一种惯性传感器与编码器相结合的AGV航迹推算系统

Dead reckoning localization system for AGV using inertial sensors and wheel revolution encoding

针对在没有外部信号的室内环境下的自动导引车定位问题,对如何提高相对定位算法的准确性与稳定性等问题进行了研究,提出了一种将惯性导航与里程计相结合的算法,设计了卡尔曼滤波器来将磁强计、陀螺仪、加速度计的数据与轮上编码器的数据相融合,搭建了以Windows XP为操作系统,固高嵌入式运动控制器为主控的两轮驱动实验平台,并基于该实验平台设计了传感器误差补偿对比实验与位置估计对比实验。实验结果表明:所提出的算法对补偿加速度计与陀螺仪的传感器误差,提升位置估计的准确性与稳定性具有显著效果。

Aiming at the problem of automatic guided vehicle positioning without external signal in indoor environments,the accuracy and stability of the relative positioning algorithm were studied,and analgorithmto combines inertial navigation system and odometry was proposed.In order to achieve optimal solutions,a Kalman filter that base on the data of magnetometer,gyroscope,accelerometer and data of wheelencoder was designed. A two-wheel drive experimental platform with Windows XP and GT motion controller was set up. And based on the experimental platform,sensor error compensation comparison experiment and position estimation comparison experiment were designed. The results of the comparison experiment indicate that the algorithm has significant effect on compensating the sensor error and improving the accuracy and stability of the position estimation.