One Approach to the Integration of Low-Cost Inertial Sensors and Global Positioning System for Mobile Robots

Abstract Mobile robots are reality these days. Advances in the new technologies, including relatively cheap sensors, new communication and internet technologies together with the increases in the computational speed provide significant advances in the mobile robots autonomy. Precise navigation parameters (position, velocity and attitude) play crucial role for mobile robots to respond autonomously. Supplying wrong or not precise navigation parameters to the Guidance and Control System can turn to be catastrophic for mobile robots. In navigation the trend is to use integrated systems. The idea is to integrate more navigation systems and to achieve better navigation accuracy. In this paper a low-cost integrated navigation system was developed where Extended Kalman Filter (EKF) was used for integration of the Global Positioning System (GPS) information and measurements from the single yaw gyro. Extensive practical experiments were carried out to validate the presented approach. The algorithm was tested on a mobile robot platform Itar Pejo and a car. The results show improvements of the integrated navigation system then the GPS and gyro used alone.

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