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Data handling

Onboard storage, file systems, compression, prioritization and the downlink budget that decides which measurements a mission actually keeps.

A surface vehicle generates more data than it can send. The return link is set by antenna geometry, relay orbiter geometry and buffer allocations, and the cameras and instruments are sized for what the vehicle can sense, not for what the link carries. On the Mars Exploration Rovers, relay through orbiters carried 89 percent of the returned data by the end of the 90-sol primary mission, at an average of about 56 Mb per sol per rover through Odyssey [3]. Data handling is the set of decisions that fit the first quantity into the second: what is stored and where, how hard it is compressed, which products leave first, and how the link itself is scheduled. The flight computer adds a second constraint: the RAD6000 class processors that flew on MER and MSL run at 20 MIPS, so any method has to fit in minutes of processor time and a small memory [21].

MER, 2004. Image compression was the main tool, with ICER and LOCO used from the first sols [1]. ICER, a progressive wavelet compressor with segment-based error containment, averaged 1.13 bits per pixel over 5132 images in the first month, against 6.24 bits per pixel for modified LOCO lossless over 489 images [1]. The design rationale and the pre-flight benchmark on Mars Pathfinder images are in [2]. The rovers also sent a 64 by 64 thumbnail of every image at about 650 bytes [1]. Odyssey’s allocation was 120 Mb per rover [3].

Storage faults, MER and MSL. Spirit was effectively lost for three sols after a defect in the file system library, in which deleted-file entries remained in a RAM-resident structure and exhausted the memory needed to mount the volume at boot [4][25]. Curiosity’s A-side computer was recovered in a flight software build that moved the file system from NAND flash into half of the NOR flash, cutting usable volume by about 99 percent, from 2 GB to 64 MB [5]. Mars 2020 inherited and selectively rewrote the MSL data management and file system infrastructure [6]. Perseverance keeps four locations for critical files, none synchronized automatically, so every parameter change must be applied to the backup by ground command [7].

MSL, 2012 onward. Mastcam and MARDI returned most images as lossy JPEG with a lossless option [12]. AEGIS autonomous target selection has been in routine operations since sol 1343, at a cost of a few minutes of plan time [18]. On the ground side, assessing whether the previous drive executed nominally went from a manual task to one that is more than 80 percent automatic, with 13 of 16 reported aspects automatable [19].

Perseverance, 2021 onward. Relay planning precomputes data volume for every overflight at every allowable rate and duration, then filters against pass count, volume and latency limits [29]. LDPC coding was commissioned on the Mars Relay Network in 2021: four MAVEN demonstration overflights returned 70 percent more data than convolutional coding predicts, and one overflight returned 2340.2 Mbits [29]. The Rapid Traverse Campaign planned 94.8 percent of 5,063.4 m autonomously, which moved the saved plan time into driving [24].

EO-1, 2003 onward. The Autonomous Sciencecraft Experiment ran onboard science analysis, planning and execution on a flight computer with tight memory and processor limits [20]. It is the main flown precedent for onboard data selection outside the rovers.

Standard compression. The CCSDS Blue Books standardize an image compressor and a Rice-based lossless compressor [8][9]. ICER-3D extends the wavelet approach to hyperspectral cubes and has been shown as a ground analysis, not as flight software [11]. Status: the standards are published; ICER-3D is ground only.

Onboard prioritization by content. OASIS proposed ranking navigation images for downlink by analyzing science content on board [14], with rock-based ranking by target signature, novelty or representative sampling [15] and caption-based ranking against scientist text queries [16]; SCOTI is the captioning version, tested in a simulator [16]. Status: presentations, ground tests and simulation. A recent framework, SYNOPSIS, is a C library that runs science-autonomy algorithms, scores each observation for science utility and diversity, and ranks products by a maximum marginal relevance rule. It was integrated into cFS and F Prime flight software and exercised in a simulator on archived, already-downlinked MSL data; tests on flight-like processors are listed as future work [27]. Autonomous detection of microscopy features and summarization reached average compression ratios of 1888 and 2247 on a flight-like processor in analog testing [17].

Faster processors for perception-driven selection. The AEGIS rock-detection front end takes 10 to 15 minutes on the 20 MIPS RAD6000, and a 64-core ground-test port reduced it to 2.9 s on one core [21]. Status: ground test.

Command-to-product tracing. Ground tooling associates each downlinked product with the uplink command that produced it, using an identifier embedded in product metadata; this was demonstrated in a 2001 field test, not on a flown vehicle [13].

Delay-tolerant file transfer. CFDP defines acknowledged and unacknowledged file delivery over long-delay links [10]. Delay-tolerant networking was simulated for Mars relay scenarios [22] and certified in ground test for the International Space Station [23]. Neither has been reported as a surface-rover data path.

Relay network growth. A notional next-generation Mars relay network of three orbiters at about 6000 km with directional X-band proximity links is a planning proposal with no link budget [28]. The Mars Sample Return campaign concept uses a relay allocation tool for three co-located assets near Jezero, modeled under assumed inputs [30]. The International Mars Ice Mapper study assesses relay and direct-to-Earth communications trades as a concept, with computed link budgets only [31].

QuantityValueSource
ICER mean rate, MER first month1.13 bits/pixel over 5132 images[1]
Modified LOCO lossless mean rate6.24 bits/pixel over 489 images[1]
ICER lossless vs LOCO, six Pancam frames4.50 vs 4.53 bits/pixel[1]
MER thumbnail sizeabout 650 bytes[1]
MER relay share of returned data89 percent at sol 90[3]
MER Odyssey allocation120 Mb per rover[3]
Curiosity file system after recovery64 MB, down from 2 GB[5]
Relay network return, late 2015561 Mb per day over 446 overflights in three months[26]
LDPC gain on MAVEN overflights70 percent over convolutional prediction[29]
Single Perseverance-MAVEN overflight2340.2 Mbits[29]
AEGIS rock detection, RAD6000 vs 64-core port10 to 15 minutes vs 2.9 s[21]
Rapid Traverse autonomy94.8 percent of 5,063.4 m[24]

On a solar-powered rover the protection backbone is the autonomous shutdown and wakeup cycle rather than a safe mode [25]. File system faults in [4] and [5] show how a storage defect propagates into the reset behavior that cycle depends on.

Compression statistics for MER cover the first month of operations on early-mission terrain and reflect operator-set byte quotas, not image content [1]. The ICER benchmark rests on six Mars Pathfinder images, and the authors note that PSNR is a poor proxy for the scientists’ ranking of filters [2]. The flight rate figures therefore do not transfer to other cameras or terrain. Relay volumes are specific to the Odyssey and Global Surveyor orbits and do not generalize to other constellations [3]. The relay snapshot is read from a single figure [26], and the LDPC gain is measured against predicted, not paired, convolutional passes [29]. Most onboard prioritization methods have not flown: the caption, novelty and signature rankings are presentation, simulation or ground-test results [15][16], the microscopy summarization was tested in analog conditions [17], and SYNOPSIS reports no onboard runtime, memory or power figures [27]. The relay concept papers contain assumptions and computed budgets, not measurements [28][30][31]. The corpus holds no flown comparison of ground-directed and onboard prioritization on the same downlink budget, and no source cited here covers storage reliability under radiation beyond the specific anomalies above.

References

  1. Kiely, A. and Klimesh, M. (2004). Preliminary Image Compression Results from the Mars Exploration Rovers . IPN Progress Report. Source
    BibTeX
    @article{kiely2004preliminary,
      title = {Preliminary Image Compression Results from the Mars Exploration Rovers},
      author = {Kiely, A. and Klimesh, M.},
      journal = {IPN Progress Report},
      volume = {42-156},
      institution = {Jet Propulsion Laboratory},
      year = {2004},
      url = {https://ipnpr.jpl.nasa.gov/progress_report/42-156/156I.pdf}
    }
  2. Kiely, A. and Klimesh, M. (2003). The ICER Progressive Wavelet Image Compressor . IPN Progress Report. Source
    BibTeX
    @article{kiely2003icer,
      title = {The ICER Progressive Wavelet Image Compressor},
      author = {Kiely, A. and Klimesh, M.},
      journal = {IPN Progress Report},
      volume = {42-155},
      institution = {Jet Propulsion Laboratory},
      year = {2003},
      url = {https://ipnpr.jpl.nasa.gov/progress_report/42-155/155J.pdf}
    }
  3. Taylor, J., Makovsky, A., Barbieri, A., Tung, R., Estabrook, P. and Thomas, A. G. (2014). Mars Exploration Rover Telecommunications . Deep Space Communications. Source
    BibTeX
    @incollection{taylor2014mars,
      title = {Mars Exploration Rover Telecommunications},
      author = {Taylor, Jim and Makovsky, Andre and Barbieri, Andrea and Tung, Ramona and Estabrook, Polly and Thomas, A. Gail},
      booktitle = {Deep Space Communications},
      series = {DESCANSO Design and Performance Summary Series},
      publisher = {Jet Propulsion Laboratory, California Institute of Technology},
      chapter = {7},
      year = {2014},
      url = {https://descanso.jpl.nasa.gov/monograph/series13/DeepCommo_Chapter7--141030.pdf}
    }
  4. 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}
    }
  5. Holloway, A., Peper, N., Anabtawi, A., Quade, J. and Byrne, D. (2022). Building a Lifeboat: MSL's Uplink and Installation Campaign to Restore a Failing Backup Computer . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{holloway2022building,
      title = {Building a Lifeboat: MSL's Uplink and Installation Campaign to Restore a Failing Backup Computer},
      author = {Holloway, Alexandra and Peper, Nick and Anabtawi, Aseel and Quade, Jackson and Byrne, DJ},
      booktitle = {IEEE Aerospace Conference},
      pages = {1-9},
      address = {Big Sky, Montana},
      year = {2022},
      doi = {10.1109/aero53065.2022.9843266},
      abstract = {Flight software updates are among the hardest and most dangerous activities for the Mars Science Laboratory (MSL) Curiosity team. While danger is often mitigated by backups, fallback strategies, and incremental installation with ground-in-the-loop cycles which provide a safety net for the installation process, the software update described in this paper was unable to use many of the common practices due to the nature of the fault addressed by the update. The MSL rover (landed August 2012) encountered a problem with one of its computer's non-volatile storage chips in 2019, requiring a swap to its backup computer and an urgent software upgrade called R-Hope. R-Hope, a lifeboat to be used in the event of primary computer issues, was written, tested, and sent to the rover in lightning speed of just 19 months. Multi-mission and team coordination allowed the 49 flight software image files to be uplinked to the rover over a 6-week period, using multiple paths and backup options for speedy delivery. In the end, the R-Hope software upgrade returned the computer to operation as a backup flight computer. The flight software transition was designed to impact science return as little as possible, and installation plans included science activities for the majority of MSL instruments. This paper describes the uplink and installation campaigns for R-Hope, and discusses the notable lessons learned by the operations team.}
    }
  6. Girerd, A. R., Kuhn, S., Roth, B., Gaines, D., Scandore, S., Cummings, D., Mendoza, R., Lefland, M., Bareh, M., Siegfriedt, R., Lenda, M., Reich, K., Shah, B. and Bohannon, E. (2022). Cross-Cutting Flight Infrastructure Improvements on M2020 . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{girerd2022cross,
      title = {Cross-Cutting Flight Infrastructure Improvements on M2020},
      author = {Girerd, Andre R and Kuhn, Stephen and Roth, Brian and Gaines, Dan and Scandore, Steve and Cummings, David and Mendoza, Ricardo and Lefland, Mallory and Bareh, Magdy and Siegfriedt, Rebekah and Lenda, Matthew and Reich, Kevin and Shah, Biren and Bohannon, Emily},
      booktitle = {IEEE Aerospace Conference},
      pages = {1-15},
      publisher = {IEEE},
      year = {2022},
      doi = {10.1109/aero53065.2022.9843523},
      abstract = {Mars2020 (M2020) was formulated as a mission that leveraged as much Mars Science Laboratory (MSL) heritage as possible, while focusing major new development efforts on the original and unique elements needed to accomplish the different mission objectives. Well publicized examples of high profile new developments include precision landing, the sampling and caching system, the specific instrument suite, improved mobility via Autonomous Navigation, and later the addition of the Ingenuity helicopter. Less well known are the refinements to the core flight infrastructure, primarily in the cross-cutting functions of Telecom, Avionics, Data Management, Communications Behaviors, and Parameter Management. These enhancements are introduced predominately via flight software, and represent increases in capability that justified their inclusion in an otherwise heritage-focused project environment. Perseverance's cross-cutting flight infrastructure improvements fall into and across the following five categories. First is a trimming of the software footprint of infrastructure modules, in order to make room for memory demands elsewhere in the system. Second is the minimization of data volume to be downlinked, through various methods such as the incorporation of new compression options. Third is the maximization of the available downlink bandwidth for data, by curtailing content-less data (fill) and introducing an improved UHF proximity link protocol. Fourth is a reduction in vulnerabilities, through increased file system redundancy, robustness, and software process monitoring. Fifth is an increase in operations efficiency by lowering file system mount times, improving parallelism between simultaneous events, minimizing the time to recover from file system errors, streamlining the purging of obsolete data, and reducing the number of commands to service parameters by a factor of 100. Individually, none of the cross-cutting infrastructure improvements are likely to garner headlines, but collectively they appreciably improve the safety and operability of Perseverance over its predecessor. This paper will describe the improvements, their promise, and where applicable, their actual impact in operations.}
    }
  7. Ruderman, E. (2024). Redundant Flight Computer and File Partition Maintenance Design for the Mars2020 Mission . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{ruderman2024redundant,
      title = {Redundant Flight Computer and File Partition Maintenance Design for the Mars2020 Mission},
      author = {Ruderman, Evan},
      booktitle = {IEEE Aerospace Conference},
      publisher = {JPL Open Repository},
      year = {2024},
      doi = {10.48577/jpl.pz8dkx}
    }
  8. CCSDS. (2017). Image Data Compression . Consultative Committee for Space Data Systems, CCSDS 122.0-B-2, Blue Book. Source
    BibTeX
    @techreport{ccsds2017image,
      title = {Image Data Compression},
      author = {{CCSDS}},
      number = {CCSDS 122.0-B-2, Blue Book},
      institution = {Consultative Committee for Space Data Systems},
      year = {2017},
      url = {https://ccsds.org/Pubs/122x0b2e1.pdf}
    }
  9. CCSDS. (2020). Lossless Data Compression . Consultative Committee for Space Data Systems, CCSDS 121.0-B-3, Blue Book. Source
    BibTeX
    @techreport{ccsds2020lossless,
      title = {Lossless Data Compression},
      author = {{CCSDS}},
      number = {CCSDS 121.0-B-3, Blue Book},
      institution = {Consultative Committee for Space Data Systems},
      year = {2020},
      url = {https://ccsds.org/Pubs/121x0b3.pdf}
    }
  10. CCSDS. (2020). CCSDS File Delivery Protocol (CFDP) . Consultative Committee for Space Data Systems, CCSDS 727.0-B-5, Blue Book. Source
    BibTeX
    @techreport{ccsds2020cfdp,
      title = {CCSDS File Delivery Protocol (CFDP)},
      author = {{CCSDS}},
      number = {CCSDS 727.0-B-5, Blue Book},
      institution = {Consultative Committee for Space Data Systems},
      year = {2020},
      url = {https://ccsds.org/Pubs/727x0b5e1.pdf}
    }
  11. Kiely, A., Klimesh, M., Xie, H. and Aranki, N. (2006). ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images . IPN Progress Report. Source
    BibTeX
    @article{kiely2006icer3d,
      title = {ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images},
      author = {Kiely, A. and Klimesh, M. and Xie, Heping and Aranki, N.},
      journal = {IPN Progress Report},
      volume = {42-164},
      institution = {Jet Propulsion Laboratory},
      year = {2006},
      url = {https://ipnpr.jpl.nasa.gov/progress_report/42-164/164A.pdf}
    }
  12. Malin, M. C., Ravine, M. A., Caplinger, M. A., Ghaemi, F. T., Schaffner, J. A., Maki, J. N., Bell III, J. F., Cameron, J. F., Dietrich, W. E., Edgett, K. S., Edwards, L., Garvin, J. B., Hallet, B., Herkenhoff, K. E., Heydari, E., Kah, L. C., Lemmon, M. T., Minitti, M. E., Olson, T., Parker, T. J., Rowland, S. K., Schieber, J., Sletten, R., Sullivan, R., Sumner, D. Y., Yingst, R. A., Duston, B., McNair, S. and Jensen, E. (2017). The Mars Science Laboratory (MSL) Mast cameras and Descent imager: I. Investigation and instrument descriptions . Earth and Space Science, 8. Source
    BibTeX
    @article{malin2017mars,
      title = {The Mars Science Laboratory (MSL) Mast cameras and Descent imager: I. Investigation and instrument descriptions},
      author = {Malin, Michal C. and Ravine, Michael A. and Caplinger, Michael A. and Ghaemi, F. Tony and Schaffner, Jacob A. and Maki, Justin N. and Bell III, James F. and Cameron, James F. and Dietrich, William E. and Edgett, Kenneth S. and Edwards, Laurence and Garvin, James B. and Hallet, B. and Herkenhoff, K. E. and Heydari, Ezat and Kah, Linda C. and Lemmon, Mark T. and Minitti, Michelle E. and Olson, T. and Parker, Timothy J. and Rowland, Scott K. and Schieber, Juergen and Sletten, Ron and Sullivan, R. and Sumner, Dawn Y. and Yingst, R. Aileen and Duston, Brian and McNair, Sean and Jensen, Elsa},
      journal = {Earth and Space Science},
      volume = {4},
      number = {8},
      pages = {506-539},
      publisher = {American Geophysical Union (AGU)},
      year = {2017},
      doi = {10.1002/2016ea000252},
      abstract = {Abstract The Mars Science Laboratory Mast camera and Descent Imager investigations were designed, built, and operated by Malin Space Science Systems of San Diego, CA. They share common electronics and focal plane designs but have different optics. There are two Mastcams of dissimilar focal length. The Mastcam‐34 has an f /8, 34 mm focal length lens, and the M‐100 an f /10, 100 mm focal length lens. The M‐34 field of view is about 20° × 15° with an instantaneous field of view (IFOV) of 218 μrad; the M‐100 field of view (FOV) is 6.8° × 5.1° with an IFOV of 74 μrad. The M‐34 can focus from 0.5 m to infinity, and the M‐100 from ~1.6 m to infinity. All three cameras can acquire color images through a Bayer color filter array, and the Mastcams can also acquire images through seven science filters. Images are ≤1600 pixels wide by 1200 pixels tall. The Mastcams, mounted on the ~2 m tall Remote Sensing Mast, have a 360° azimuth and ~180° elevation field of regard. Mars Descent Imager is fixed‐mounted to the bottom left front side of the rover at ~66 cm above the surface. Its fixed focus lens is in focus from ~2 m to infinity, but out of focus at 66 cm. The f /3 lens has a FOV of ~70° by 52° across and along the direction of motion, with an IFOV of 0.76 mrad. All cameras can acquire video at 4 frames/second for full frames or 720p HD at 6 fps. Images can be processed using lossy Joint Photographic Experts Group and predictive lossless compression.}
    }
  13. Backes, P. G., Norris, J. S., Powell, M. and Steinke, R. (2002). Relating downlink products to uplink commands in Mars Rover operations . Proceedings, IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{backes2002relating,
      title = {Relating downlink products to uplink commands in Mars Rover operations},
      author = {Backes, P. G. and Norris, J. S. and Powell, M. and Steinke, R.},
      booktitle = {Proceedings, IEEE Aerospace Conference},
      volume = {7},
      pages = {7-3257-7-3264},
      year = {2002},
      doi = {10.1109/aero.2002.1035301},
      abstract = {Downlink data products in Mars rover missions need to be associated with their uplink commanded target locations and the uplink commands that produced them. A system for automatically associating downlink data products with uplink commands and targets has been developed and used in a terrestrial rover field test. HTML reports viewable in a browser are automatically generated to relate downlink data products with the uplink sequence elements that produced them. The approach assumes that there is only one sequence thread being executed on the rover. This assumption is not true for the 2003 Mars Exploration Rover mission, so the approach cannot be used directly in the MER mission.}
    }
  14. Castano, R. and Anderson, R. (2002). Rover traverse science - the opportunities and the challenges.. dataverse.jpl.nasa.gov/dataset.xhtml
    BibTeX
    @misc{castano2002rover,
      title = {Rover traverse science - the opportunities and the challenges.},
      author = {Castano, Rebecca and Anderson, Robert},
      howpublished = {Presentation at the All Lab Lecture},
      year = {2002},
      url = {https://dataverse.jpl.nasa.gov/dataset.xhtml?persistentId=hdl:2014/39365}
    }
  15. Judd, M., Mazzonie, D., DeCosta, D., Gaines, D., Estlin, T., Anderson, R. C. and Castano, R. (2002). Mars rover image data prioritization for increases mission science return . AGU Fall Meeting. Source
    BibTeX
    @inproceedings{judd2002mars,
      title = {Mars rover image data prioritization for increases mission science return},
      author = {Judd, M. and Mazzonie, D. and DeCosta, D. and Gaines, D. and Estlin, T. and Anderson, R. C. and Castano, R.},
      booktitle = {AGU Fall Meeting},
      year = {2002},
      url = {https://ntrs.nasa.gov/citations/20060042536}
    }
  16. Ono, H. (2020). SCOTI: Science Captioning of Terrain Images for Data Prioritization and Local Image Search . Planetary and Space Science. Source
    BibTeX
    @article{ono2020scoti,
      title = {SCOTI: Science Captioning of Terrain Images for Data Prioritization and Local Image Search},
      author = {Ono, Hiro},
      journal = {Planetary and Space Science},
      volume = {188},
      pages = {104943},
      year = {2020},
      doi = {10.1016/j.pss.2020.104943},
      abstract = {Planetary exploration is full of challenges. Data bandwidth is very limited between planetary rovers and ground-based data system. What’s worse, even though NASA has accumulated over 34 million images from various missions, it requires significant effort and is hardly possible for any scientist to go through all of them. In order to improve the degree of automation and the efficiency of these processes, we propose a system leveraging machine learning for planetary rovers to actively look for scientifically interesting and valuable features according to text instructions from scientists and prioritize the images captured onboard with those features for downlink. Such an image prioritization mechanism can also be naturally applied to content-based image search through text description in any local planetary image data server, allowing scientists to search for images with desired features without going through them one by one. Besides theoretical and engineering details of our proposed approach, we also present both quantitative and qualitative evaluation of the system along with some concrete examples.}
    }
  17. 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}
    }
  18. Francis, R., Estlin, T., Doran, G., Gaines, D., Johnstone, S., Montano, S., Peret, L., Mousset, V., Gasnault, O., Frydenvang, J., Wiens, R. C., Schaffer, S., Pavri, B., Verma, V., Chattapadhyay, D., Bornstein, B., Mittal, N. and Deflores, L. (2018). Incorporating AEGIS Autonomous Science into Mars Science Laboratory Rover Mission Operations . SpaceOps Conference. Source
    BibTeX
    @inproceedings{francis2018incorporating,
      title = {Incorporating AEGIS Autonomous Science into Mars Science Laboratory Rover Mission Operations},
      author = {Francis, Raymond and Estlin, Tara and Doran, Gary and Gaines, Daniel and Johnstone, Stephen and Montano, Suzanne and Peret, Laurent and Mousset, Valerie and Gasnault, Olivier and Frydenvang, Jens and Wiens, Roger C. and Schaffer, Steven and Pavri, Betina and Verma, Vandana and Chattapadhyay, Debarati and Bornstein, Benjamin and Mittal, Nimisha and Deflores, Lauren},
      booktitle = {SpaceOps Conference},
      publisher = {American Institute of Aeronautics and Astronautics},
      address = {Marseille, France},
      year = {2018},
      doi = {10.2514/6.2018-2576},
      abstract = {The AEGIS (Autonomous Exploration for Gathering Increased Science) intelligent targeting software system has been in use on the Mars Science Laboratory (MSL) mission since 2016. The system allows on-board autonomous selection of targets for the ChemCam remote geochemistry instrument based on analysis of images taken by the rover. This paper describes the deployment of AEGIS to MSL and the operational use of the system since rollout to science operations in May of 2016. We describe how MSL Science Operations have adapted to include autonomous target selection, both in procedures and in exploration strategies, and how mission planners and scientists have used AEGIS autonomy to enhance their work on the MSL mission.}
    }
  19. Rollins, P., Sabzehi, M. and Kafadarian, L. (2024). Look Mob, No Hands! Automating Mobility Downlink for the Mars Science Laboratory . IEEE Field and Service Robots. Source
    BibTeX
    @inproceedings{rollins2024look,
      title = {Look Mob, No Hands! Automating Mobility Downlink for the Mars Science Laboratory},
      author = {Rollins, PJ and Sabzehi, Mielad and Kafadarian, Lauren},
      booktitle = {IEEE Field and Service Robots},
      publisher = {JPL Open Repository},
      year = {2024},
      doi = {10.48577/jpl.rhrlbe}
    }
  20. Sherwood, R. L., Chien, S., Tran, D., Cichy, B., Castano, R., Davies, A. and Rabideau, G. (2005). Intelligent systems in space: the EO-1 Autonomous Sciencecraft . Infotech@Aerospace. doi.org/10.2514/6.2005-6917
    BibTeX
    @misc{sherwood2005intelligent,
      title = {Intelligent systems in space: the EO-1 Autonomous Sciencecraft},
      author = {Sherwood, Robert L. and Chien, Steve and Tran, Daniel and Cichy, Benjamin and Castano, Rebecca and Davies, Ashley and Rabideau, Gregg},
      booktitle = {Infotech@Aerospace},
      year = {2005},
      doi = {10.2514/6.2005-6917},
      abstract = {The Autonomous Sciencecraft Software (ASE) is currently flying onboard the Earth Observing One (EO-1) Spacecraft. This software enables the spacecraft to autonomously detect and respond to science events occurring on the Earth. The package includes software systems that perform science data analysis, deliberative planning, and runtime robust execution. Because of the deployment to the EO-1 spacecraft, the ASE software has stringent constraints of autonomy and limited computing resources. We describe these constraints and how they are reflected in our operations approach. A summary of the final results of the experiment is also included. This software has demonstrated the potential for space missions to use onboard decision-making to detect, analyze, and respond to science events, and to downlink only the highest value science data. As a result, ground-based mission planning and analysis functions have been greatly simplified, thus reducing operations cost.}
    }
  21. 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}
    }
  22. Krupiarz, C. J., Jennings, E. H., Seguí, J. S., Pang, J. N., Schoolcraft, J. B. and Torgerson, J. L. (2006). Spacecraft data and relay management using delay tolerant networking . SpaceOps Conference. Source
    BibTeX
    @inproceedings{krupiarz2006spacecraft,
      title = {Spacecraft data and relay management using delay tolerant networking},
      author = {Krupiarz, Christopher J. and Jennings, Esther H. and Seguí, John S and Pang, Jackson N and Schoolcraft, Joshua B. and Torgerson, J. Leigh},
      booktitle = {SpaceOps Conference},
      year = {2006},
      doi = {10.2514/6.2006-5754},
      abstract = {NASA's demonstration of the successful transmission of relay data through the orbiting Mars Odyssey, Mars Global Surveyor, and Mars Express by the Mars Exploration Rovers has shown not only the benefit of using a relay satellite for multiple landed assets in a deep space environment but also the benefit of international standards for such architecture. As NASA begins the quest defined in the Vision for Exploration with robotic and manned missions to the Moon, continues its study of Mars, and is joined in these endeavors by countries world-wide, landed assets transmitting data through relay satellites will be crucial for completing mission objectives. However, this method of delivery of data will result in increased complexity in routing and prioritization of data transmission as the number of missions increases. Also, there is currently no standard method among organizations conducting such missions to return these data sets to Earth given a complex environment. One possibility for establishing such a standard is for mission designers to deploy protocols which fall under the umbrella of Delay Tolerant Networking (DTN). These developing standards include the Bundle Protocol (BP) which provides a standard, secure, store and forward mechanism designed for high latency and asymmetric communication links and the Licklider Transmission Protocol (LTP) which is used to provide a reliable deep space link transmission service.}
    }
  23. Schlesinger, A., Willman, B. M., Pitts, L., Davidson, S. R. and Pohlchuck, W. A. (2016). Delay/Disruption Tolerant Networking for the International Space Station (ISS) . SpaceOps. Source
    BibTeX
    @inproceedings{schlesinger2016delay,
      title = {Delay/Disruption Tolerant Networking for the International Space Station (ISS)},
      author = {Schlesinger, Adam and Willman, Brett M. and Pitts, Lee and Davidson, Suzanne R. and Pohlchuck, William A.},
      booktitle = {SpaceOps},
      pages = {1-14},
      year = {2016},
      doi = {10.1109/aero.2017.7943857},
      abstract = {Disruption Tolerant Networking (DTN) is an emerging data networking technology designed to abstract the hardware communication layer from the spacecraft/payload computing resources. DTN is specifically designed to operate in environments where link delays and disruptions are common (e.g., space-based networks). The National Aeronautics and Space Administration (NASA) has demonstrated DTN on several missions, such as the Deep Impact Networking (DINET) experiment, the Earth Observing Mission 1 (EO-1) and the Lunar Laser Communication Demonstration (LLCD). To further the maturation of DTN, NASA is implementing DTN protocols on the International Space Station (ISS). This paper explains the architecture of the ISS DTN network, the operational support for the system, the results from integrated ground testing, and the future work for DTN expansion.}
    }
  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. 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.}
    }
  26. Wenkert, D., Gladden, R. E., Edwards, C. D., Schmitz, P., Denis, M. and Winton, A. J. (2016). Enabling International Data Relay at Mars . SpaceOps Conference. Source
    BibTeX
    @inproceedings{wenkert2016enabling,
      title = {Enabling International Data Relay at Mars},
      author = {Wenkert, Daniel and Gladden, Roy. E. and Edwards, Charles D. and Schmitz, Peter and Denis, Michel and Winton, Alistair J.},
      booktitle = {SpaceOps Conference},
      publisher = {American Institute of Aeronautics and Astronautics},
      year = {2016},
      doi = {10.2514/6.2016-2355}
    }
  27. Wronkiewicz, M., Doran, G., Lightholder, J., Hasnain, Z., Stockham, R., Brown, R. J., Zemerick, S. A. and Mandrake, L. (2026). A Flight-Ready Software Platform for Deploying Science Autonomy Onboard Spacecraft . IEEE Transactions on Aerospace and Electronic Systems. Source
    BibTeX
    @article{wronkiewicz2026flight,
      title = {A Flight-Ready Software Platform for Deploying Science Autonomy Onboard Spacecraft},
      author = {Wronkiewicz, Mark and Doran, Gary and Lightholder, Jack and Hasnain, Zaki and Stockham, Rex and Brown, Robert J. and Zemerick, Scott A. and Mandrake, Lukas},
      journal = {IEEE Transactions on Aerospace and Electronic Systems},
      volume = {62},
      pages = {3879--3890},
      year = {2026},
      doi = {10.1109/taes.2025.3650728},
      abstract = {Spacecraft exploring Earth and other bodies in the solar system are producing increasingly large and complex volumes of scientific data. Recently, the field of science autonomy has begun to develop data analysis algorithms to select, prioritize, and characterize science instrument data directly onboard the spacecraft. These data-derived insights can then inform downstream autonomous decisions like data prioritization to mitigate data bandwidth constraints. However, science autonomy development has largely focused on bespoke, instrument-specific algorithms; there are no generalized platforms for sharing reusable utilities or centralizing the operation of multiple science autonomy algorithms. To accelerate future development of flight-ready science autonomy, we developed a software package called Science Yield Improvement via Onboard Prioritization and Summary of Information System (SYNOPSIS). SYNOPSIS manages the execution of one or more science autonomy algorithms, stores their outputs in a centralized database, and prioritizes data even across multiple instruments. We simulated the use of SYNOPSIS with science autonomy algorithms to analyze and prioritize data collected by the Curiosity rover on Mars and integrated it into two popular flight software packages — core Flight System (cFS) and F-Prime — to ease infusion of future science autonomy algorithms. As opportunities for onboard data analysis grow with the volume and complexity of data, we expect that platform technologies like SYNOPSIS will facilitate future exploration of our solar system.}
    }
  28. Edwards, C., Gladden, R. and Lee, C. (2021). Next-Generation Relay Capabilities for Future Robotic and Human Mars Exploration. ntrs.nasa.gov/citations/20220003436
    BibTeX
    @misc{edwards2021next,
      title = {Next-Generation Relay Capabilities for Future Robotic and Human Mars Exploration},
      author = {Edwards, C. and Gladden, R. and Lee, C.},
      year = {2021},
      url = {https://ntrs.nasa.gov/citations/20220003436},
      abstract = {No abstract provided}
    }
  29. Young, E., Yang, G., Wagner, T., Ridenhour, F., Lawler, C. and Cox, N. (2023). Relay Planning in the Perseverance Rover's First 600 Solar Days on Mars . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{young2023relay,
      title = {Relay Planning in the Perseverance Rover's First 600 Solar Days on Mars},
      author = {Young, Emma and Yang, Genevie and Wagner, Travis and Ridenhour, Flora and Lawler, Christopher and Cox, Nagin},
      booktitle = {IEEE Aerospace Conference},
      publisher = {JPL Open Repository},
      year = {2023},
      doi = {10.48577/jpl.f9zcgz},
      abstract = {Since landing in Jezero Crater on Mars on February 18, 2021, the Mars 2020 mission’s Perseverance rover has been performing daily operations on the Martian surface and has been collecting samples that may one day be returned to Earth. The majority of science and engineering data from the Perseverance rover is returned through the Mars orbiters operated by the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) that make up the Mars Relay Network: Mars Reconnaissance Orbiter (MRO), Mars Odyssey (ODY), Mars Atmosphere and Volatile Evolution (MAVEN), and Trace Gas Orbiter (TGO). Prior to the rover’s landing, the Mars 2020 team joined the Mars Relay Network to begin planning relay through the coordinated, multi-mission process that is the cornerstone of relay planning. The Perseverance rover has now been on the Martian surface for more than 600 Martian solar days (“sols”) with several UHF relay sessions planned and executed per sol. The Mars 2020 relay planning team has established and improved upon the recurring process and tool suite to enable both data return and forward link of rover uplink products, and continues to coordinate and negotiate relay asset usages and constraints with the Mars Science Laboratory and Insight relay planning teams. Among many accomplishments, the relay planning team has supported checkouts and commissioning of Low-Density Parity-Check (LDPC) relay link configurations, the mission’s first solar conjunction period, and several rover flight software transitions.The Mars 2020 team has also been performing a checkout and commissioning campaign for the use of bitstream, or “unreliable”, relay sessions. Nominal use of bitstream relay is a new operational capability intended for the Perseverance rover that will allow specific science or engineering activities to run in parallel with the relay session, rather than pausing all other activities during relay, enabling additional and more timely data return. Pending the completion of the checkout and commissioning campaign, the operations team plans to approve and begin regular scheduling and use of bitstream UHF relay sessions beginning in 2023. This paper describes the Mars 2020 relay planning processes and tool architecture, key accomplishments (including progress for the bitstream checkout and commissioning campaign), and lessons learned and ongoing challenges during the first 600 sols of the Mars 2020 surface mission.}
    }
  30. Donitz, B. P., Didion, A., Nicholas, A., Voss, T. and Lee, C. (2021). Assessing Relay Communications for Mars Sample Return Surface Mission Concepts . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{donitz2021assessing,
      title = {Assessing Relay Communications for Mars Sample Return Surface Mission Concepts},
      author = {Donitz, Benjamin P and Didion, Alan and Nicholas, Austin and Voss, Thaddaeus and Lee, Charles},
      booktitle = {IEEE Aerospace Conference},
      pages = {1-10},
      publisher = {IEEE},
      year = {2021},
      doi = {10.1109/aero50100.2021.9438273},
      abstract = {The Mars Sample Return (MSR) Campaign is a 3-mission campaign concept supported by NASA and ESA to return samples from the Mars surface. MSR will, for the first time ever, present a need to communicate with multiple surface assets that are co-located on Mars in a coordinated effort to accomplish the unified objective of fetching, transporting, and returning samples from Mars. Currently, Mars surface assets relay data to and from Earth using a number of orbiters in what's known as the Mars Relay Network (MRN). This network is characterized by a small number of surface assets distributed across the Martian globe and a larger number of orbiters to provide relay services. As of June 2020, there are two surface assets for which five orbiters are providing relay. During the MSR Campaign, there will be two rovers and a lander that all will require relay communication from a small number of Mars orbiters to meet the aggressive MSR timeline. The inversion of the current MRN paradigm, a system of many surface assets requiring relay and few orbiters to provide relay, necessitates the unique challenge of optimally allocating relay passes to maximize the operational capability of all assets. The allocation must consider a large number of trade variables including Mars asset operational requirements and Earth ground system constraints, including staffing schedules, operations planning across time zones, and more. To address these telecommunication challenges, the Mars Asset Relay Mission Link Allocation Design Environment (MARMLADE) tool was developed. It is a MATLAB-based tool to assign orbiter passes or Direct-From-Earth (DFE) links to each of the three surface assets and quantify the operational efficiency of each surface asset. MARMLADE uses a data set of simulated Mars relay orbiter geometry and telecommunication capabilities provided by JPL's Telecom Orbit Analysis and Simulation Tool (TOAST) software to compute which asset should get each pass based on a series of heuristics and predictions of all assets' states. Within MARMLADE, the user can provide inputs including the option for time-based pass splitting, fixed FWD data rate capabilities, DFE communication capabilities, and link parameters allowing for the assessment of complex operations and hardware trades using surface mission operational efficiency as a primary figure of merit. As the MSR mission concepts continue to mature, MARMLADE is being used to assess ability of all MSR elements to meet the surface mission timeline requirements and to provide relay link allocations to each of the MSR surface assets. This paper will describe the motivation and design of the MARMLADE tool and how it is being used to perform campaign and mission level trades, generate requirements, and support development of the MSR surface mission scenarios.}
    }
  31. Marcozzi, M., Santoni, A., Amoroso, M., Mugnuolo, R., Edwards, C. and Viotti, M. (2024). International Mars Ice Mapper Communication System . International Astronautical Congress, IAC-24/B2/5.87741. Source
    BibTeX
    @inproceedings{marcozzi2024international,
      title = {International Mars Ice Mapper Communication System},
      author = {Marcozzi, M. and Santoni, A. and Amoroso, M. and Mugnuolo, R. and Edwards, C. and Viotti, M.},
      booktitle = {International Astronautical Congress},
      number = {IAC-24/B2/5.87741},
      publisher = {JPL Open Repository},
      year = {2024},
      doi = {10.48577/jpl.rouwbh},
      abstract = {The Italian Space Agency (ASI) and Thales Alania Space in Italy (TAS-I) in the context of the International Mars Ice Mapper (I-MIM) mission and in collaboration with the NASA Jet Propulsion Laboratory (JPL) are studying an innovative multi-band Communication Subsystem designed to deliver scientific data of at least 500 Gbit per day from the mission’s three elements (E): a main orbiter (E1), a demonstration lander (E2), and a freeflying smallsat (E3). The planned E1 instruments are a polarimetric synthetic aperture radar (SAR) in L-band, a Very High Frequency (VHF) sounder, and a submillimeter sounder. The E3 orbiter would carry a high-resolution imager. All of these next-generation sensors would generate high volumes of data and require large data-rate (>100 Mbps) acquisition. With analysis and definition of mission scenarios during its concept phase, the mission team has identified two main communication links. The Direct to Earth (DTE) link would deliver the science data and telecommand and telemetry at a high data rate primarily in Ka-bands (32 GHz) and in X-bands, with data transmission above 10 Mbps with Deep Space Network ground stations. The preliminary defined architecture anticipates that the 6-m aperture Large Deployable Reflector antenna (LDR) would support both DTE and the SAR instrument. The other main link under definition is the Proximity Link, which would support the relay of science data from the E3 smallsat to the main orbiter through X band for subsequent DTE links. This proximity link would potentially be available to relay data from future Mars orbiters and next-generation rovers and landers on the surface. A UHF proximity link would be onboard to relay data from legacy users on the surface already at Mars, as well as potentially support I-MIM’s E2 lander. While both UHF and X-band are the primary considered bands for the proximity link, the mission team is also considering Ka-band and optical links to take into account the evolution of future exploration missions. With the goal of identifying and characterizing accessible, near-surface water ice in the mid latitudes of Mars, the I-MIM mission is a multilateral collaboration being developed by the Agenzia Spaziale Italiana (ASI), the Canadian Space Agency (CSA), the Japan Aerospace Exploration Agency (JAXA), and the National Aeronautics and Space Administration (NASA).}
    }