DC Field | Value | Language |
---|---|---|
dc.contributor.author | HYUN, JIEUM | ko |
dc.contributor.author | Myung, Hyun | ko |
dc.date.accessioned | 2020-07-02T00:20:15Z | - |
dc.date.available | 2020-07-02T00:20:15Z | - |
dc.date.created | 2020-06-25 | - |
dc.date.created | 2020-06-25 | - |
dc.date.issued | 2020-06-22 | - |
dc.identifier.citation | The 17th International Conference on Ubiquitous Robots (UR 2020) | - |
dc.identifier.uri | http://hdl.handle.net/10203/275084 | - |
dc.description.abstract | Ultra-wideband(UWB)-based simultaneous localization and mapping(SLAM) researches has been widely studied to replace situations where vision-based sensors or global positioning system(GPS) signals are not available. In this paper, we propose an extended Kalman filter(EKF) SLAM framework for estimating position and orientation of a robot and UWB anchors. The framework consists of three main processes: initialization of position of a UWB anchor, pre-integration of an inertial measurement unit(IMU) sensor measurement, and the EKF framework. A state vector of the system augmented with bias of a gyroscope, scale factor of a gyroscope, and bias of an accelerometer is estimated from the UWB-IMU tightly-coupled EKF framework. With the performance test for positioning of a robot when UWB anchors are fixed or moved, it is verified that position root-mean-square-error(RMSE) is less than 20 cm. | - |
dc.language | English | - |
dc.publisher | Korea Robot Society | - |
dc.title | UWB-inertial SLAM based on Tightly-coupled EKF Framework | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | The 17th International Conference on Ubiquitous Robots (UR 2020) | - |
dc.identifier.conferencecountry | JA | - |
dc.identifier.conferencelocation | Virtual Conference | - |
dc.contributor.localauthor | Myung, Hyun | - |
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