Indirect Kalman Filter in Mobile Robot Application
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.
Copyright: © 2010 Surachai Panich. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Indirect Kalman filter
- differential encoder system
- sensor data fusion