Dense 3D map building based on LRF data and color image fusion
Dense 3D map building based on LRF data and color image fusion
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DOI：
10.1109/iros.2005.1545235
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发表时间：
2005-12
期刊：
影响因子：
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通讯作者：
K. Ohno;S. Tadokoro
中科院分区：
文献类型：
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作者：
K. Ohno;S. Tadokoro
研究目标是搜救机器人的三维地图构建和定位。本文提出了一种新的稠密三维地图生成方法，并给出了实验结果。为了建立地图，有必要估计机器人运动。然而，在碎石上，很难估计机器人的运动里程计或陀螺仪。因此，在这个框架中，粗糙的3D地图和离散的机器人运动推导出使用SLAM基于3D扫描匹配。匹配方法采用ICP算法。然后，从粗糙的3D地图和纹理图像重建密集的3D地图。
Research objective of the authors is 3D map building and localization of search robot for rescue use. In this paper, the authors propose a novel method of dense 3D map building and present its trial result. For building a map, it is necessary to estimate robot motion. However, on rubble, it is difficult to estimate robot motion by using odometry or gyro. Therefore, in this framework, rough 3D map and discrete robot motions are derived using SLAM based on 3D scan matching. ICP algorithm is used for the matching method. Then, the dense 3D map is reconstructed from the rough 3D map and texture images.