基于联邦滤波进行立体相机/IMU/里程计运动平台组合导航定位

Mobile Platform Localization by Integration of Stereo Cameras, IMU and Wheel Qdometer Based on Federated Filter

  • 摘要: 在无GPS信号的受限环境中,基于序列立体影像的运动平台视觉定位精度较高,能够改正航迹推算方法的误差累积,但在纹理贫乏或光照不足的环境下容易定位失败。为提高受限环境下运动平台定位的精度与稳健性,提出一种基于联邦滤波的立体相机、惯性测量单元(inertial measurement unit,IMU)及里程计组合导航方法。该方法在联邦滤波中利用IMU分别同里程计与立体相机构成子滤波器,有效避免立体视觉定位失效而导致的系统定位失败,提高了定位稳健性。地下巷道实验结果证明,所提方法能有效提高运动平台导航定位的精度,并且在立体视觉定位失效的情况下仍能实现连续定位。

     

    Abstract: In a GPS-denied environment, visual odometry based on sequential stereo images can be applied to correction of accumulated localization errors from dead-reckoning. Visual odometry however, preforms. poorly or even fails under poor texture or illumination conditions. To achieve high precision and robust localization, a federated filter based localization method is proposed that integrates stereo cameras, the IMU, and wheel odometer. The two sub filters in the federated filter, constructed by a IMU integrated with the wheel odometer and stereo cameras provide robust localization when visual odometry fails. Experimental results in an underground field demonstrate robust performance and improvement in localization accuracy.

     

/

返回文章
返回