Accurate and Robust Attitude Estimation Using MEMS Gyroscopes and a Monocular Camera

Abstract

In order to estimate accurate rotations of mobile robots and vehicle, we propose a hybrid system which combines a low-cost monocular camera with gyro sensors. Gyro sensors have drift errors that accumulate over time. On the other hand, a camera cannot obtain the rotation continuously in the case where feature points cannot be extracted from images, although the accuracy is better than gyro sensors. To solve these problems we propose a method for combining these sensors based on Extended Kalman Filter. The errors of the gyro sensors are corrected by referring to the rotations obtained from the camera. In addition, by using the reliability judgment of camera rotations and devising the state value of the Extended Kalman Filter, even when the rotation is not continuously observable from the camera, the proposed method shows a good performance. Experimental results showed the effectiveness of the proposed method.