Heading Measurements for Indoor Mobile Robots with Minimized Drift Using a MEMS Gyroscopes

Abstract

To achieve further minimized drift on yaw angle measurements for mobile robot, this chapter examines a simple, yet a very practical and effective filtering method that suppresses short-term broadband noise in low cost MEMS gyros. This filtering method is applied after the self-calibration procedure that is a novel algorithm developed for the longterm performance. The main idea of the proposed approach is consists of two phases; 1) threshold filter for steady or straight path maneuver, and 2) moving average filter for steady turning maneuver. However, it should be noted that no filter is applied to retain given edge sharpness for transient period. The switching criteria for the proposed filters are determined by the motion patterns of vehicle recognized via the signals from both gyro and encoder. Through this strategy, short-term errors at the gyro signal can be suppressed, and accurate yaw angles can be estimated regardless of motion status. The proposed method that combines both threshold filter for straight maneuver and moving average filter for steady turning maneuver was evaluated through experiments with Epson XV3500 gyro showing little drift at all time (estimated bias drift as 9 deg/hr), and 74% error reduction, compared with pure integration result. This method can be extended to increase the travel distance in-between absolute position updates, and thus results in lower installation and operating costs for the whole system.