DLR Planetary Stereo Solid-State LiDAR Inertial Dataset

 

We 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. The dataset is intended to expose several factors that challenge visual- and LiDAR-based localization and mapping pipelines, when operating in severely unstructured environments. The harsh lighting conditions, combined with extreme visual aliasing, as well as the lack of salient structures, limit the possibility of performing place recognition through traditional approaches. Furthermore, the LiDAR sensor, employed in this dataset, is built relying on novel Solid-State technologies, that have promising characteristics for their implementation in space applications. The narrow Field-of-View (~70H x 30V) of the LiDAR, combined with the geometry of the landscape, does not allow to implement traditional LiDAR SLAM, and require to investigate the usage of the sensor as a complement to the visual inputs. This dataset offers 7 sequences, with peculiar characteristics in terms of type of trajectories and type of landscape, with accurate D-GNSS ground truth.

Corresponding Publication – How to cite us:

R. Giubilato, W. Stürzl, A. Wedler and R. Triebel, „Challenges of SLAM in extremely unstructured environments: the DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset,“ in IEEE Robotics and Automation Letters, 2022,

 

BibTex:

@ARTICLE{9813579,
  author={Giubilato, Riccardo and Stürzl, Wolfgang and Wedler, Armin and Triebel, Rudolph},  
  journal={IEEE Robotics and Automation Letters},   
  title={Challenges of SLAM in extremely unstructured environments: the DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset},   
  year={2022},  
  volume={},  
  number={},  
  pages={1-8},  
  doi={10.1109/LRA.2022.3188118}}

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