Mr. Mengmeng Li Profile

Mengmeng Li

at Univ of Science and Technology of China

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Proceedings Article | 19 October 2023 Paper

Research on a data fusion scheme for a depth camera and LIDAR of mobile robot based on depth completion

Mengmeng Li, Daoding Hong, Yingfu Wang, Xin Cheng, Wei Zhao, Zengxiang Zhou

Proceedings Volume 12709, 127095U (2023) https://doi.org/10.1117/12.2684536

KEYWORDS: Calibration, Point clouds, LIDAR, Cameras, Sensors, Computer graphics, Data fusion, Depth maps

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In the process of robot target recognition, depth cameras and LIDAR are often used as extended sensors. The data collected by both have their own advantages and disadvantages, LIDAR can obtain accurate position information but not the morphology information of the object, while depth cameras can obtain abundant image information but cannot obtain accurate three-dimensional position information of objects. To better achieve the robot's recognition of specific targets, we fused the two information sources and obtained point cloud data with RGB information. To solve the problem of inconsistency in the coordinate system of the sensor system, we identify a specific calibration plate and propose an ellipse identification method for fault point clouds. To solve the problem of LIDAR point clouds sparsity, we compare the improved completion algorithm based on computer graphics and the completion algorithm based on deep learning, we figure out that the method of computer graphics meets our expectations better based on the fact that it have a larger number of point clouds. Finally, The accuracy of the method based on computer graphics is measured, and the errors of length and width are only 0.003% and 3.64%, which proves that the proposed method can meet the fusion accuracy in small indoor environment.

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