[Attribution] [Acknowledgements] [Support] [Download Primary Dataset] [Download Extras] |
Description
The Polar Optical Lunar Analog Reconstruction (POLAR) dataset seeks to recreate the imaging conditions at the poles of the Moon for stereo vision evaluation. The dominant factors of appearance at the Lunar poles are oblique sunlight, natural terrain, regolith reflectance, and the absence of atmospheric scattering. Lighting is therefore very harsh, resulting in long cast shadows and high dynamic range (HDR) conditions due to contrasting shadowed and illuminated regions. The surface appearance at the Lunar poles is part of a family of optical environments which are prevalent on airless bodies throughout the solar system, but rarely encountered here on Earth.
In developing stereo vision capability for a proposed NASA mission to the lunar poles, we were surprised to learn that there was little prior work in the area and almost no publicly available rover-relevant data on this topic. Despite the proliferation of robots and the wealth of terrestrial stereo datasets, few in the robotics community have looked at imaging specific to airless planetary bodies. In this work, we sought to develop a common framework for stereo vision researchers: (1) an understanding and reproduction of polar/airless optical conditions in a laboratory setting, (2) a library of stereo images for algorithm development complete with ground truth, and (3) metrics and standards for comparative evaluation.
For experimentation, analog terrains were constructed in a laboratory setting using a regolith simulant testbed and populated with rocks and craters. Each terrain was then illuminated with a constellation of oblique sun sources and imaged with a stereo rig from several viewpoints. Finally, a high resolution LIDAR scanner provided ground truth geometry at sub-2mm accuracy for each image pixel. The complete dataset comprises 12 terrain experiments - featuring over 2500 HDR stereo pairs and 12GB of sensor data, supplemented with ground truth, radiometric calibrations, and registration information.

Changelog:
Nov 01, 2017 - Fixed documentation broken linkMay 08, 2017 - Initial Release
Attribution
Citation:
Our NESF16 poster at NASA Tech Reports Server [.pdf].
Acknowledgements
We would like to thank Joe Minafra, Vinh To, Rick Elphic, Tony Colaprete, Greg Schmidt, Bill Bluethmann, Howard Cannon, Jackie Quinn, Daniel Andrews and the RP team for advice and support.
Support and Documentation
Download the dataset documentation [.pdf]. |
For questions about the dataset, contact: Dr. Uland Wong <uland dot wong at nasa dot gov> or Dr. Larry Edwards <laurence dot j dot edwards at nasa dot gov>.
Primary Dataset
Download the entire dataset including extras [.zip, 11.5 GB] or download individual parts below. The individual parts contain just the images, ground truth LIDAR clouds, and geometric calibrations. |
Terrain 1 |
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Description: This should be an easy hazard
detection case. Features a distribution of rocks that are
mostly large and prominent, with ample spacing in between. The
surface has been prepared with a texture that has undulating
features but is relatively smooth. There are 15 rocks in this
terrain.
Download: 730 MB [.zip] |
Terrain 2 |
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Description: Using the same rocks as Terrain
1, but a giant rock has been introduced into the foreground.
The idea is to test a large area of cast shadow and HDR in the
form of a prominent, bright foreground object. There are 16
rocks (one giant, and 15 large/medium).
Download: 911 MB [.zip] |
Terrain 3 |
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Description: Using the same large rocks as
Terrain 1, but small and medium rocks have been added to the
scene in a uniform manner. While derived from Surveyor 7 (S7)
counts, this distribution is weighted toward larger rocks in
order to test hazard performance. There are 28 rocks in this
distribution.
Download: 917MB [.zip] |
Terrain 4 |
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Description: Using the same distribution as
Terrain 3, but rocks have been randomly shuffled to different
locations. This distribution is weighted toward larger rocks
in order to test hazard performance. One side of the terrain
has a greater density than the other. The areal placement of
large rocks in this scene makes it a good test of left-right
occlusions in stereo. There are 28 rocks in this distribution.
Download: 923 MB [.zip] |
Terrain 5 |
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Description: This is an S7 sampled
distribution centered on small-medium sized rocks. A cluster
of larger rocks appears in the corner where it is easily
visible from multiple views. This scene tests hazard detection
sensitivity near the 10cm range as well as accurate detection
of larger rocks when they are possibly arranged with complex
shadows. The surface of the regolith is also contains several
small negative features (e.g. pitted, craters)
Download: 919 MB [.zip] |
Terrain 6 |
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Description: This is a featureless terrain
which is thought to be the hardest case for stereo
correlation. The terrain lacks rocks, though the surface has
smooth undulations which may provide false positives. The
surface has been dusted over, however some brushing and
natural texture features remain.
Download: 925 MB [.zip] |
Terrain 7 |
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Description: Large rocks are arranged in a
“checkerboard” manner on one side of the sandbox. Small rocks
are arranged randomly on the opposite side. The side with the
small rocks is meant to simulate a rough-but-traversible area.
This scene tests complex shadows between the large rocks and
also shadows cast from the large rocks onto the the
traversible side. There are 19 rocks in this distribution.
Download: 938 MB [.zip] |
Terrain 8 |
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Description: This terrain features a field of
small and medium sized rocks centered on a large boulder. The
large boulder is actually a cluster of rocks stacked together.
This scene is designed to test the effect of a (central rather
than peripheral) large cast shadow on mostly passable terrain.
As our large rock has complex surface geometry with
self-occlusions, it is also a good feature to test stereo
reconstruction. There are 16 rocks in this distribution,
including one “giant” rock pile.
Download: 927 MB [.zip] |
Terrain 9 |
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Description: This is a distribution of rocks
that are at or near the 10cm hazard limit. The rocks are
spaced far apart, with none touching. This should be a simple,
clear test case for hazard detection. There are 20 rocks in
this distribution.
Download: 926 MB [.zip] |
Terrain 10 |
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Description: This terrain uses the same rock
distribution as Terrain 9 with a different placement scheme.
Various rocks are clustered in an area of higher density where
many are almost touching, while areas of the terrain have no
rocks. The terrain is intended to test the effect of areal
density of features on hazard detection/reconstruction
accuracy. There are 20 rocks in this distribution.
Download: 917 MB [.zip] |
Terrain 11 |
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Description: This scene features a large
negative obstacle which is meant represent a smooth "fresh"
crater. There are some medium-sized rocks along the rim and
periphery. The relief of the crater is exaggerated
(particularly the rim) in order to also test detection of
steep slopes at the particular angle of view. The shape of the
crater produces interesting interior shadows and
inter-reflected light. The smooth slopes and terrain provide a
correlation challenge case. There are 9 rocks in this
distribution and one crater.
Download: 903 MB [.zip] |
Terrain 12 |
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Description: The fresh crater in Terrain 11
is eroded to create an “old” crater. The rim is reduced in
height and sharpness. Large rocks lie collapsed along one wall
and covered in regolith while the other side lacks rocks. The
regolith has been surfaced with pockmarks to simulate rough
texturing from small rocks and accumulated micro-impacts.
There are 21 rocks in this distribution and one crater.
Download: 918 MB [.zip] |
Dataset Extras
Terrain 13 |
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Description: This is a small sandbox using
the LHT regolith simulant which is prohibitively expensive for
use in bulk. In comparison to the JSC-1A simulant used in the
other terrains, this material is lighter and closer in
appearance to the regolith at the lunar poles. Three small
rocks (~10cm) have been placed in the scene, and while the
light clocks in azimuth. This data is provided as-is and is
not well calibrated.
Download: 202 MB [.zip] |
Radiometric Calibrations |
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Description: Radiometric camera response
functions used to convert pixel value to scene irradiance.
Calibration images, data, and curves in lookup table format. Download: 16 MB [.zip] |
Organized GroundTruth Point Clouds |
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Description: Organized point clouds are
3-channel images mapping 3D LIDAR scan points to projected
locations in a rectified coordinate system. Useful to compare
pixel-wise errors with intensity images. Download:380 MB [.zip] |
Dataset Tools and Code |
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Description: Matlab functions and scripts for
programmatically parsing, loading and manipulating the data. Download: Preparation of the code for open-source release is currently in progress. Please check back in the future. |