Fuzzy logic based 2D position estimation for small robotic fish using low cost MEMS accelerometer

This paper presents an effective calibration method and a fuzzy logic based smart signal-processing algorithm in order to accurately estimate a 2D position for small robotic fish with MEMS accelerometers. For position estimation, it is easy to be influenced by errors which come from MEMS accelerometer. The sources of error can be categorized into two groups, deterministic type and stochastic type. The former primarily includes bias, scale factor error and non-orthogonality; the latter contains signal drifting. Subsequently, the least squares algorithm is used to modify the deterministic error and the fuzzy filter can suppress the stochastic noise. Therefore, the proposed method integrated of least squares algorithm and fuzzy signal processing is utilized to enhance the accuracy and performance of MEMS accelerometer. The experimental results show the efficiency of this algorithm.