<![CDATA[Research on wheeled robot navigation control has been developed by using human commands directly, one of which is by using hand gestures. The aim is to overcome problems related to the navigation control system. The implementation of an inertial measurement unit (IMU) sensor was developed on the hand gesture control device to detect all forms of movement produced. However, the measurement results by sensors are often inaccurate. The Kalman Filter algorithm is the ideal approach to optimize the estimation of the inaccuracy of signals produced by sensors. Manually tuning the covariance filter is done by changing the matrix covariance noise process with the try and error method based on the predetermined test scenario. The Kalman Filter signal test results show the determination of the variable Q_angle = 0.001, Q_bias = 0.003 and the value of R_measure = 0.03 is optimal in estimating measurements to minimize the effects of noise.]]>
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