Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : September 05, 2021 - September 08, 2021
Small and light-weight 9-axis sensor modules have been developed with the MEMS technology progresses. A sensor fusion that corrects drift errors in the gyro sensor output using the measurement information from the accelerometer and magnetometer has been proposed, and is used for posture estimation in daily activities such as walking and sports activities. However, during bicycle riding, the translational acceleration changes and impact from the road surface occurs. This paper presents an extended Kalman filter for pose estimation during bicycle riding using noise covariance matrices based on sensor output. Postural change appears in the gyroscope output because the rotational motion of the joints produces human movement. Therefore, the process noise covariance matrix was determined based on the gyroscope output. An observation noise covariance matrix was determined based on the accelerometer and magnetometer output because the acceleration and geomagnetic sensors’ outputs were used as observation values. The sensor fusion algorithm also uses information obtained from the nine-axis motion sensors to estimate the lower limb joint angles by correcting the centrifugal acceleration and tangential acceleration.
