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We have investigated this problem using robots with compatible visual sensing capabilities and with each robot having its individual long-term place memory. Here, each place refers to a spatial region as defined by a collection of appearances and in the place memory, the knowledge is organized in a tree hierarchy. In the proposed merging approach, the hierarchical organization plays a key role\u2014as it corresponds to a nested sequence of hyperspheres in the appearance space. The merging proceeds by considering the extent of overlap of the respective nested hyperspheres\u2014starting with the largest covering hypersphere. Thus, differing from related work, knowledge is merged in as large chunks as possible while the hierarchical structure is preserved accordingly. As such, the merging scales better as the extent of knowledge to be merged increases. This is demonstrated in an extensive set of multirobot experiments where robots share their knowledge and then use their merged knowledge when visiting these places.<\/jats:p>","DOI":"10.1007\/s10514-020-09911-2","type":"journal-article","created":{"date-parts":[[2020,3,26]],"date-time":"2020-03-26T18:04:20Z","timestamp":1585245860000},"page":"1009-1027","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Merging of appearance-based place knowledge among multiple robots"],"prefix":"10.1007","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6671-9366","authenticated-orcid":false,"given":"Hakan","family":"Karao\u011fuz","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"H. 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