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中文摘要：
同时的本地化的一条扩大 Kalman 过滤器途径并且印射(撞击) 基于本地地图被建议。一个本地原则在我们拒绝了进全球原则的机器人和里程碑的机器人，然后观察的位置周期性地被建立。因为本地地图的独立，途径不堆积估计，被生产由的计算错误直接猛击 usingKalman 过滤器。同时，它减少计算复杂性。这个方法被证明在模拟实验正确、可行。
英文摘要：
An extended Kalman filter approach of simultaneous localization and mapping（SLAM） was proposed based on local maps A local frame of reference was established periodically at the position of the robot, and then the observations of the robot and landmarks were fused into the global frame of reference. Because of the independence of the local map, the approach does not cumulate the estimate and calculation errors which are produced by SLAM using Kalman filter directly. At the same time, it reduces the computational complexity. This method is proven correct and feasible in simulation experiments.
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