A Novel Inertial-Visual Heading Determination System for Wheeled Mobile Robots

Finding an alternative way to replace the magnetic compass to determine the robot heading angle indoor is always a challenge in the robotics society. This brief proposes a structurally simple yet efficient nonmagnetic heading determination system, which can be used in the planar indoor environment with abundant ferromagnetic and electromagnetic interferences, by the combination of gyroscope and vision. The gyroscope is utilized to perceive the yaw rate, whereas a downward-looking camera is used to capture the prelaid auxiliary strips to acquire the absolute angle of the robot heading. Due to the existence of pseudomeasurement, varying noise statistical characteristics, and asynchronization between state propagation and measurement, the existing Kalman filters cannot be applied to fuse the gyroscopic and visual data. Therefore, a novel fusion algorithm named pseudomeasurement-resistant adaptive asynchronous Kalman filter is proposed, which is experimentally verified to be efficient in the environment with various interferences.