Data for SLAM Datasets

<div>This project contains a dataset generated with a Kobuki Turtlebot 2 and a RP LiDAR A2. The goal of the project is that the user can experiment the issues that LiDAR has detecting glass walls or mapping with excessive light. The topics available contain robot odometry, laser scans, poseupdates, commands given to the robot, its trajectory, clocks, and the needed transforms to perform a map. With the bags included in bag folder you can replicate the ros topics generated during an indoor walkthrough of UC3M corridors.</div> <div> <div>This information can also be found in the next link, please check it for updates: <a href="https://gitlab.netcom.it.uc3m.es/predict-6g/slam-datasets" target="_blank" rel="noopener">PREDICT 6G / SLAM Datasets &middot; GitLab (uc3m.es)</a></div> <div>&nbsp;</div> <div> <p><em>This work has been partly funded by the European Commission Horizon Europe SNS JU&nbsp;<a href="https://predict-6g.eu/" target="_blank" rel="nofollow noreferrer noopener">PREDICT-6G</a>&nbsp;(GA 101095890) and&nbsp;<a href="https://hexa-x-ii.eu/" target="_blank" rel="nofollow noreferrer noopener">Hexa-X-II</a>&nbsp;(GA 101095759) projects, and the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union-NextGeneration-EU through the UNICO 5G I+D&nbsp;<a href="https://unica6g.it.uc3m.es/6g-edgedt/" target="_blank" rel="nofollow noreferrer noopener">6G-EDGEDT</a>&nbsp;and&nbsp;<a href="https://unica6g.it.uc3m.es/6g-datadriven/" target="_blank" rel="nofollow noreferrer noopener">6G-DATADRIVEN</a>.</em></p> <p><em>This work has been funded by the Spanish Ministry of Economic Affairs and Digital Transformation under European Union NextGeneration-EU projects TSI-063000-2021-59 RISC6G and TSI-063000-2021-63 MAP-6G.</em></p> </div> </div>