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3D Localization of a Mobile Robot by Using Monte Carlo Algorithm and 2D Features of 3D Point Cloud

机译:使用Monte Carlo算法和3D点云的2D特征3D移动机器人的定位

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Modern buildings are designed with wheelchair accessibility, giving an opportunity for wheeled robots to navigate through sloped areas while avoiding staircases. Nonetheless, working safely and autonomously in uneven or unstructured environments is still challenging for mobile robots. Herein, we propose the use of a point cloud treatment and Monte Carlo localization in an algorithm for 3D localization of a mobile robot in uneven and unstructured environments. The point cloud treatment consists of projecting the acquired 3D point cloud and generated 2D features. These features are used to recreate an occupancy map. To perform localization in real-time, the robot systems use the occupancy map and 2D features as input in conjunction with the Monte Carlo algorithm.
机译:现代建筑设计有轮椅可行性,为轮式机器人提供了机会,以避免楼梯的倾斜区域。 尽管如此,在不均匀或非结构化环境中安全,自主地工作仍然挑战移动机器人。 在此,我们提出了在不均匀和非结构化环境中的移动机器人的3D定位算法中使用点云处理和蒙特卡罗定位。 点云处理包括投影所收购的3D点云并生成的2D特征。 这些功能用于重新创建占用映射。 为了实时执行本地化,机器人系统使用占用映射和2D特征与蒙特卡罗算法一起使用。

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