自平衡机器人中数据融合算法的研究与实现

摘要

轮式自平衡机器人是一种通用的机器人，它适用于各种复杂环境中，通过陀螺仪和加速度计采集的数据可以控制其平衡性，但是不够精确和实时。为了进一步提高系统的响应，文中通过离散卡尔曼算法将ENC03陀螺仪和MMA7260加速度计采集的数据进行融合输出。首先研究了传统的卡尔曼算法，然后建立了适合自平衡机器人的算法模型，最后介绍了其工程实现。通过实时监测可以看出，在未进行角度融合之前，加速度计计算得出的角度在静态和动态都有着极大的噪声。经过卡尔曼滤波算法融合后的角度平滑稳定，达到了预期效果。%Self-balancing robot is general and uses the data collected by gyroscope and accelerometer to control its balance,which can be applied to various complex environments. In order to improve the response of the system because of its limited accuracy and punctuality, the discrete Kalman algorithm is utilized for fusion of the data acquired from the gyroscope ( ENC-03 ) and accelerometer ( MMA-7260). Research of the traditional Kalman algorithm is carried on,then establishment of its model for self balancing robot,finally intro-duction of its engineering implementation. According to the real-time monitoring,it can be seen that the angle calculated from the acceler-ometer without angle infusion has great noise both in its dynamic and static aspects. The angle acquired from Kalman filtering algorithm fusion is smooth and stable,achieving the desired effect.