Abstract
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.
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