Attitude estimation of crane hook based on adaptive complementary filter with outlier rejection

This paper considers the problem of the crane hook attitude estimation under the complex industrial environment such as magnetic interference, windy condition and obstructed view. A wireless inertial measurement unit is developed using adaptive complementary filter. In the data preprocessing, an improved method is proposed to reject the outliers. After a detailed analysis of conventional complementary filter algorithm, fusing the data acquired from Micro-Electro-Mechanical Systems (MEMS) accelerometer and gyroscope based on the adaptive complementary filter algorithm is designed. This makes the designed unit achieve the real-time attitude measurement. The experimental result indicates that the application of MEMS inertial sensors using this algorithm can realize high precision without affecting the crane operation by the wireless transmission which has a potential application prospect.