Bibliography
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.
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.
José Luis Blanco Claraco. A modular optimization framework for localization and mapping. In Robotics: Science and Systems (RSS 2019). 2019.
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.
José Luis Blanco Claraco. A flexible framework for accurate LiDAR odometry, map manipulation, and localization. ArXiV, 2024. URL: https://arxiv.org/abs/2407.20465.
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.
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.
Giseop Kim, Yeong Sang Park, Younghun Cho, Jinyong Jeong, and Ayoung Kim. Mulran: multimodal range dataset for urban place recognition. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). Paris, May 2020.
Martin Magnusson, Achim Lilienthal, and Tom Duckett. Scan registration for autonomous mining vehicles using 3d-ndt. Journal of Field Robotics, 24(10):803–827, 2007.
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.