An adaptive filtering method to improve measurement accuracy of walking robot attitude

The objective of this work is to improve the measurement accuracy of robot attitude with an adaptive filter method. Two main topics are highlighted in this work. The first topic is to build the Kalman filtering fusion equation of the acceleration and angular velocity (gyroscope) sensors. The second topic is to show that a Sage-husa adaptive Kalman filtering method is simplified and improved for the system, and an adaptive R is realized, then the exact attitude information is achieved. The experimental results are presented to show that the Sage-husa adaptive Kalman filtering method outperforms the traditional Kalman method in this paper in terms of noise reduction.

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