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RGB-D sensor based mobile robot SLAM in indoor environment

机译:室内环境中基于RGB-D传感器的移动机器人SLAM

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A simultaneous localization and mapping (SLAM) approach based on RGB-D sensor in indoor environment is presented in this paper. The S-NARF feature of point cloud was extracted, and then used for point cloud registration. In particular, a semi-random search strategy is proposed for the loop closures detection. The poses estimation was optimized under the g2o framework. The experiments demonstrate that the approach can effectively solve SLAM problem in indoor environment and the poses estimation have met the demand for precision.
机译:提出了一种基于RGB-D传感器的室内定位同时定位(SLAM)方法。提取点云的S-NARF特征,然后将其用于点云注册。特别地,提出了一种半随机搜索策略来检测闭环。姿势估计在g2o框架下进行了优化。实验表明,该方法可以有效解决室内环境中的SLAM问题,姿态估计满足了精度要求。

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