Hilti SLAM Challenge

Introduced by Helmberger et al. in The Hilti SLAM Challenge Dataset

Hilti SLAM Challenge is a dataset for Simultaneous Localization and Mapping (SLAM) algorithms due to sparsity, varying illumination conditions, and dynamic objects. The sensor platform used to collect this dataset contains a number of visual, lidar and inertial sensors which have all been rigorously calibrated. All data is temporally aligned to support precise multi-sensor fusion. Each dataset includes accurate ground truth to allow direct testing of SLAM results. Raw data as well as intrinsic and extrinsic sensor calibration data from twelve datasets in various environments is provided. Each environment represents common scenarios found in building construction sites in various stages of completion.

Papers


Paper Code Results Date Stars

Dataset Loaders


No data loaders found. You can submit your data loader here.

Tasks


License


  • Unknown

Modalities


Languages