Paper:

# Measurement of a Vehicle Motion Using a New 6-DOF Motion Sensor System – Angular Velocity Estimation with Kalman Filter Using Motion Characteristic of a Vehicle –

## Ryoji Onodera^{*} and Nobuharu Mimura^{**}

^{*}Graduate School of Science and Technology, Niigata University, 8050 Ikarashi 2-nocho, Nishi-ku, Niigata-shi, Niigata 950-2181, Japan

^{**}Faculty of Engineering, Niigata University

This paper describes a new multi-degrees-of-freedom (DOF) motion sensor system in three-dimensional space. Our sensor system detects the acceleration of moving objects. In general, the moving objects each have 3 DOFs in the translational and rotational directions. Thus, the accurate measurement of all 6 DOFs of motion is essential to control these objects. We have developed a new acceleration sensor that measures 6-DOF motions by resolving multiple acceleration signals and are currently investigating its performance. In the case of multi-axial sensors, a specific problem of cross effect arises, which means the value obtained is different from the actual value, so sensor calibration becomes important. In this work, we achieved relatively stable measurement by inhibiting the cross effect through calibration. Though the only physical value that our sensor system can measure directly is 6-DOF acceleration, we investigated the angular velocity to compare with a conventional highly accurate gyro sensor. In calculations of angular velocity, we combined the motion characteristic with a Kalman filter and estimated angular velocities from detected accelerations. Our method generates a required observational signal in the Kalman filter artificially, using detected translational accelerations with gravity components and non-periodically refers to the observational signal. Finally, we investigated the proposed method in an experiment involving vehicle motion especially likely to have cross effect, and demonstrate that our sensor system (6-DOF accelerometer) performs well.

*J. Robot. Mechatron.*, Vol.20, No.1, pp. 116-124, 2008.

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