Bibliography

[ABN+24]

Fernando J. Aguilar, José-Luis Blanco, Abderrahim Nemmaoui, Fernando Cañadas-Aránega, Manuel Aguilar, and Jose Carlos Moreno. Preliminary results of a low-cost portable terrestrial lidar based on icp-slam algorithms. application to automatic forest digital inventory. In 6th Euro-Mediterranean Conference for Environmental Integration (EMCEI-2024). may 2024.

[BPM24]

Vedant Bhandari, Tyson Govan Phillips, and Peter Ross McAree. Minimal configuration point cloud odometry and mapping. The International Journal of Robotics Research, pages 02783649241235325, 2024.

[BC19a]

José Luis Blanco Claraco. A modular optimization framework for localization and mapping. In Robotics: Science and Systems (RSS 2019). 2019.

[BC19b]

José Luis Blanco Claraco. OLAE-ICP: robust and fast alignment of geometric features with the optimal linear attitude estimator. CoRR, 2019. URL: http://arxiv.org/abs/1906.10783, arXiv:1906.10783.

[BC24]

José Luis Blanco Claraco. A flexible framework for accurate LiDAR odometry, map manipulation, and localization. ArXiV, 2024. URL: https://arxiv.org/abs/2407.20465.

[CanadasAranegaBCMRD24]

Fernando Cañadas Aránega, José Luis Blanco Claraco, Jose Carlos Moreno, and Francisco Rodriguez-Diaz. Mobile robotic dataset for a typical mediterranean greenhouse: the greenbot dataset. Sensors, jan 2024. URL: https://arm.ual.es/arm-group/dataset-greenhouse-2024/, doi:10.3390/s24061874.

[GLSU13]

Andreas Geiger, Philip Lenz, Christoph Stiller, and Raquel Urtasun. Vision meets robotics: the kitti dataset. The International Journal of Robotics Research, 32(11):1231–1237, 2013.

[VGM+23]

Ignacio Vizzo, Tiziano Guadagnino, Benedikt Mersch, Louis Wiesmann, Jens Behley, and Cyrill Stachniss. Kiss-icp: in defense of point-to-point icp–simple, accurate, and robust registration if done the right way. IEEE Robotics and Automation Letters, 8(2):1029–1036, 2023.