Sensor fusion algorithms for encoder resolution enhancement in educational mobile robots

High-quality motion control calls for precise position and velocity signals. However, velocity estimation based on simple numerical differentiation from only the position measurement may be very erroneous, especially when the sampling frequency is high or the velocity is very low. The problem would...

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Bibliographic Details
Published in2016 International Conference on Advanced Robotics and Intelligent Systems (ARIS) pp. 1 - 5
Main Authors Juing-Huei Su, Chyi-Shyong Lee, Chao-Wei Chen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2016
Subjects
accelerometer
Accelerometers
encoder
Kalman filters
Mobile robots
Observers
Robot sensing systems
Sensor fusion
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Summary:High-quality motion control calls for precise position and velocity signals. However, velocity estimation based on simple numerical differentiation from only the position measurement may be very erroneous, especially when the sampling frequency is high or the velocity is very low. The problem would become more severe for educational mobile robots in which most low cost encoders have very low resolutions. Thanks to the fast development of MEMS (Micro Electro Mechanical Systems) devices, it is easy to install gyros and accelerometers on educational mobile robots. Therefore, this paper devises two sensor fusion algorithms that are based on the observer and Kalman filter theories to remedy this problem. Students can not only control the educational mobile robots in a more precise way, but also expose themselves to more advanced control algorithms. These two algorithms are experimentally validated and compared on an educational mobile robot which is developed for Robotrace and Micromouse contests.
DOI:10.1109/ARIS.2016.7886612