Abstract
The two-wheeled self-balancing robot has a simple structure, low cost and high flexibility, which is very suitable for indoor space. In this paper, we designed a self-balancing robot, by using the STM32 microprocessor as the main controller, and the attitude sensor MPU6050 is used to collect the obliquity and angular velocity. However, the gyroscope and the accelerometer make noise interference and drift error, the Kalman filter algorithm, therefore, is used to fuse the obliquity and angular velocity, in order to obtain the optimal obliquity. The PID control algorithm will combine the optimal obliquity and the real-time speed obtained by the high-precision encoder of the coaxial motor, to output the stable and reliable PWM signal, which can be sent to the motor drive chip. The motor drive chip can drive the operation of the two motors, to obtain the more ideal operation control effect. The results showed that the self-balancing robot could achieve stable self-balancing control.
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Peng, L., Zhou, C. (2018). Design and Implementation of Self-balancing Robot Based on STM32. In: Li, K., Li, W., Chen, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2017. Communications in Computer and Information Science, vol 874. Springer, Singapore. https://doi.org/10.1007/978-981-13-1651-7_33
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DOI: https://doi.org/10.1007/978-981-13-1651-7_33
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