A distributed framework for monocular visual SLAM
| dc.contributor.author | Egoda Gamage, Ruwan | |
| dc.contributor.author | Tuceryan, Mihran | |
| dc.contributor.department | Computer and Information Science, School of Science | en_US |
| dc.date.accessioned | 2018-04-26T17:43:39Z | |
| dc.date.available | 2018-04-26T17:43:39Z | |
| dc.date.issued | 2017-04 | |
| dc.description.abstract | In Distributed Simultaneous Localization and Mapping (SLAM), multiple agents generate a global map of the environment while each performing its local SLAM operation. One of the main challenges is to identify overlapping maps, especially when agents do not know their relative starting positions. In this paper we are introducing a distributed framework which uses an appearance based method to identify map overlaps. Our framework generates a global semi-dense map using multiple monocular visual SLAM agents, each localizing itself in this map. | en_US |
| dc.eprint.version | Author's manuscript | en_US |
| dc.identifier.citation | Egodagamage, R., & Tuceryan, M. (2017). A distributed framework for monocular visual SLAM (pp. 55–61). Presented at the 28th Modern Artificial Intelligence and Cognitive Science Conference, MAICS 2017. | en_US |
| dc.identifier.uri | https://hdl.handle.net/1805/15917 | |
| dc.language.iso | en | en_US |
| dc.relation.journal | Proceedings of the 28th Modern Artificial Intelligence and Cognitive Science Conference 2017 | en_US |
| dc.rights | Publisher Policy | en_US |
| dc.source | Author | en_US |
| dc.subject | Simultaneous Localization and Mapping | en_US |
| dc.subject | distributed framework | en_US |
| dc.subject | monocular visual SLAM | en_US |
| dc.title | A distributed framework for monocular visual SLAM | en_US |
| dc.type | Conference proceedings | en_US |