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Velocity estimation by using imperfect accelerometer and encoder for rigid contact modeling and control

Velocity estimation is crucial to certain robotic applications involving high bandwidth modeling and control. In the conventional approaches, the velocities generated from encoders or tachometers are quite noisy and low-pass filters are usually engaged to generate usable velocity signals. The low-pass filter, however, cause non negligible phase lag that may severely affect both modeling and control accuracy in the middle and high frequency range. In this paper, two approaches of using a fusion of an encoder and an imperfect accelerometer are proposed to estimate accurate velocities. The two approaches, namely the two-channel approach and the observer-based approach, estimate velocities by using proper frequency weightings over the encoder and accelerometer signals. The encoder mainly contributes to the low-frequency part of the velocity estimation and the accelerometer mainly contribute to the high-frequency part of the velocity estimation. An adaptive mechanism for estimating the accelerometer gain is also presented. The effectiveness of the two proposed velocity estimation approaches is verified experimentally with respect to a one degree-of-freedom robot in terms of both rigid contact modeling and control