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Benchmark Maps
CROOS-CV
HOWS-CL-25
Long Range Navigation Tests (LRNTs)
Marokko-Navigations-Tests
Minimal Texture Dataset for RGB-D SLAM
MMX Nav Testing
ReSyRIS
s3li dataset
StereoInstancesOnSurfaces
THR Dataset
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Scientific datasets
Benchmark Maps
2.5D elevation maps of planetary environment that were collected on Mt. Etna during the space-analogous ARCHES mission. In addition to the raw elevation maps, we provide cost maps that encode the traversibility of the terrain.
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CROOS-CV
The CROOS-CV dataset is intended to support and benchmark Computer Vision (CV) development for Close Range On-Orbit Servicing (CROOS). It is an representative image dataset for CROOS operations with distances of 2 m between servicer and client satellite that was recorded under illumination conditions similar to a Low Earth Orbit.
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HOWS-CL-25
HOWS-CL-25 is a synthetic dataset especially designed for object classification on mobile robots operating in a changing environment (like a household), where it is important to learn new, never seen objects on the fly.
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Long Range Navigation Tests (LRNTs)
During the ROBEX demo mission space campaign that took place during June–July 2017 on Mt. Etna, Italy, we performed some Long Range Navigation Tests.
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Morocco Navigation Tests
The Institute was part of the PERASPERA Space Robotics Technologies Cluster in the operational grants OG3 and OG6. In that context, the research group participated in the 2018 November/December field test in the Moroccan desert close to the city of Erfoud.
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Minimal Texture Dataset for RGB-D SLAM
The Minimal Texture Dataset for RGB-SLAM consists of 16 challenging sequences for RGB-D SLAM in textureless environments.
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MMX Navigation Testing Data Set
Public collection of test data that is used to test the DLR Autonomous Navigation Experiment on the MMX Rover for Phobos
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Planetary Stereo Solid-State LiDAR Inertial Dataset
e release a dataset recorded on the Moon-like environment of Mount Etna, Sicily, with a sensor setup that comprises a stereo camera, a LiDAR and an IMU.
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ReSyRIS
The Real-Synthetic Rock Instance Segmentation dataset (ReSyRIS) is created for training and evaluation of rock segmentation, detection and instance segmentation in (quasi-)extra-terrestrial environments.
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STIOS
The Stereo Instances on Surfaces Datensatz (STIOS) is created for evaluation of instance-based algorithm and mainly intended for robotic applications, which is why the dataset refers to horizontal surfaces.
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THR Dataset
The THR (Top Hat Rail) data set consists of color and depth images from different objects taken from multiple views in different scenes. The data set consists of 9 object classes and can be used e.g. to improve perception algorithms by learning.
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