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University of Luxembourg LunaLab

The LunaLab test field: coarse basaltic soil, placed rocks and craters, black-coated walls and ceiling, the ceiling OptiTrack cameras and the single sun-simulating spotlight, with the four illumination cases used for the SPICE-HL3 dataset at 200, 100 to 1, 25 to 1 and 0.1 lux.

Source: [1]. CC BY 4.0.

LunaLab is an indoor lunar analogue built to reproduce light, not soil. Its design case is the high-latitude lunar visual environment: a sun a few degrees above the horizon, almost no atmospheric scattering, and a scene dominated by long moving shadows. The operators chose coarse basaltic gravel over regolith simulant deliberately, on cost and health grounds, and that choice is what bought them an 11 by 8 m field instead of a small bin [2]. The field has also been reproduced as a photogrammetric digital twin inside an open-source lunar simulator, so work that starts on the physical terrain can continue in simulation without rebuilding the scene [3].

ParameterValue
OperatorUniversity of Luxembourg, SnT, Space Robotics group, with ispace Europe
LocationEsch-sur-Alzette, Luxembourg [2]
CommissionedConstructed 2019 to 2020, reported October 2020. No formal date published
TypeIndoor analogue terrain field at 1 g, built for optical and vision-based navigation
Floor area88 m2, 11 x 8 m ; 77 m2, 7 x 11 m, in the construction paper . See below
CapabilitiesTerrain field, sun simulator, motion capture
Simulant or terrainCoarse basaltic gravel and sand, 20 t, 0.2 to 4 mm. Not a simulant
Instrumentation12 OptiTrack PrimeX cameras at 25 Hz. No load cells described
Ground truthMotion capture position and quaternion attitude at 25 Hz
Fidelity limitsGrain size 0.2 to 4 mm against 40 to 130 um lunar; no opposition effect . See below
AccessNot published. The dataset is public on Zenodo, code on GitHub
Cited byNone. Published users are fictionlab Leo rovers [4]
ParameterValue
Working volume11 x 8 m; 7 x 11 m in the construction paper [2]. Bed depth not published
Test article limitsArticles run are Leo rovers, about 359 x 296 mm, masts to 550 mm
VacuumNot applicable. Ambient pressure
TemperatureNot applicable. No thermal capability
IlluminationSee sun simulator
Simulant or terrainBasaltic gravel and sand, 20 t, 0.2 to 4 mm, with placed rocks and shaped craters [2]
Gravity offloadNot applicable
InstrumentationCeiling OptiTrack; walls and ceiling painted black

A rectangular field of loose basaltic material with rocks and shaped craters on it, inside a room whose walls and ceiling are painted black. Every element of that is an optical decision.

The soil choice is the most consequential and the operators explain it directly. Regolith simulant was rejected because of its cost and because its fine fraction is a carcinogenic inhalation hazard, and rejecting it is what allowed the field to be built at 20 t and tens of square meters rather than as a small enclosed bin [2]. The material is chosen for its reflectance and its ability to hold a shaped crater rim, not for its mechanical behavior under a wheel: basalt sand at 0.2 to 1 mm plus gravel at 2 to 5 mm, and a separate ispace lunar yard of 8 by 8 m holding 3 t was built alongside it [2]. Bed depth and relative density control are not published.

Black paint on the walls and ceiling is the shadow-contrast measure. The operators record it as a mitigation rather than a solution: lunar shadows are darker than the room can produce, and the paint reduces but does not remove the bounce that fills them.

ParameterValue
Working volumeOne movable head on the short side of the field
IlluminationAputure LightStorm 600c Pro, 600 W, 69 to 51,100 lux, 2300 to 10,000 K
SlopeSolar elevation 8 degrees at 80 cm lamp height, 4 degrees at 40 cm
InstrumentationLamp position adjustable vertically and horizontally

The lamp is a single source and its height is the control variable. At 80 cm above the floor it subtends 8 degrees at the field center and at 40 cm it subtends 4 degrees, which brackets the elevations a polar site sees across a lunar day [1]. Color temperature is set to 6000 K to approximate the solar spectrum. Four standard cases were defined for the published dataset: a reference case at 200 lux, a noon case at 100 down to 1 lux, a dawn and dusk case at 25 down to 1 lux, and a night case at 0.1 lux [1].

The earlier configuration used a 2000 W and a 1000 W tungsten bulb with a focusing lens, reaching about 100,000 lux at 1 m, run in flood mode with barn doors [2].

ParameterValue
Working volumeCeiling mounted over the field
Instrumentation12 OptiTrack PrimeX cameras, logging at 25 Hz
IlluminationEmits infrared tracking light and status LED rings into the scene

Accuracy is stated by the operators only as sub-millimeter, with no numeric figure published [1]. A validation of the same class of array, a 16-camera OptiTrack rig at NASA Glenn’s SLOPE facility, found the software’s self-reported mean error of 0.17 mm was honest as an aggregate but understated error in regions where test hardware occluded cameras, and that more cameras were needed to close the occluded regions [10]; an unvalidated sub-millimeter claim here should be read the same way. The system pollutes the scene it measures, which is treated below as a fidelity limit rather than as an instrumentation note.

Ground truth is the twelve-camera ceiling-mounted OptiTrack rig described above.

The instrumentation that matters here is the payload rather than the facility. The published campaign carried a monochrome camera, a stereo-inertial sensor and, for the first time in a planetary exploration setting, a single-photon avalanche diode camera, alongside wheel odometry and an inertial unit [1]. A single-photon detector is the natural instrument for a scene whose interesting cases are at 1 lux and below, and the facility is built to produce those cases.

Regolith. Grain size is 0.2 to 4 mm against 40 to 130 um for lunar regolith, a difference of one to two orders of magnitude [1]. The real material also carries bulk density rising from about 1.30 g/cm3 at the surface toward 1.92 g/cm3 by 60 cm depth [6] and shear strength that climbs with it, above 2 kPa at 1 m depth, none of which loose basalt gravel at 1 g is built to match [9]. Nothing measured here about wheel sinkage, slip, dust lofting or adhesion transfers to the Moon, and the facility does not claim it does. The operators’ rejection of simulant is itself consistent with the wider record: NASA’s own simulant-scoring work finds that even purpose-built lunar simulants rarely exceed a composition figure of merit around 0.6 against an Apollo reference, because none but the NU-LHT series contain anything standing in for lunar agglutinates [7][8], so a graded basalt that makes no claim to compositional fidelity is not obviously worse placed than a simulant that claims it and falls short. The same workshop that set NASA’s simulant framework also tabulated the geotechnical envelope a simulant is expected to reproduce, cohesion 0.1 to 1 kPa and friction angle 30 to 50 degrees among the targets [8], a bar the facility’s coarse gravel does not attempt to clear.

The opposition effect. The operators state plainly that the backscatter surge lunar regolith shows near zero phase angle cannot be reproduced in the facility at all [1]. The opposition surge is a first-order term in lunar photometry, so a photometrically calibrated perception algorithm cannot be validated against it here.

Regolith reflectance. The soil is less reflective than real regolith, which the operators offer as a worst-case optical scenario rather than as a match.

Collimated sunlight. The lamp is close to the field relative to the field’s size, so illuminance falls off as the inverse square across it, producing uneven illumination and inconsistent exposure along a long trajectory [1]. Real solar illumination is effectively collimated and uniform across a rover’s traverse.

A dark scene that is only dark. The measurement system contaminates the measurement. Status LED rings and the infrared illumination the motion capture cameras emit act as secondary light sources, producing faint glows, ghosting and lens flares in the dark cases, an effect the operators describe as overlooked and unavoidable. Any perception result at 0.1 lux [1] carries it.

Lunar shadow contrast and full solar illuminance. The lamps reach about 100,000 lux in the earlier configuration against a lunar solar constant equivalent of about 135,000 lux, and shadows are not as black as lunar shadows even with black walls and ceiling [2].

Dust discipline. The fine material still lifts and has to be allowed to settle between runs, and it ingresses into mechanisms [2].

SPICE-HL3 dataset, recorded 2024 and published 2026. Two fictionlab Leo rovers, 88 sequences and 1.3 million images across seven trajectories and four illumination conditions, at 5 cm/s and 50 cm/s, with and without headlights [1]. Measured: stereo RGB-inertial, monocular monochrome and single-photon imagery with wheel odometry and inertial data, all against motion capture ground truth. The single-photon camera produced tighter and more stable image quality distributions clustered around the mean, while the conventional cameras reached lower absolute minimum and mean quality scores because of their higher resolution; visual SLAM pipelines were run to their failure points under the dark cases. The dataset is the facility’s principal published output.

Facility construction, 2019 to 2020. The construction paper is itself a lessons-learned report on lighting, surface material and shadow contrast for two indoor lunar analogues, the LunaLab and the adjacent ispace yard [2].

Terrain-induced vibration prediction. LunaLab is one of three test environments, along with a lakeshore and a disused mine, used to validate a lightweight method that predicts rover vibration from LiDAR terrain roughness corrected with IMU data on a Leo Rover [4].

Downstream simulation. The photogrammetric digital twin of LunaLab is one of the environments distributed with an open-source lunar robotics simulator, and a separate terramechanics campaign on a 20 m sand bed has since fitted slip and sinkage models for that same simulator, an effective-radius correction for grousered wheels among the results [3][5].

References

  1. Rodríguez-Martínez, D., van der Meer, D., Song, J., Bera, A., Pérez-del-Pulgar, C. J. and Olivares-Mendez, M. A. (2026). SPICE-HL3: Single-Photon, Inertial, and Stereo Camera Dataset for Exploration of High-Latitude Lunar Landscapes . Scientific Data. Source
    BibTeX
    @article{rodriguezmartinez2026spice,
      title = {{SPICE-HL3}: Single-Photon, Inertial, and Stereo Camera Dataset for Exploration of High-Latitude Lunar Landscapes},
      author = {Rodríguez-Martínez, David and van der Meer, Dave and Song, Junlin and Bera, Abhishek and Pérez-del-Pulgar, Carlos J. and Olivares-Mendez, Miguel Angel},
      journal = {Scientific Data},
      volume = {13},
      pages = {374},
      year = {2026},
      doi = {10.1038/s41597-026-06668-8},
      abstract = {Abstract Exploring high-latitude lunar regions presents a challenging visual environment for robots. The low sunlight elevation angle and minimal light scattering result in a visual field dominated by a strong contrast featuring long, dynamic shadows. Reproducing these conditions on Earth requires sophisticated simulators and specialized facilities. We introduce a unique dataset recorded at the LunaLab from the SnT - University of Luxembourg, an indoor test facility designed to replicate the optical characteristics of multiple lunar latitudes. Our dataset includes images, inertial measurements, and wheel odometry data from robots navigating different trajectories under multiple illumination scenarios, simulating high-latitude lunar conditions from dawn to nighttime with and without the aid of headlights, resulting in 88 distinct sequences containing a total of 1.3 M images. Data was captured using a stereo RGB-inertial sensor, a monocular monochrome camera, and, for the first time, a novel single-photon avalanche diode (SPAD) camera. We recorded both static and dynamic image sequences, with robots navigating at slow (5 cm/s) and fast (50 cm/s) speeds. All data is calibrated, synchronized, and timestamped, providing a valuable resource for validating perception tasks from vision-based autonomous navigation to scientific imaging for future lunar missions targeting high-latitude regions or those intended for robots operating across perceptually degraded environments.}
    }
  2. Ludivig, P., Calzada-Diaz, A., Olivares Mendez, M. A., Voos, H. and Lamamy, J. (2020). Building a Piece of the Moon: Construction of Two Indoor Lunar Analogue Environments . International Astronautical Congress, IAC-20-A3.2B.3. Source
    BibTeX
    @inproceedings{ludivig2020building,
      title = {Building a Piece of the {Moon}: Construction of Two Indoor Lunar Analogue Environments},
      author = {Ludivig, Philippe and Calzada-Diaz, Abigail and Olivares Mendez, Miguel Angel and Voos, Holger and Lamamy, Julien},
      booktitle = {International Astronautical Congress},
      number = {IAC-20-A3.2B.3},
      organization = {International Astronautical Federation},
      year = {2020},
      url = {https://orbilu.uni.lu/handle/10993/45539}
    }
  3. Richard, A., Kamohara, J., Uno, K., Santra, S., van der Meer, D., Olivares-Mendez, M. and Yoshida, K. (2024). OmniLRS: A Photorealistic Simulator for Lunar Robotics . IEEE International Conference on Robotics and Automation (ICRA). Source
    BibTeX
    @inproceedings{richard2024omnilrs,
      title = {OmniLRS: A Photorealistic Simulator for Lunar Robotics},
      author = {Richard, Antoine and Kamohara, Junnosuke and Uno, Kentaro and Santra, Shreya and van der Meer, Dave and Olivares-Mendez, Miguel and Yoshida, Kazuya},
      booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
      pages = {16901-16907},
      year = {2024},
      doi = {10.1109/icra57147.2024.10610026},
      abstract = {Developing algorithms for extra-terrestrial robotic exploration has always been challenging. Along with the complexity associated with these environments, one of the main issues remains the evaluation of said algorithms. With the regained interest in lunar exploration, there is also a demand for quality simulators that will enable the development of lunar robots. In this paper, we propose Omniverse Lunar Robotic-Sim (OmniLRS) that is a photorealistic Lunar simulator based on Nvidia’s robotic simulator. This simulation provides fast procedural environment generation, multi-robot capabilities, along with synthetic data pipeline for machine-learning applications. It comes with ROS1 and ROS2 bindings to control not only the robots, but also the environments. This work also performs sim-to-real rock instance segmentation to show the effectiveness of our simulator for image-based perception. Trained on our synthetic data, a yolov8 model achieves performance close to a model trained on real-world data, with 5% performance gap. When finetuned with real data, the model achieves 14% higher average precision than the model trained on real-world data, demonstrating our simulator’s photorealism. The code is fully open-source, accessible here: https://github.com/AntoineRichard/OmniLRS, and comes with demonstrations.}
    }
  4. Garcia, G. M., Aravecchia, S. and Olivares-Mendez, M. A. (2026). RoughSense: Lightweight Terrain-Induced Rover Vibration Prediction Using Point Clouds and IMU Feedback. arxiv.org/abs/2609.03720v1
    BibTeX
    @misc{garcia2026roughsense,
      title = {RoughSense: Lightweight Terrain-Induced Rover Vibration Prediction Using Point Clouds and IMU Feedback},
      author = {Garcia, Gabriel Manuel and Aravecchia, Stephanie and Olivares-Mendez, Miguel Angel},
      year = {2026},
      url = {https://arxiv.org/abs/2609.03720v1}
    }
  5. Kern, J. M., Hurrell, J. M., Santra, S., Takehana, K., Uno, K. and Yoshida, K. (2025). Data-Driven Terramechanics Approach Towards a Realistic Real-Time Simulator for Lunar Rovers . arXiv preprint. Source
    BibTeX
    @article{kern2026data,
      title = {Data-Driven Terramechanics Approach Towards a Realistic Real-Time Simulator for Lunar Rovers},
      author = {Kern, Jakob M. and Hurrell, James M. and Santra, Shreya and Takehana, Keisuke and Uno, Kentaro and Yoshida, Kazuya},
      journal = {arXiv preprint},
      pages = {662-668},
      year = {2025},
      doi = {10.1109/isparo66239.2025.11436587},
      abstract = {High-fidelity simulators for the lunar surface provide a digital environment for extensive testing of rover operations and mission planning. However, current simulators focus on either visual realism or physical accuracy, which limits their capability to replicate lunar conditions comprehensively. This work addresses that gap by combining high visual fidelity with realistic terrain interaction for a realistic representation of rovers on the lunar surface. Because direct simulation of wheel-soil interactions is computationally expensive, a data-driven approach was adopted, using regression models for slip and sinkage from data collected in both full-rover and single-wheel experiments and simulations. The resulting regression-based terramechanics model accurately reproduced steady-state and dynamic slip, as well as sinkage behavior, on flat terrain and slopes up to 20°, with validation against field test results. Additionally, improvements were made to enhance the realism of terrain deformation and wheel trace visualization. This method supports real-time applications that require physically plausible terrain response alongside high visual fidelity.}
    }
  6. Heiken, G. H., Vaniman, D. T. and French, B. M. (1991). Lunar Sourcebook: A User's Guide to the Moon . Endeavour. Source
    BibTeX
    @book{heiken1991lunar,
      title = {Lunar Sourcebook: A User's Guide to the Moon},
      author = {Heiken, Grant H. and Vaniman, David T. and French, Bevan M.},
      journal = {Endeavour},
      volume = {16},
      pages = {96},
      publisher = {Cambridge University Press},
      year = {1991},
      doi = {10.1016/0160-9327(92)90014-g}
    }
  7. Schrader, C. M., Rickman, D. L., McLemore, C. A. and Fikes, J. C. (2010). Lunar Regolith Simulant User's Guide . NASA Marshall Space Flight Center, NASA/TM-2010-216446. Source
    BibTeX
    @techreport{schrader2010lunar,
      title = {Lunar Regolith Simulant User's Guide},
      author = {Schrader, C. M. and Rickman, Douglas L. and McLemore, Carole A. and Fikes, John C.},
      number = {NASA/TM-2010-216446},
      institution = {NASA Marshall Space Flight Center},
      year = {2010},
      url = {https://ntrs.nasa.gov/citations/20100038451},
      abstract = {Based on primary characteristics, currently or recently available lunar regolith simulants are discussed from the perspective of potential experimental uses. The characteristics used are inherent properties of the material rather than their responses to behavioral (geomechanical, physiochemical, etc.) tests. We define these inherent or primary properties to be particle composition, particle size distribution, particle shape distribution, and bulk density. Comparable information about lunar materials is also provided. It is strongly emphasized that anyone considering either choosing or using a simulant should contact one of the members of the simulant program listed at the end of this document.}
    }
  8. Sibille, L., Carpenter, P., Schlagheck, R. and French, R. A. (2006). Lunar Regolith Simulant Materials: Recommendations for Standardization, Production, and Usage . NASA Marshall Space Flight Center, NASA/TP-2006-214605. Source
    BibTeX
    @techreport{sibille2006development,
      title = {Lunar Regolith Simulant Materials: Recommendations for Standardization, Production, and Usage},
      author = {Sibille, Laurent and Carpenter, Paul and Schlagheck, R. and French, R. A.},
      number = {NASA/TP-2006-214605},
      institution = {NASA Marshall Space Flight Center},
      type = {NASA Technical Publication},
      year = {2006},
      url = {https://ntrs.nasa.gov/citations/20060051776},
      abstract = {Experience gained during the Apollo program demonstrated the need for extensive testing of surface systems in relevant environments, including regolith materials similar to those encountered on the lunar surface. As NASA embarks on a return to the Moon, it is clear that the current lunar sample inventory is not only insufficient to support lunar surface technology and system development, but its scientific value is too great to be consumed by destructive studies. Every effort must be made to utilize standard simulant materials, which will allow developers to reduce the cost, development, and operational risks to surface systems. The Lunar Regolith Simulant Materials Workshop held in Huntsville, AL, on January 24 26, 2005, identified the need for widely accepted standard reference lunar simulant materials to perform research and development of technologies required for lunar operations. The workshop also established a need for a common, traceable, and repeatable process regarding the standardization, characterization, and distribution of lunar simulants. This document presents recommendations for the standardization, production and usage of lunar regolith simulant materials.}
    }
  9. Connolly, J. F. and Carrier, W. D. (2023). An Engineering Guide to Lunar Geotechnical Properties . IEEE Aerospace Conference. Source
    BibTeX
    @inproceedings{connolly2023engineering,
      title = {An Engineering Guide to Lunar Geotechnical Properties},
      author = {Connolly, John F. and Carrier, W. David},
      booktitle = {IEEE Aerospace Conference},
      pages = {1-9},
      address = {Big Sky, Montana},
      year = {2023},
      doi = {10.1109/aero55745.2023.10115961},
      abstract = {The renewed interest in returning human and robotic explorers to the lunar surface has identified a need for a renewed understanding of lunar geotechnical properties related to landing, exploration, excavation, and construction activities on the lunar surface. This paper summarizes measurements conducted during US and Russian/Soviet landed missions as well as experiments performed on returned samples to establish fundamental geotechnical properties such as particle size distribution, particle shape, bulk density, shear strength, cohesion and bearing strength. While many of these properties are well known, how they vary with increased lunar soil depth is less understood, and those properties that vary significantly as a function of depth are explored in additional detail. Selected examples discuss mechanical excavation forces, rocket exhaust erosion forces, and the preparation of launch/landing pad surfaces, with the goal of a better understanding of lunar soil geotechnical properties that apply to large-scale exploration of the lunar surface and dictate the design of future exploration systems.}
    }
  10. Schepelmann, A. and Gerdts, S. (2022). Characterization of Infrared Optical Motion Tracking System in NASA's Simulated Lunar Operations (SLOPE) Laboratory . NASA, NASA/TM-20220005304. Source
    BibTeX
    @techreport{schepelmann2022characterization,
      title = {Characterization of Infrared Optical Motion Tracking System in NASA's Simulated Lunar Operations (SLOPE) Laboratory},
      author = {Schepelmann, Alexander and Gerdts, Stephen},
      number = {NASA/TM-20220005304},
      institution = {NASA},
      year = {2022},
      url = {https://ntrs.nasa.gov/citations/20220005304},
      abstract = {This work characterizes the accuracy of a 16 camera OptiTrack motion tracking system installed in NASA Glenn Research Center's Simulated Lunar Operations (SLOPE) laboratory.  The position of a rigid body mounted on a motorized linear stage is compared to its position reported by the motion tracking system as it travels through the facility's 777m$^3$ capture volume of interest.  Experiments show that the mean error reported by the motion tracking system for the aggregate capture volume is in-line with independent measurements collected using the motion stage.  Error within regions of the capture volume exceed the mean error reported by the motion tracking system, likely due to occlusion, and suggests that additional cameras should be used to increase measurement accuracy in these regions.  Overall, results show that error values reported by the motion tracking system are representative of the measurement error in a collected data set and validates the system's use for characterizing the mobility and tractive performance of robots, rovers, and other vehicles for planetary exploration.}
    }