Mo-SLAM: Multi object SLAM with run-time object discovery through duplicates

Thanuja Dharmasiri, Vincent Lui, Tom Drummond

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

14 Citations (Scopus)


In this paper, we present MO-SLAM, a novel visual SLAM system that is capable of detecting duplicate objects in the scene during run-time without requiring an offline training stage to pre-populate a database of objects. Instead, we propose a novel method to detect landmarks that belong to duplicate objects. Further, we show how landmarks belonging to duplicate objects can be converted to first-order entities which generate additional constraints for optimizing the map. We evaluate the performance of MO-SLAM with extensive experiments on both synthetic and real data, where the experimental results verify the capabilities of MO-SLAM in detecting duplicate objects and using these constraints to improve the accuracy of the map.

Original languageEnglish
Title of host publication2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016)
Subtitle of host publicationDaejeon, South Korea, 9-14 October, 2016
EditorsWolfram Burgard
Place of PublicationPiscataway, NJ
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages8
ISBN (Electronic)9781509037629
ISBN (Print)9781509037636
Publication statusPublished - 28 Nov 2016
EventIEEE/RSJ International Conference on Intelligent Robots and Systems 2016 - Daejeon, Korea, Republic of (South)
Duration: 9 Oct 201614 Oct 2016 (Proceedings)


ConferenceIEEE/RSJ International Conference on Intelligent Robots and Systems 2016
Abbreviated titleIROS 2016
Country/TerritoryKorea, Republic of (South)
Internet address

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