{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:23:45Z","timestamp":1760243025379,"version":"build-2065373602"},"reference-count":31,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2015,5,29]],"date-time":"2015-05-29T00:00:00Z","timestamp":1432857600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, a new method to solve computational problems using reaction diffusion (RD) systems is presented. The novelty relies on the use of a model configuration that tailors its spatiotemporal dynamics to develop Voronoi diagrams (VD) as a part of the system\u2019s natural evolution. The proposed framework is deployed in a solution of related robotic problems, where the generalized VD are used to identify topological places in a grid map of the environment that is created from sensor measurements. The ability of the RD-based computation to integrate external information, like a grid map representing the environment in the model computational grid, permits a direct integration of sensor data into the model dynamics. The experimental results indicate that this method exhibits significantly less sensitivity to noisy data than the standard algorithms for determining VD in a grid. In addition, previous drawbacks of the computational algorithms based on RD models, like the generation of volatile solutions by means of excitable waves, are now overcome by final stable states.<\/jats:p>","DOI":"10.3390\/s150612736","type":"journal-article","created":{"date-parts":[[2015,5,29]],"date-time":"2015-05-29T10:37:21Z","timestamp":1432895841000},"page":"12736-12764","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Reaction Diffusion Voronoi Diagrams: From Sensors Data to Computing"],"prefix":"10.3390","volume":"15","author":[{"given":"Alejandro","family":"V\u00e1zquez-Otero","sequence":"first","affiliation":[{"name":"Department of Computer Sciences and Automatic Control, UNED, C\/ Juan del Rosal, 16, Madrid 28040, Spain"},{"name":"Institute of Physics ASCR, Na Slovance 2, 18221 Prague 8, Czech Republic"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6193-0792","authenticated-orcid":false,"given":"Jan","family":"Faigl","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Electrical Engineering, Czech Technical University in Prague, Technicka 2, 16627 Prague 6, Czech Republic"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1175-5065","authenticated-orcid":false,"given":"Raquel","family":"Dormido","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences and Automatic Control, UNED, C\/ Juan del Rosal, 16, Madrid 28040, Spain"}]},{"given":"Natividad","family":"Duro","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences and Automatic Control, UNED, C\/ Juan del Rosal, 16, Madrid 28040, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2015,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Walgraef, D. 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