Abstract
For a mobile robot movement, the position measurement using internal reference sensors are of low accuracy. Encoder measurements are affected by skid, accelerometer results are affected by noise and final calculation by additive errors. In this paper is presented a method for acquiring and processing data in order to be used for the correction to be performed in order to determine the position of a mobile robot with increased accuracy. The used sensors in the proposed system are accelerometer and encoders, while the perturbation filtering is made with Kalman method. The data obtained from sensors are processed and analyzed, in order to reduce the measurement error.
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Florin, S., Sorin, N., Romeo, N., Anca, P., Sergiu, F. (2018). Data Acquisition and Processing with Fusion Sensors, Used in Algorithms for Increasing Accuracy of Position Measurement of Mobile Robots. In: Balas, V., Jain, L., Balas, M. (eds) Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-319-62524-9_42
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DOI: https://doi.org/10.1007/978-3-319-62524-9_42
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