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在动态环境中研究如何同步完成机器人定位、环境轮廓刻画、环境变化区域判别的任务,提出一种全局扫描匹配方法.该方法提出“试探-验证-求解(PVS)”的匹配策略,并提出利用高层几何统计特征描述激光扫描数据的分割段和扫描点.扫描数据准确匹配后,在刻画环境轮廓的同时也矫正了机器人位姿,而环境中的变化则在利用PVS策略匹配的过程中进行了辨别.最后通过多个未知动态室内环境下的真实激光数据集上的实验,验证了所提出方法的有效性.
In the dynamic environment, how to synchronously complete the task of robot localization, contouring of the environment and discrimination of the environment change region is proposed, and a global scanning matching method is proposed. This method proposes a matching strategy of "heuristic-verification-solution (PVS) The segmentation and scanning points of the laser scanning data are described by using the high-level geometric statistical features.After the exact matching of the scanning data, the posture of the robot is also corrected when the environmental contour is depicted, while the changes in the environment are utilized in the match of the PVS strategy Finally, the experimental results on real laser datasets in several unknown dynamic indoor environments show the effectiveness of the proposed method.