = {IEEE Aerospace Conference},
  publisher = {JPL Open Repository},
  year = {2023},
  doi = {10.48577/jpl.v0obta},
  abstract = {Future space missions can benefit from processing imagery onboard to detect science events, create insights, and respond autonomously. One of the challenges to this mission concept is that traditional space flight computing has limited capabilities because it is derived from much older computing to ensure reliable performance in the extreme environments of space, particularly radiation. Modern Commercial Off The Shelf (COTS) processors, such as the Movidius Myriad X and the Qualcomm Snapdragon, provide significant improvements in small Size Weight and Power (SWaP) packaging and offer direct hardware acceleration for deep neural networks. We deploy neural network models on these processors hosted by Hewlett Packard Enterprise’s Spaceborne Computer-2 onboard the International Space Station (ISS). We benchmark a variety of algorithms trained on visual, synthetic aperture radar (SAR), or spectroscopic data from Earth or Mars, and standard deep learning models for image classification. Models are run multiple times, and memory checkers are deployed to test for radiation effects.}
}
  15. Guertin, S. M. (2018). Guideline for Single-Event Effect (SEE) Testing of System on a Chip (SOC) Devices . NASA, 20190002148. Source
    BibTeX
    @techreport{guertin2018guideline,
  title = {Guideline for Single-Event Effect (SEE) Testing of System on a Chip (SOC) Devices},
  author = {Guertin, Steven M.},
  number = {20190002148},
  institution = {NASA},
  year = {2018},
  url = {https://ntrs.nasa.gov/citations/20190002148},
  abstract = {The use of complex single and multicore processors with significant cache memory, on-chip peripherals, memory controllers, and high speed input/output (IO) that integrate many of the parts of a traditional computer system is becoming more common in space applications. Such devices are often referred to as system on a chip devices (SOCs), even though the term is used somewhat inaccurately due to the lack of analog and mixed signal subcircuits. These devices are complex combinations of single- or multi-core processors with memory controllers, high-speed input/output (IO), and other peripheral structures that formerly would have been handled by off-chip resources. In the past the processors were tested for single event effects (SEE) separately, and the peripherals were often put into custom application-specific integrated circuits (ASICs) along with other resources required by the user. Performance and cost pressures have pushed commercial devices to incorporate many of the functional blocks into a single chip, an SOC. The NASA Electronic Parts and Packaging Program (NEPP) has been examining ways to perform SEE radiation hardness assurance (RHA) testing of these processor-centric SOCs to achieve reasonable understanding of their performance in space missions.}
}
  16. McClure, S. S., Allen, G. R., Irom, F., Scheick, L. Z., Adell, P. C. and Miyahira, T. F. (2010). Compendium of test results of recent single event effect tests conducted by the Jet Propulsion Laboratory . IEEE Radiation Effects Data Workshop. Source
    BibTeX
    @inproceedings{mcclure2010compendium,
  title = {Compendium of test results of recent single event effect tests conducted by the Jet Propulsion Laboratory},
  author = {McClure, Steven S. and Allen, Gregory R. and Irom, Farokh and Scheick, Leif Z. and Adell, Philippe C. and Miyahira, Tetsuo F.},
  booktitle = {IEEE Radiation Effects Data Workshop},
  pages = {6-6},
  publisher = {IEEE},
  year = {2010},
  doi = {10.1109/redw.2010.5619495},
  abstract = {This paper reports heavy ion and proton-induced single event effect (SEE) results from recent tests for a variety of microelectronic devices. The compendium covers devices tested over the last two years by the Jet Propulsion Laboratory.}
}
  17. Allen, G. R., Guertin, S. M., Scheick, L. Z., Irom, F. and Zajac, S. (2012). Compendium of recent test results of single event effects conducted by the Jet Propulsion Laboratory . IEEE Radiation Effects Data Workshop. Source
    BibTeX
    @inproceedings{allen2012compendium,
  title = {Compendium of recent test results of single event effects conducted by the Jet Propulsion Laboratory},
  author = {Allen, Gregory R. and Guertin, Steven M. and Scheick, Leif Z. and Irom, Farokh and Zajac, Stephanie},
  booktitle = {IEEE Radiation Effects Data Workshop},
  pages = {1-10},
  publisher = {IEEE},
  year = {2012},
  doi = {10.1109/redw.2012.6353747},
  abstract = {This paper reports heavy ion, proton, and laser induced single event effects results for a variety of microelectronic devices targeted for possible use in NASA spacecrafts. The compendium covers devices tested within the years of 2010 through 2012.}
}
  18. Towfic, Z. J., Ogbe, D., Sauvageau, J., Sheldon, D., Jongeling, A., Chien, S., Mirza, F., Dunkel, E., Swope, J., Ogut, M. and Cretu, V. (2022). Benchmarking and Testing of Qualcomm Snapdragon System-on-Chip for JPL Space Applications and Missions . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{towfic2022benchmarking,
  title = {Benchmarking and Testing of Qualcomm Snapdragon System-on-Chip for JPL Space Applications and Missions},
  author = {Towfic, Zaid J and Ogbe, Dennis and Sauvageau, Joe and Sheldon, Douglas and Jongeling, Andre and Chien, Steve and Mirza, Faiz and Dunkel, Emily and Swope, Jason and Ogut, Mehmet and Cretu, Vlad},
  booktitle = {IEEE Aerospace Conference},
  pages = {1-12},
  publisher = {IEEE},
  year = {2022},
  doi = {10.1109/aero53065.2022.9843518},
  abstract = {As some space missions become more challenging due to new environments, greater distances, or more limited size, weight, and power (SWaP) constraints, spacecraft avionics must adapt to allow the spacecraft to be more autonomous and agile‐‐‐eliminating the Spacecraft-Earth-Spacecraft feedback loop whenever possible. Prime examples of such missions include Aerobots (such as Ingenuity with extremely low SWaP constraints and demanding signal/image processing during flight) and landers in possibly hostile environments (such as a Europa lander mission, with limited communication capacity, high latency, and constrained power budget). To address these challenges, JPL worked with Qualcomm to demonstrate the use of their Snapdragon 801 system-on-chip (SoC) onboard the Ingenuity Helicopter on Mars. The Qualcomm Snapdragon SoC contains various subsystems, including an ARM cluster, a Graphics processing unit, a Digital Signal Processing subsystem, a Neural Processing Engine, Image Signal Processing subsystem, among others. Since the success of Ingenuity, JPL is continuing to work with Qualcomm to address other applications of the Snapdragon SoC technology. This includes the deployment of two 855 Snapdragon development boards onboard the International Space Station (ISS) for successful in-situ benchmarking of applications in space (beyond those tested on Ingenuity). In this paper, we will examine the performance of various applications that have been identified to benefit from greater onboard computational capability. These applications include (among others): machine vision algorithms that are expected to be critical in autonomous entry-descent-and-landing scenarios and real-time Aerobot flight navigation; Hyperspectral compression algorithms; Synthetic Aperture Radar Processing along with various instrument processing algorithms. We discuss how the infusion of Qualcomm's Snapdragon SoC is capable of enabling missions that may not have been able to achieve their goals with traditional flight computing. In addition, we also show that for some algorithms, the software implementation on the Snapdragon SoC outperforms traditional FPGA implementations.}
}
  19. Bornstein, B., Estlin, T., Clement, B. and Springer, P. (2011). Using a multicore processor for rover autonomous science . Aerospace Conference. Source
    BibTeX
    @inproceedings{bornstein2011multicore,
  title = {Using a multicore processor for rover autonomous science},
  author = {Bornstein, Benjamin and Estlin, Tara and Clement, Bradley and Springer, Paul},
  booktitle = {Aerospace Conference},
  pages = {1-9},
  publisher = {IEEE},
  year = {2011},
  doi = {10.1109/aero.2011.5747454}
}
  20. Dinkel, H., Di, J., Santos, J., Albee, K., Borges, P., Moreira, M., Alexandrov, O., Coltin, B. and Smith, T. (2023). Multi-Agent 3D Map Reconstruction and Change Detection in Microgravity with Free-Flying Robots . International Astronautical Congress, IAC-23,D1,6,1,x78669. Source
    BibTeX
    @inproceedings{dinkel2023multi,
  title = {Multi-Agent 3D Map Reconstruction and Change Detection in Microgravity with Free-Flying Robots},
  author = {Dinkel, Holly and Di, Julia and Santos, Jamie and Albee, Keenan and Borges, Paulo and Moreira, Marina and Alexandrov, Oleg and Coltin, Brian and Smith, Trey},
  booktitle = {International Astronautical Congress},
  number = {IAC-23,D1,6,1,x78669},
  publisher = {JPL Open Repository},
  year = {2023},
  doi = {10.48577/jpl.lbsjso},
  abstract = {Assistive free-flyer robots autonomously caring for future crewed outposts---such as NASA’s Astrobee robots on the International Space Station (ISS)---must be able to detect day-to-day interior changes to track inventory, detect and diagnose faults, and monitor the outpost status. This work presents a framework for multi-agent cooperative mapping and change detection to enable robotic maintenance of space outposts. One agent is used to reconstruct a 3D model of the environment from sequences of images and corresponding depth information. Another agent is used to scan the environment for inconsistencies against the 3D model. Change detection is validated using real image and pose data collected by Astrobee robots on Earth in a test environment and in space on the ISS. This work outlines the objectives, requirements, and algorithmic modules for the multi-agent reconstruction system, including recommendations for its use aboard future microgravity outposts.}
}
  21. Wronkiewicz, M., Lee, J., Lightholder, J., Doran, G., Mauceri, S., Schibler, T., Moorjani, E., Nadeau, J., Lindensmith, C. and Mandrake, L. (2023). Onboard Science Instrument Autonomy for the Detection of Microscopy Biosignatures on the Ocean Worlds Life Surveyor . AIAA Journal of Spacecraft and Rockets: MAPLD. Source
    BibTeX
    @article{wronkiewicz2023onboard,
  title = {Onboard Science Instrument Autonomy for the Detection of Microscopy Biosignatures on the Ocean Worlds Life Surveyor},
  author = {Wronkiewicz, Mark and Lee, Jake and Lightholder, Jack and Doran, Gary and Mauceri, Steffen and Schibler, Thomas and Moorjani, Eshaan and Nadeau, Jay and Lindensmith, Chris and Mandrake, Lukas},
  journal = {AIAA Journal of Spacecraft and Rockets: MAPLD},
  publisher = {JPL Open Repository},
  year = {2023},
  doi = {10.48577/jpl.mflyra}
}
  22. Alexandrov, O., Barlow, J., Benavides, J., Bualat, M., Carlino, R., Coltin, B., Cortez, J., Daley, E., Feller, J., Flückiger, L., Fong, T., Fusco, J., Garcia Ruiz, R., Hamilton, K., Kanis, S., Katterhagen, A., Kim, Y., Love, J. F., McIntyre, M., McLachlan, B., Mora Vargas, A., Moratto, Z., Moreira, M., Morse, T., Orosco, H., Park, I.-W., Provencher, C., Sanchez, H., Sharif, K., Smith, E., Smith, T., Soussan, R., Symington, A., Talavera, R. O., To, V., Wheeler, D. and Yoo, J. (2026). Astrobee: Free-Flying Robots for the International Space Station . IEEE Transactions on Field Robotics. Source
    BibTeX
    @article{alexandrov2026astrobee,
  title = {Astrobee: Free-Flying Robots for the International Space Station},
  author = {Alexandrov, Oleg and Barlow, Jonathan and Benavides, Jose and Bualat, Maria and Carlino, Roberto and Coltin, Brian and Cortez, Jose and Daley, Earl and Feller, Jeffrey and Flückiger, Lorenzo and Fong, Terrence and Fusco, Jesse and Garcia Ruiz, Ruben and Hamilton, Kathryn and Kanis, Simeon and Katterhagen, Aric and Kim, Yunkyung and Love, John F. and McIntyre, Michael and McLachlan, Blair and Mora Vargas, Andres and Moratto, Zack and Moreira, Marina and Morse, Theodore and Orosco, Henry and Park, In-Won and Provencher, Christopher and Sanchez, Hugo and Sharif, Khaled and Smith, Ernest and Smith, Trey and Soussan, Ryan and Symington, Andrew and Talavera, Rafael Omar and To, Vinh and Wheeler, DW and Yoo, Jongwoon},
  journal = {IEEE Transactions on Field Robotics},
  year = {2026},
  url = {https://ntrs.nasa.gov/citations/20260001396},
  abstract = {The Astrobees are free-flying robots that operate inside the International Space Station (ISS) and were launched to the ISS
in 2019. Since then they have successfully performed hundreds of activities in space supporting almost two dozen separate
research projects. The robots were designed to overcome multiple challenges unique to the ISS environment, including safety,
upgradeability and maintainability, limited mass and computation, and unique localization challenges from lack of gravity and a
constantly changing environment. This article provides an overview of Astrobee, from hardware and software design to deployment
results and activities.}
}
  23. Maimone, M. W., Leger, P. C. and Biesiadecki, J. J. (2007). Overview of the Mars Exploration Rovers' Autonomous Mobility and Vision Capabilities . IEEE International Conference on Robotics and Automation, Space Robotics Workshop. Source
    BibTeX
    @inproceedings{maimone2007overview,
  title = {Overview of the Mars Exploration Rovers' Autonomous Mobility and Vision Capabilities},
  author = {Maimone, Mark W. and Leger, P. Chris and Biesiadecki, Jeffrey J.},
  booktitle = {IEEE International Conference on Robotics and Automation, Space Robotics Workshop},
  address = {Rome, Italy},
  year = {2007},
  url = {https://www-robotics.jpl.nasa.gov/media/documents/mer_autonomy_icra_2007.pdf}
}
  24. 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.}
}
  25. Greco, M. E. and Snyder, J. F. (2005). Operational Modification of the Mars Exploration Rovers Flight Software . IEEE International Conference on Systems, Man and Cybernetics. Source
    BibTeX
    @inproceedings{greco2005operational,
  title = {Operational Modification of the Mars Exploration Rovers Flight Software},
  author = {Greco, Martin E. and Snyder, Joseph F.},
  booktitle = {IEEE International Conference on Systems, Man and Cybernetics},
  address = {Waikoloa, Hawaii},
  year = {2005},
  url = {https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=hdl:2014/37496}
}
  26. Reeves, G. E. and Neilson, T. A. (2005). The Mars Rover Spirit FLASH Anomaly . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{reeves2005mars,
  title = {The Mars Rover Spirit FLASH Anomaly},
  author = {Reeves, Glenn E. and Neilson, Tracy A.},
  booktitle = {IEEE Aerospace Conference},
  pages = {4186-4199},
  address = {Big Sky, Montana},
  year = {2005},
  doi = {10.1109/aero.2005.1559723},
  abstract = {The Mars Exploration Rover "Spirit" suffered a debilitating anomaly that prevented communication with Earth for several anxious days. With the eyes of the world upon us, the anomaly team used each scrap of information, our knowledge of the system, and sheer determination to analyze and fix the problem, then return the vehicle to normal operation. This paper will discuss the Spirit FLASH anomaly, including the drama of the investigation, the root cause and the lessons learned from the experience}
}
  27. 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.}
}
  28. Daniel, A. C. and Allen, G. R. (2018). Heavy-Ion Test Results of Several Commercial Components for Use in a JPL Class D Interplanetary Mission Payload . JPL Open Repository. Source
    BibTeX
    @inproceedings{daniel2018heavy,
  title = {Heavy-Ion Test Results of Several Commercial Components for Use in a JPL Class D Interplanetary Mission Payload},
  author = {Daniel, Andrew C. and Allen, Gregory R.},
  publisher = {JPL Open Repository},
  year = {2018},
  url = {https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=hdl:2014/48478}
}
  29. Verma, V., Nash, J., Saldyt, L., Dwight, Q., Wang, H., Myint, S., Biesiadecki, J., Maimone, M., Tumbar, A., Ansar, A., Kubiak, G. and Hogg, R. (2024). Enabling Long and Precise Drives for the Perseverance Mars Rover via Onboard Global Localization . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{verma2024enabling,
  title = {Enabling Long and Precise Drives for the Perseverance Mars Rover via Onboard Global Localization},
  author = {Verma, Vandi and Nash, Jeremy and Saldyt, Lucas and Dwight, Quintin and Wang, Haoda and Myint, Steven and Biesiadecki, Jeffrey and Maimone, Mark and Tumbar, Andrei and Ansar, Adnan and Kubiak, Gerik and Hogg, Robert},
  booktitle = {IEEE Aerospace Conference},
  address = {Big Sky, Montana},
  year = {2024},
  url = {https://www-robotics.jpl.nasa.gov/media/documents/2024_Global_Localization_IEEE_Aero.pdf}
}
  30. Nash, J., Verma, V., Graser, E., Wang, H., Kubiak, G., Maimone, M., Myint, S., Biesiadecki, J. and Romano, P. (2026). A Software-Based Approach to Radiation Mitigation for Planetary Mission . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{nash2026software,
  title = {A Software-Based Approach to Radiation Mitigation for Planetary Mission},
  author = {Nash, Jeremy and Verma, Vandi and Graser, Evan and Wang, Haoda and Kubiak, Gerik and Maimone, Mark and Myint, Steven and Biesiadecki, Jeffrey and Romano, Philip},
  booktitle = {IEEE Aerospace Conference},
  publisher = {JPL Open Repository},
  year = {2026},
  doi = {10.48577/jpl.okks5v},
  abstract = {The Perseverance Mars rover needs to drive long distances between regions of scientific interest to collect a diverse set of samples. Position knowledge is needed for navigating to the region of interest. Planetary mobile robots accumulate position uncertainty as they move. Globally localizing the robot to an orbital map of Mars removes this uncertainty. Previously this was performed manually on the ground by humans for mobile surface and aerial robots. This can be accurate but requires communication between planets. This takes significant time and the need for it limits how far Perseverance can autonomously navigate without ground-in-the-loop.The Perseverance Mars rover is in the process of deploying a new onboard global localization capability that has the potential for significantly improving long-distance autonomous navigation. It allows the rover to precisely determine its position by comparing panoramic images from its navigation cameras with high-resolution orbital maps. This paper provides an outline of the development and successful deployment of onboard global localization system on the Perseverance Mars rover and the challenges encountered. Leveraging a fast, commercial off-the-shelf (COTS) Snapdragon 801 processor from the Ingenuity Helicopter Base Station, the system performs complex image-processing tasks to accurately determine the rover's position relative to orbital maps. This approach overcomes the limitations of the rover's slower, radiation-hardened processor, and is a paradigm shift in planetary robotics.}
}
  31. Powell, W. A., Johnson, M. A., Wilmot, J., Some, R., Gostelow, K. P., Reeves, G. and Doyle, R. J. (2011). Enabling future robotic missions with multicore processors . Infotech@Aerospace. Source
    BibTeX
    @inproceedings{powell2011enabling,
  title = {Enabling future robotic missions with multicore processors},
  author = {Powell, Wesley A. and Johnson, Michael A. and Wilmot, Jonathan and Some, Raphael and Gostelow, Kim P. and Reeves, Glenn and Doyle, Richard J.},
  booktitle = {Infotech@Aerospace},
  publisher = {American Institute of Aeronautics and Astronautics},
  year = {2011},
  doi = {10.2514/6.2011-1447}
}
  32. Alexander, J. W., Clement, B. J., Gostelow, K. P. and Lai, J. Y. (2012). Fault mitigation schemes for future spaceflight multicore processors . Infotech@Aerospace. Source
    BibTeX
    @inproceedings{alexander2012fault,
  title = {Fault mitigation schemes for future spaceflight multicore processors},
  author = {Alexander, James W and Clement, Bradley J. and Gostelow, Kim P. and Lai, John Y.},
  booktitle = {Infotech@Aerospace},
  publisher = {American Institute of Aeronautics and Astronautics},
  year = {2012},
  doi = {10.2514/6.2012-2509},
  abstract = {Future planetary exploration missions demand significant advances in on-board computing capabilities over current avionics architectures based on a single-core processing element. The state-of-the-art multi-core processor provides much promise in meeting such challenges while introducing new fault tolerance problems when applied to space missions. Software-based schemes are being presented in this paper that can achieve system-level fault mitigation beyond that provided by radiation-hard-by-design (RHBD). For mission and time critical applications such as the Terrain Relative Navigation (TRN) for planetary or small body navigation, and landing, a range of fault tolerance methods can be adapted by the application. The software methods being investigated include Error Correction Code (ECC) for data packet routing between cores, virtual network routing, Triple Modular Redundancy (TMR), and Algorithm-Based Fault Tolerance (ABFT). A robust fault tolerance framework that provides fail-operational behavior under hard real-time constraints and graceful degradation will be demonstrated using TRN executing on a commercial Tilera(R) processor with simulated fault injections.}
}
  33. Canham, T. K. (2022). The Mars Ingenuity Helicopter - A Victory for Open-Source Software . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{canham2022mars,
  title = {The Mars Ingenuity Helicopter - A Victory for Open-Source Software},
  author = {Canham, Timothy K},
  booktitle = {IEEE Aerospace Conference},
  pages = {01-11},
  publisher = {IEEE},
  year = {2022},
  doi = {10.1109/aero53065.2022.9843438}
}