000131604 001__ 131604 000131604 005__ 20240212142201.0 000131604 0247_ $$2doi$$a10.1109/ACCESS.2024.3357400 000131604 0248_ $$2sideral$$a136927 000131604 037__ $$aART-2024-136927 000131604 041__ $$aeng 000131604 100__ $$0(orcid)0000-0002-8949-2632$$aPérez-Yus, Alejandro$$uUniversidad de Zaragoza 000131604 245__ $$aRASPV: A robotics framework for augmented simulated prosthetic vision 000131604 260__ $$c2024 000131604 5060_ $$aAccess copy available to the general public$$fUnrestricted 000131604 5203_ $$aOne 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 000131604 536__ $$9info:eu-repo/grantAgreement/ES/MICINN-AEI/PID2021-125209OB-I00$$9info:eu-repo/grantAgreement/ES/UZ/JIUZ-2022-IAR-05 000131604 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/ 000131604 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000131604 700__ $$aSantos-Villafranca, María$$uUniversidad de Zaragoza 000131604 700__ $$aTomás-Barba, Julia 000131604 700__ $$0(orcid)0000-0002-8479-1748$$aBermúdez-Cameo, Jesús$$uUniversidad de Zaragoza 000131604 700__ $$aMontano-Oliván, Lorenzo 000131604 700__ $$0(orcid)0000-0001-9347-5969$$aLópez-Nicolás, Gonzalo$$uUniversidad de Zaragoza 000131604 700__ $$0(orcid)0000-0001-5209-2267$$aGuerrero, José J.$$uUniversidad de Zaragoza 000131604 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát. 000131604 773__ $$g12 (2024), 15251-15267$$pIEEE Access$$tIEEE Access$$x2169-3536 000131604 8564_ $$s9754975$$uhttps://zaguan.unizar.es/record/131604/files/texto_completo.pdf$$yVersión publicada 000131604 8564_ $$s2673904$$uhttps://zaguan.unizar.es/record/131604/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000131604 909CO $$ooai:zaguan.unizar.es:131604$$particulos$$pdriver 000131604 951__ $$a2024-02-12-13:57:38 000131604 980__ $$aARTICLE