Paper
22 January 2010 Mobile robot GPS/DR integrated navigation positioning technique research
Yuanliang Zhang, Kil To Chong
Author Affiliations +
Proceedings Volume 7500, ICMIT 2009: Mechatronics and Information Technology; 75000T (2010) https://doi.org/10.1117/12.858570
Event: ICMIT 2009: Mechatronics and Information Technology, 2009, Gwangju, Korea, Republic of
Abstract
GPS is widely used for global positioning system. But GPS signal is easily interrupted when it is used alone. DR (dead reckoning) can calculate the position of mobile robots by using direction and speed sensors. However, DR system error can accumulate over time due to the error of electronic compass and odometer sensors. So DR system can't be used separately for a long time. The integrated navigation system combined GPS with DR will effectively integrated advantages of these two systems, higher positioning precision and reliability. In this paper Kalman filter model for GPS/DR integrated navigation system is set up to filter the GPS and DR data. And then the outputs of Kalman filter are inputted to a BP neural network for training. BP neural network is employed to predict next sampling time GPS output and a new Kalman filter based data fusion method is proposed to do the navigation information fusion with encoders and compass system. Simulation is done to validate the proposed fusion method. The simulation result shows the potential of this fusion method for outside used mobile robot navigation. Finally experiments are done to validate the proposed fusion method.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuanliang Zhang and Kil To Chong "Mobile robot GPS/DR integrated navigation positioning technique research", Proc. SPIE 7500, ICMIT 2009: Mechatronics and Information Technology, 75000T (22 January 2010); https://doi.org/10.1117/12.858570
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KEYWORDS
Global Positioning System

Navigation systems

Mobile robots

Neural networks

Data fusion

Filtering (signal processing)

Sensors

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