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Study on indoor robot of self-localization based on RGB-D sensor

机译:基于RGB-D传感器的室内机器人自定位研究

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In order to solve the localization problem of the simultaneous localization and mapping (SLAM), a method of indoor robot's self-localization algorithm based on RGB-D sensor was proposed. Firstly, the feature points set were extracted from the environment pictures by SURF (Speed Up Robust Features) method and the corresponding matching points were found using nearest neighbor method. Secondly, the matching points' 3D data were reconstructed by using a combination of vision data and depth data. Thirdly, the robot's movement parameters which are consisted of rotation matrix and transport vector are estimated by SVD and optimized by ICP algorithm. Finally, experimental results indicated the validation of the proposed method.
机译:为了解决同时定位与定位(SLAM)的定位问题,提出了一种基于RGB-D传感器的室内机器人自定位算法。首先,通过SURF(提速鲁棒特征)方法从环境图片中提取特征点集,并使用最近邻法找到对应的匹配点。其次,结合视觉数据和深度数据重建匹配点的3D数据。第三,由旋转矩阵和传输矢量组成的机器人运动参数通过SVD估计,并通过ICP算法进行优化。最后,实验结果表明了该方法的有效性。

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