GPS and Discrete Kalman Filter for Indoor Robot Navigation

Authors: Mbaitiga Zacharie

Abstract:

This paper discusses the implementation of the Kalman Filter along with the Global Positioning System (GPS) for indoor robot navigation. Two dimensional coordinates is used for the map building, and refers to the global coordinate which is attached to the reference landmark for position and direction information the robot gets. The Discrete Kalman Filter is used to estimate the robot position, project the estimated current state ahead in time through time update and adjust the projected estimated state by an actual measurement at that time via the measurement update. The navigation test has been performed and has been found to be robust.

Keywords: Global positioning System, kalman filter, robot navigation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1334914

References:

[1] M. Hentschel andB. Wagner. ÔÇ│ Autonomus Robot Navigation Based on AopenStreetMap GeodataÔÇ│. Proceedings of the e 13 th Intelligent IEEE Conference on Intelligent System, pp: 1645-1650, DOI: 10.1109/ITSC.2010.5625022, 2010.
[2] M. Hentschel, O. Wulf and B.Wagner. ÔÇ│ A GPS and Laser-based Localization for Urban and Non-Urban Outdoor EnvironmentsÔÇ│. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp: 149-154, Nive, France, 2008.
[3] P.Cao, M. Saxena, M. Tedder, S.Michalske and E.L.Hall. ÔÇ│An Application of GPS Systems on a Mobile RobotÔÇ│. http://www.min.uc.edu/robotics/papers/paper2001/Peter2001e.pdf.
[4] N. Kyriakoulis, A.Gasteratos and A.Amanatiadis. ÔÇ│Comparison of Data Techniques for robot NavigationÔÇ│. Proceedings of the 4th Hellenic International on Advanced in Artificial Intelligence, pp: 547-550, 2006.
[5] H. Niwa, K. Kogdaka, Y.Skamoto and S. Shigeki. ÔÇ│Indoor GPS Receiver for Mobile RobotÔÇ│. Proceedings of the KSAE Fall Conference, Branch of. Busan-Ulsan Gyeongnam, pp:.95-102, 2003.
[6] D.Kim, K.Hwang, D.Lee and T.kue. ÔÇ│A Simple Ultrasonic GPS System for Indoor Robot System using Kalman FilterÔÇ│.Proceesings of the International joint Conference SICE-ICASE, pp: 2915-2918,DOI: 10.1109/SICE.2006.314996
[7] Z. Mbaitiga. ÔÇ│Sensor Fusion Based Discrete Kalman Filter for outdoor Robot NavigationÔÇ│.International Conference on Control, Automation and robotics(ICCAR-11), Paris, France, August 24-26,2011.
[8] Z. Mbaitiga. ÔÇ│Adaptive Fuzzy Knowledge Based Controller for Autonomous Robot Motion ControlÔÇ│. Journal of Computer Science Vol.6, Issue10, pp: 1048-1055, 2010, Science Publications, New York, USA.