基于多传感器融合的移动机器人定位研究

针对室内未知环境下单一传感器定位累积误差大、受环境局限等缺点,设计一种多传感器非线性融合定位系统,以提高移动机器人自主导航的定位精度。该系统通过高斯牛顿方程对由激光雷达、惯性测量单元、轮式里程计测量得到的位姿信息进行融合优化,补偿由于在室内环境信息下单一传感器定位精度低所带来的定位误差。实验结果表明:应用多传感器融合定位系统的移动机器人在长6 m、宽3 m的室内面对曲折复杂的路径和各种噪声干扰时运行总路程12.8 m后,可以将定位误差稳定在0.106 3 m内,并将平均相对误差稳定在0.716%左右。与现有方法对比,使用该方法提高了室内移动机器人定位的精度和鲁棒性。

Research on Mobile Robot Localization Based on Multi sensor Fusion

Aiming at the shortcomings of single sensor positioning in indoor unknown environment, such as large cumulative error and limited by environment, a multi sensor nonlinear fusion positioning system was designed to improve the positioning accuracy of mobile robot autonomous navigation. In the system, Gauss-Newton equation was used to fuse and optimize the pose information measured by the lidar, inertial measurement unit and wheel odometer to compensate the positioning error caused by the low positioning accuracy of a single sensor under indoor environmental information. The experimental results show that the mobile robot using the multi sensor fusion positioning system can stabilize the positioning error within 0.106 3 m after running a total distance of 12.8 m when the indoor is 6 m long and 3 m wide while facing a tortuous and complex path and various noise disturbances. And the average relative error is stable about 0.716%. Compared with existing methods, using this method improves the accuracy and robustness of indoor mobile robot positioning.