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Reliability of visual inertial odometry on an unmanned aerial vehicle

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dc.contributor.author Setati, Tiro
dc.contributor.author Maweni, Thabisa
dc.contributor.author Botha, Natasha
dc.date.accessioned 2024-02-07T06:39:23Z
dc.date.available 2024-02-07T06:39:23Z
dc.date.issued 2023-11
dc.identifier.citation Setati, T., Maweni, T. & Botha, N. 2023. Reliability of visual inertial odometry on an unmanned aerial vehicle. http://hdl.handle.net/10204/13582 . en_ZA
dc.identifier.uri http://hdl.handle.net/10204/13582
dc.description.abstract There is a need to ensure that an Unmanned Aerial Vehicle (UAV) can fly safely in indoor environments. In this paper, the visual inertial odometry (VIO) implemented in a commercial UAV is tested to determine its reliability to keep its position in confined indoor spaces. The experimental results indicated that the UAV was able to track the subjectfrom an average distance of 3915.23 mm in the y-direction, with RMSEx and RMSEy of 452.47 mm and 332.66 mm, respectively. This shows that the UAV can track objects in confined environments, such as the aisles of an indoor warehouse en_US
dc.format Fulltext en_US
dc.language.iso en en_US
dc.relation.uri https://site.rapdasa.org/wp-content/uploads/2023/10/RAPDASA-Annual-Conference-Book-Complete.pdf en_US
dc.source RAPDASA-RobMech-PRASA-AMI Conference, CSIR International Convention Centre, Pretoria, South Africa, 30 October – 2 November 2023 en_US
dc.subject Unmanned Aerial Vehicle en_US
dc.subject UAV en_US
dc.subject Visual inertial odometry en_US
dc.subject VIO en_US
dc.title Reliability of visual inertial odometry on an unmanned aerial vehicle en_US
dc.type Conference Presentation en_US
dc.description.pages 8 en_US
dc.description.note © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (https://creativecommons.org/licenses/by/4.0/). The item was also presented as a paper at RAPDASA-RobMech-PRASA-AMI Conference, CSIR International Convention Centre, Pretoria, South Africa, 30 October – 2 November 2023. en_US
dc.description.cluster Manufacturing en_US
dc.description.impactarea Industrial AI en_US
dc.identifier.apacitation Setati, T., Maweni, T., & Botha, N. (2023). Reliability of visual inertial odometry on an unmanned aerial vehicle. http://hdl.handle.net/10204/13582 en_ZA
dc.identifier.chicagocitation Setati, Tiro, Thabisa Maweni, and Natasha Botha. "Reliability of visual inertial odometry on an unmanned aerial vehicle." <i>RAPDASA-RobMech-PRASA-AMI Conference, CSIR International Convention Centre, Pretoria, South Africa, 30 October – 2 November 2023</i> (2023): http://hdl.handle.net/10204/13582 en_ZA
dc.identifier.vancouvercitation Setati T, Maweni T, Botha N, Reliability of visual inertial odometry on an unmanned aerial vehicle; 2023. http://hdl.handle.net/10204/13582 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Setati, Tiro AU - Maweni, Thabisa AU - Botha, Natasha AB - There is a need to ensure that an Unmanned Aerial Vehicle (UAV) can fly safely in indoor environments. In this paper, the visual inertial odometry (VIO) implemented in a commercial UAV is tested to determine its reliability to keep its position in confined indoor spaces. The experimental results indicated that the UAV was able to track the subjectfrom an average distance of 3915.23 mm in the y-direction, with RMSEx and RMSEy of 452.47 mm and 332.66 mm, respectively. This shows that the UAV can track objects in confined environments, such as the aisles of an indoor warehouse DA - 2023-11 DB - ResearchSpace DP - CSIR J1 - RAPDASA-RobMech-PRASA-AMI Conference, CSIR International Convention Centre, Pretoria, South Africa, 30 October – 2 November 2023 KW - Unmanned Aerial Vehicle KW - UAV KW - Visual inertial odometry KW - VIO LK - https://researchspace.csir.co.za PY - 2023 T1 - Reliability of visual inertial odometry on an unmanned aerial vehicle TI - Reliability of visual inertial odometry on an unmanned aerial vehicle UR - http://hdl.handle.net/10204/13582 ER - en_ZA
dc.identifier.worklist 27451 en_US


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