用卡尔曼滤波提升差速机器人定位与轨迹估计精度
Kalman Filter Applied To A Differential Robot
- 结合编码器数据与卡尔曼滤波进行状态估计
- 实测显示滤波后轨迹误差显著降低
- 适合做移动机器人定位的初学者参考
本文研究自主移动差速机器人的定位与轨迹跟踪问题，重点将卡尔曼滤波应用于其位置与轨迹估计。实验通过差速机器人内置的两个增量式编码器获取数据，控制与数据处理在连接电脑的Matlab/Simulink环境中完成。结果以图表形式展示，对比了采用PI控制和卡尔曼滤波估计器时机器人实际路径的表现，验证了滤波方法在真实系统中对轨迹估计的有效性。
原文摘要 · Abstract (English)
This document presents the study of the problem of location and trajectory that a robot must follow. It focuses on applying the Kalman filter to achieve location and trajectory estimation in an autonomous mobile differential robot. The experimental data was carried out through tests obtained with the help of two incremental encoders that are part of the construction of the differential robot. The data transmission is carried out from a PC where the control is carried out with the Matlab/Simulink software. The results are expressed in graphs showing the path followed by the robot using PI control, the estimator of the Kalman filter in a real system.
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