de Miguel, Miguel ÁngelAl-Kaff, AbdullaGarcía, FernandoGuindel, Carlos2024-11-042024-11-042023-06-01M. Á. de Miguel, C. Guindel, A. Al-Kaff and F. García, "High-Accuracy Patternless Calibration of Multiple 3-D LiDARs for Autonomous Vehicles," in IEEE Sensors Journal, vol. 23, no. 11, pp. 12200-12208, 1 June1, 2023, doi: 10.1109/JSEN.2023.32683381530-437X (print)1558-1748 (online)https://hdl.handle.net/10115/41029This work has been supported by the Madrid Government (Comunidad de MadridSpain) under the Multiannual Agreement with UC3M (“Fostering Young Doctors Research”, APBI-CM-UC3M), and in the context of the V PRICIT (Research and Technological Innovation Regional Programme), and also by the Spanish Government through the projects ID2021-128327OA-I00 and TED2021-129374AI00 funded by MCIN/AEI /10.13039/501100011033 and by the European Union NextGenerationEU/PRTR. The authors also acknowledge support from the Ministry of Universities, the Universidad Carlos III de Madrid’s Call for Grants for the requalification of the Spanish university system for 2021-2023, of May 31, 2022, and the Universidad Carlos III de Madrid’s Call for Grants for the requalification of the Spanish university system for 2021-2023, dated July 1, 2021, based on Royal Decree 289/2021, dated April 20, 2021, which regulates the direct granting of subsidies to public universities for the requalification of the Spanish university systemThis article proposes a new method for estimating the extrinsic calibration parameters between any pair of multibeam LiDAR sensors on a vehicle. Unlike many state-of-the-art works, this method does not use any calibration pattern or reflective marks placed in the environment to perform the calibration; in addition, the sensors do not need to have overlapping fields of view. An iterative closest point (ICP)-based process is used to determine the values of the calibration parameters, resulting in better convergence and improved accuracy. Furthermore, a setup based on the car learning to act (CARLA) simulator is introduced to evaluate the approach, enabling quantitative assessment with ground-truth data. The results show an accuracy comparable with other approaches that require more complex procedures and have a more restricted range of applicable setups. This work also provides qualitative results on a real setup, where the alignment between the different point clouds can be visually checked. The open-source code is available at https://github.com/midemig/pcd_calib.engAtribución 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/article10.1109/JSEN.2023.3268338info:eu-repo/semantics/openAccess