Improvement of angular velocity and position estimation in gyro‐free inertial navigation based on vision aid equipment

Abstract

In conventional navigation systems, inertial sensors consist of accelerometers and gyroscopes. These sensors suffer from in‐built errors, accumulated drift and high‐level noise sensitivity. The accurate gyroscopes are expensive and not suitable in cost‐effective applications. To minimise such disadvantages, one solution is the combination of inertial sensors with different aiding sensors. To lower the cost, utilisation of redundant accelerometer structure as gyro‐free inertial measurement unit (GFIMU) has been proposed. In this study, Gyro‐Free navigation errors using four tri‐axial accelerometers are illustrated. Compensation of errors in terms of angular velocity and position estimation is verified based on adding a simple gyroscope, inexpensive stereo cameras as well as creating an easy to use topological map. The topological map is easily created by means of scale‐invariant feature transform method. The estimation of angular velocity is corrected on the basis of fusing the measurements from GFIMU and a simple gyroscope using unscented Kalman filter. The correction of position is performed by comparing the estimated position from GFIMU and observation of stereo cameras together with topological map. The results of the research show that the collaboration of GFIMU, stereo cameras and simple gyroscope will improve the robustness and accuracy of navigation, significantly.