Kalman Filter Algorithm Realization Based on SOPC in Self-balancing Robot

摘要

Two wheeled self-balancing robot system for a single inertial sensor data collection is not accurate enough,and vulnerable to external noise interference.This paper introduces Kalman(Kalman) filtering algorithm based on SOPC to realize multi-inertia Sensor data fusion system design.Basic principles of Kalman filter,characteristics and applications are introduced.Using reconfigurable FPGA features,Nios soft core processor SOPC system hardware platform was built.The hardware platform used C language for more Attitude Sensor Kalman filter algorithm,which provided an effective tool for the two wheeled self-balance robot multi-sensor data fusion to obtain the data from the balance of the optimal estimation of robot pose and solve the inertial gyroscope and accelerometer sensor data compensation.Test results show that the FPGA hardware platform Kalman filter,are highly efficient,attitude data fusion accurate,reliable and able to meet the self-balancing robot control system estimates the optimal attitude angle data in real-time feedback and requirements,and the system is stable.