A localization system of mobile robots using artificial landmarks

This paper proposes a localization system for indoor mobile robots. The localization system includes a camera and artificial landmarks for global positioning, and encoders and gyro sensors for local positioning. The Kalman filter is applied to take into account the stochastic errors of all sensors. Also, we develop a dead reckoning system to estimate the global position when the robot moves into blind spots, where it cannot see artificial landmarks. Learning engines using modular networks are designed to improve the performance of the dead reckoning system. The experimental results are then presented to verify the usefulness of the proposed localization system.