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Using self-organizing hierarchy, aspects of centralization and decentralization can be combined: robots can understand their relative positions system-wide and fuse their information at one point, without requiring, e.g., a fully connected or static communication network. In this way, multi-sensor fusion techniques that were designed for fully centralized systems can be applied to a self-organized system for the first time, without losing the key practical benefits of decentralization. We implement simple proof-of-concept fusion in a self-organizing hierarchy approach and test it against three fully decentralized benchmark approaches. We test the perceptual accuracy of the approaches for absolute conditions that are uniform time-invariant, time-varying, and spatially nonuniform with high heterogeneity, as well as the scalability and fault tolerance of their accuracy. We show that, under our tested conditions, the self-organizing hierarchy approach is generally more accurate, more consistent, and faster than the other approaches and also that its accuracy is more scalable and comparably fault-tolerant. Under spatially nonuniform conditions, our results indicate that the four approaches are comparable in terms of similarity to the reference samples. In future work, extending these results to additional methods, such as collective probability distribution fitting, is likely to be much more straightforward in the self-organizing hierarchy approach than in the decentralized approaches.<\/jats:p>","DOI":"10.34133\/icomputing.0044","type":"journal-article","created":{"date-parts":[[2023,7,4]],"date-time":"2023-07-04T16:26:24Z","timestamp":1688487984000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark_01","source":"Crossref","is-referenced-by-count":3,"title":["Reducing Uncertainty in Collective Perception Using Self-Organizing Hierarchy"],"prefix":"10.34133","volume":"2","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2628-1309","authenticated-orcid":false,"given":"Aryo","family":"Jamshidpey","sequence":"first","affiliation":[{"name":"IRIDIA, Universit\u00e9 Libre de Bruxelles, Brussels, Belgium."},{"name":"University of Ottawa, Ottawa, Canada."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3971-0507","authenticated-orcid":false,"given":"Marco","family":"Dorigo","sequence":"additional","affiliation":[{"name":"IRIDIA, Universit\u00e9 Libre de Bruxelles, Brussels, Belgium."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1595-8487","authenticated-orcid":true,"given":"Mary Katherine","family":"Heinrich","sequence":"additional","affiliation":[{"name":"IRIDIA, Universit\u00e9 Libre de Bruxelles, Brussels, Belgium."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"221","published-online":{"date-parts":[[2023,9,13]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.3389\/frobt.2019.00016"},{"issue":"49","key":"e_1_3_4_3_2","doi-asserted-by":"crossref","first-page":"abe4385","DOI":"10.1126\/scirobotics.abe4385","article-title":"Reflections on the future of swarm robotics","volume":"5","author":"Dorigo M","year":"2020","unstructured":"Dorigo M, Theraulaz G, Trianni V. 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