131604 20260306152057.0 doi 10.1109/ACCESS.2024.3357400 sideral 136927 ART-2024-136927 eng Pérez-Yus, Alejandro Universidad de Zaragoza (orcid)0000-0002-8949-2632 RASPV: A robotics framework for augmented simulated prosthetic vision 2024 Access copy available to the general public Unrestricted One of the main challenges of visual prostheses is to augment the perceived information to improve the experience of its wearers. Given the limited access to implanted patients, in order to facilitate the experimentation of new techniques, this is often evaluated via Simulated Prosthetic Vision (SPV) with sighted people. In this work, we introduce a novel SPV framework and implementation that presents major advantages with respect to previous approaches. First, it is integrated into a robotics framework, which allows us to benefit from a wide range of methods and algorithms from the field (e.g. object recognition, obstacle avoidance, autonomous navigation, deep learning). Second, we go beyond traditional image processing with 3D point clouds processing using an RGB-D camera, allowing us to robustly detect the floor, obstacles and the structure of the scene. Third, it works either with a real camera or in a virtual environment, which gives us endless possibilities for immersive experimentation through a head-mounted display. Fourth, we incorporate a validated temporal phosphene model that replicates time effects into the generation of visual stimuli. Finally, we have proposed, developed and tested several applications within this framework, such as avoiding moving obstacles, providing a general understanding of the scene, staircase detection, helping the subject to navigate an unfamiliar space, and object and person detection. We provide experimental results in real and virtual environments. The code is publicly available at https://www.github.com/aperezyus/RASPV info:eu-repo/grantAgreement/ES/MICINN-AEI/PID2021-125209OB-I00 info:eu-repo/grantAgreement/ES/UZ/JIUZ-2022-IAR-05 info:eu-repo/semantics/openAccess by-nc-nd https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es 3.6 2024 COMPUTER SCIENCE, INFORMATION SYSTEMS 93 / 258 = 0.36 2024 Q2 T2 TELECOMMUNICATIONS 51 / 120 = 0.425 2024 Q2 T2 ENGINEERING, ELECTRICAL & ELECTRONIC 130 / 368 = 0.353 2024 Q2 T2 0.849 2024 Engineering (miscellaneous) 2024 Q1 Computer Science (miscellaneous) 2024 Q1 Materials Science (miscellaneous) 2024 Q2 9.0 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Santos-Villafranca, María Universidad de Zaragoza (orcid)0009-0009-5663-3185 Tomás-Barba, Julia Bermúdez-Cameo, Jesús Universidad de Zaragoza (orcid)0000-0002-8479-1748 Montano-Oliván, Lorenzo López-Nicolás, Gonzalo Universidad de Zaragoza (orcid)0000-0001-9347-5969 Guerrero, José J. Universidad de Zaragoza (orcid)0000-0001-5209-2267 5007 520 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Ingen.Sistemas y Automát. 12 (2024), 15251-15267 IEEE Access IEEE Access 2169-3536 9754975 http://zaguan.unizar.es/record/131604/files/texto_completo.pdf Versión publicada 2673904 http://zaguan.unizar.es/record/131604/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:131604 articulos driver 2026-03-06-15:18:44 ARTICLE