Self-calibration of gyro using monocular SLAM for an indoor mobile robot

Rate gyros are widely used to calculate the heading angle for mobile robot localization. They are normally calibrated in the factory using an expensive rate table prior to their use. In this paper, a self-calibration method using a monocular camera without a rate table is proposed. The suggested method saves time and cost for extra calibration procedure. SLAM (Simultaneous Localization And Mapping) based on visual features and odometry gives reference heading (yaw) angles. Using these, the coefficients of a scale factor function are estimated through Kalman filtering. A new undelayed feature initialization method is proposed to estimate the heading angle without any delay. Experimental results show the efficiency of the proposed method.