The POLAR Traverse Dataset: A Dataset of Stereo Camera Images Simulating Traverses across Lunar Polar Terrain under Extreme Lighting Conditions
This dataset addresses the challenge of testing navigation algorithms for lunar polar environments, where lighting conditions are harsh and unpredictable, though it is incremental as it provides new simulated data rather than a novel method.
The authors created the POLAR Traverse Dataset, a high-fidelity stereo image dataset simulating lunar polar terrain traverses under extreme lighting, to aid in developing algorithms like visual odometry for lunar missions.
We present the POLAR Traverse Dataset: a dataset of high-fidelity stereo pair images of lunar-like terrain under polar lighting conditions designed to simulate a straight-line traverse. Images from individual traverses with different camera heights and pitches were recorded at 1 m intervals by moving a suspended stereo bar across a test bed filled with regolith simulant and shaped to mimic lunar south polar terrain. Ground truth geometry and camera position information was also recorded. This dataset is intended for developing and testing software algorithms that rely on stereo or monocular camera images, such as visual odometry, for use in the lunar polar environment, as well as to provide insight into the expected lighting conditions in lunar polar regions.