Fusing the RGBD SLAM with Wheel Odometry
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F19%3APU133890" target="_blank" >RIV/00216305:26220/19:PU133890 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2405896319326734" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2405896319326734</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Fusing the RGBD SLAM with Wheel Odometry
Original language description
This paper deals with data fusion of existing visual SLAM algorithm and wheel odometry. The result of this connection is the possibility of suppressing measurement error of each position estimation method and creating more accurate 3D model of the examined environment. We have made a brief review of existing visual SLAM projects that are available in open-source domain and as the best option we have choose the Elastic Fusion project and we enriched the existing localization pipeline with another data source that is realized by our high-precision odometry vehicle frame. The modified technique has been validated on three different scenarios. The result is the more robust SLAM algorithm and better precision 3D model of sensed environment compared to original one.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
20204 - Robotics and automatic control
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů