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- W4384009593 abstract "Abastact- The roadheader is an important equipment for mining coal underground, and precise positioning is the key technology for the intelligentization of the roadheader. This paper proposes a machine learning-based ultra wide band-inertial measurement unit (UWB-IMU) positioning method for the roadheader. By fitting the nonlinear transformation relationship between the 16 ranging values of UWB, 2 attitude angles of IMU, and the position and yaw angle of the roadheader using machine learning, the three-axis position average absolute error of the method is less than 0.10m, and the average absolute error of the three-axis attitude angle is less than 1°, which meets the positioning requirements of the roadway roadheader according to experimental verification." @default.
- W4384009593 created "2023-07-13" @default.
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- W4384009593 date "2023-05-19" @default.
- W4384009593 modified "2023-09-23" @default.
- W4384009593 title "UWB-IMU Pose Estimation for Roadheader Based on Machine Learning" @default.
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- W4384009593 doi "https://doi.org/10.1109/icmsp58539.2023.10170844" @default.
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