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- W4323767907 abstract "In the last decades, numerous simultaneous localization and mapping (SLAM) methods based on different sensors have been proposed. However, it is still an open research problem to achieve robust SLAM in harsh environments. Compared to LiDAR and camera, millimeter wave radar can operate well under different weather and lack of light conditions. In this paper, an error state Kalman filter (ESKF) based SLAM algorithm is proposed. It utilizes a millimeter wave radar and an inertial measurement unit (IMU) to estimate the location of the unmanned vehicle and the mapping result of the surroundings. The unmanned vehicle state is estimated by the state prediction, registration, and the state update step, and the surrounding environment is constructed into a map through the map update step. The proposed algorithm is evaluated via experiment." @default.
- W4323767907 created "2023-03-11" @default.
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- W4323767907 date "2023-01-01" @default.
- W4323767907 modified "2023-09-27" @default.
- W4323767907 title "An ESKF Based SLAM Approach with Millimeter Wave Radar and IMU" @default.
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- W4323767907 doi "https://doi.org/10.1007/978-981-99-0479-2_214" @default.
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