Abstract
A major risk in developing control loops for autonomous mobile robots is to rely on a single piece of measuring equipment. This paper describes the construction and application of a multi-sensor platform on which sensor-fusion algorithms can be implemented and analyzed. The proposed application puts together signals from rotary encoders and inertial sensors. Wheel encoders are prone to errors due to slipping and skidding and inertial information gathered from an electronic gyroscope and an accelerometer sensor rapidly accumulates error due to numerical integration. Preliminary results show that the performance of robot localization increases by merging the above-mentioned sensors through a complementary filter. Moreover, this paper aims to provide a support work-frame for future analysis on mapping and path finding algorithms for autonomous mobile systems.
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Negirla, PO., Nagy, M. (2021). Mobile Robot Platform for Studying Sensor Fusion Localization Algorithms. In: Balas, V., Jain, L., Balas, M., Shahbazova, S. (eds) Soft Computing Applications. SOFA 2018. Advances in Intelligent Systems and Computing, vol 1221. Springer, Cham. https://doi.org/10.1007/978-3-030-51992-6_25
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DOI: https://doi.org/10.1007/978-3-030-51992-6_25
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