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The SLAM algorithm of mobile robot with omnidirectional vision based on EKF

机译:基于EKF的全向移动机器人SLAM算法

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摘要

An improved simultaneous localization and mapping(SLAM) method based on extended Kalman filter(EKF) is presented to solve the SLAM problem of mobile robot with omnidirectional vision. The environment feature is extracted from the environment information around the mobile robot got by onmidirectional vision, then the landmark is located, finally, the position and attitude of the mobile robot and the map library are updated synchronously by using the EKF algorithm. Simulation results and real robot experiment results indicate the effectiveness and accuracy of the proposed approach.
机译:提出了一种基于扩展卡尔曼滤波(EKF)的改进的同时定位与映射(SLAM)方法,以解决全向视觉移动机器人的SLAM问题。从通过单向视觉获得的移动机器人周围的环境信息中提取环境特征,然后定位地标,最后使用EKF算法同步更新移动机器人的位置和姿态以及地图库。仿真结果和实际机器人实验结果表明了该方法的有效性和准确性。

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