--- license: cc-by-4.0 pretty_name: xclean 3-D maps tags: - slam - gaussian-splatting - 3d-reconstruction - visual-inertial-odometry --- # xclean 3-D maps 3-D Gaussian-splat maps reconstructed by **Necessity Robotics** with **xclean**, a real-time stereo visual-inertial SLAM system. They are the map files behind the 3-D viewer on https://necessityrobotics.github.io. Every map uses xclean's own live camera poses, from the median of three runs on the final board, not ground truth. Each map's `ATTRIBUTION.json` states its limitations as they are. | map | source data | source licence | |---|---|---| | oak_161834 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data | | oak_160543 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data | | oak_164002 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data | | oak_164424 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data | | oak_161206 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data | | rosario_01 | The Rosario Dataset (CIFASIS-CONICET), https://robot.cifasis-conicet.gov.ar/ | CC BY 4.0 | | rosario_03 | The Rosario Dataset (CIFASIS-CONICET), https://robot.cifasis-conicet.gov.ar/ | CC BY 4.0 | | rosario_04 | The Rosario Dataset (CIFASIS-CONICET), https://robot.cifasis-conicet.gov.ar/ | CC BY 4.0 | ## Licence and credit - The maps are released under **CC BY 4.0**. - Maps made from the Rosario Dataset must also credit the source: "The Rosario Dataset, CIFASIS-CONICET, CC BY 4.0 (Pire et al., IJRR 2019)". The changes: a 3-D map was reconstructed from its images. - The OAK maps come from Necessity Robotics' own recordings. ## Files per map - `splats.spz`: the viewer's standard tier. - `splats_lite.*`: the phone / quick tier. - `full/splats.ply`: full resolution. - `points.bin` / `points.json`: the sparse point cloud. - `traj.json`: the camera path. - `keyframes/`: small keyframe images. - `film/`: the fly-through video. - `ATTRIBUTION.json` and `manifest.json` describe the map.