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INTEGRATING DEPTH AND IMAGE SEQUENCES FOR PLANETARY ROVER MAPPING USING RGB-D SENSOR

机译:使用RGB-D传感器集成深度和图像序列以用于行星漫游

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RGB-D camera allows the capture of depth and color information at high data rates, and this makes it possible and beneficial integrate depth and image sequences for planetary rover mapping. The proposed mapping method consists of three steps. First, the strict projection relationship among 3D space, depth data and visual texture data is established based on the imaging principle of RGB-D camera, then, an extended bundle adjustment (BA) based SLAM method with integrated 2D and 3D measurements is applied to the image network for high-precision pose estimation. Next, as the interior and exterior elements of RGB images sequence are available, dense matching is completed with the CMPMVS tool. Finally, according to the registration parameters after ICP, the 3D scene from RGB images can be registered to the 3D scene from depth images well, and the fused point cloud can be obtained. Experiment was performed in an outdoor field to simulate the lunar surface. The experimental results demonstrated the feasibility of the proposed method.
机译:RGB-D摄像机允许以高数据速率捕获深度和颜色信息,这使得可能和有益地整合深度和图像序列以用于行星流动站映射。所提出的映射方法包括三个步骤。首先,根据RGB-D相机的成像原理建立3D空间,深度数据和视觉纹理数据之间的严格投影关系,然后将基于扩展束调整(BA)的SLAM方法与2D和3D测量集成在一起用于高精度姿态估计的图像网络。接下来,由于可以使用RGB图像序列的内部和外部元素,因此可以使用CMPMVS工具完成密集匹配。最后,根据ICP之后的配准参数,可以将RGB图像中的3D场景很好地配准到深度图像中的3D场景,并获得融合点云。在室外野外进行了模拟月球表面的实验。实验结果证明了该方法的可行性。

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