Indoor map construction algorithm based on RGBD semantic segmentation

Jie-Ying He
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Abstract

In the field of robotics and autonomous driving, vision or laser-based map construction has always been the main direction for solving mobile vehicle's perception and localization. The stereo camera is widely used in robot map construction because it can perceive both color information and depth information. Based on the RGBD semantic segmentation network, this paper proposes a map construction algorithm based on deep semantic segmentation. By using the pixel information of deep semantic segmentation, the missing part of the 3D point cloud is filled to construct an octomap. After experiments, on the datasets, the algorithm has achieved better results than only using the depth information, and after actual deployment, the algorithm has completed the construction of real-time indoor semantic maps on the robot.
基于RGBD语义分割的室内地图构建算法
在机器人和自动驾驶领域,基于视觉或激光的地图构建一直是解决移动车辆感知和定位问题的主要方向。立体摄像机由于既能感知颜色信息又能感知深度信息,在机器人地图构建中得到了广泛的应用。在RGBD语义分割网络的基础上,提出了一种基于深度语义分割的地图构建算法。利用深度语义分割的像素信息,填充三维点云缺失的部分,构建八元图。经过实验,该算法在数据集上取得了比仅利用深度信息更好的效果,经过实际部署,该算法在机器人上完成了实时室内语义地图的构建。
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