Research Article Open Access

Indirect Kalman Filter in Mobile Robot Application

Surachai Panich

Abstract

Problem statement: The most successful applications of Kalman filtering are to linearize about some nominal trajectory in state space that does not depend on the measurement data. The resulting filter is usually referred to as simply a linearized Kalman filter. Approach: This study introduced mainly indirect Kalman filter to estimate robot’s position. A developed differential encoder system integrated accelerometer is experimental tested in square shape. Results: Experimental results confirmed that indirect Kalman filter improves the accuracy and confidence of position estimation. Conclusion: In summary, we concluded that indirect Kalman filter has good potential to reduce error of measurement data.

Journal of Mathematics and Statistics
Volume 6 No. 3, 2010, 381-384

DOI: https://doi.org/10.3844/jmssp.2010.381.384

Submitted On: 18 April 2010 Published On: 30 September 2010

How to Cite: Panich, S. (2010). Indirect Kalman Filter in Mobile Robot Application. Journal of Mathematics and Statistics, 6(3), 381-384. https://doi.org/10.3844/jmssp.2010.381.384

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Keywords

  • Indirect Kalman filter
  • differential encoder system
  • sensor data fusion