doi:10.1109/LRA.2023.3251722engFontan, AlejandroGiubilato, RiccardoMaza, Laura OlivaCivera, JavierTriebel, RudolphSID-SLAM: Semi-Direct Information-Driven RGB-D SLAMART-2023-135269This work presents SID-SLAM, a complete SLAM framework for RGB-D cameras. Our main contribution is a semi-direct approach that, for the first time, combines tightly and indistinctly photometric and feature-based image measurements. Additionally, SID-SLAM uses information metrics to reduce the state size with a minimal impact in the accuracy. Our evaluation on several public datasets shows that we achieve state-of-the-art performance regarding accuracy, robustness and computational footprint in CPU real time. In order to facilitate research on semi-direct SLAM, we record the Minimal Texture dataset, composed by RGB-D sequences challenging for current baselines and in which our pipeline excels.2023http://zaguan.unizar.es/record/12813410.1109/LRA.2023.3251722http://zaguan.unizar.es/record/128134oai:zaguan.unizar.es:128134info:eu-repo/grantAgreement/ES/DGA/T45-20Rinfo:eu-repo/grantAgreement/ES/MICINN/PID2021-127685NB-I00info:eu-repo/grantAgreement/EUR/MICINN/TED2021-131150B-I00IEEE Robotics and Automation Letters 8, 10 (2023), 6387-6394All rights reservedhttp://www.europeana.eu/rights/rr-f/info:eu-repo/semantics/openAccess