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Abstract

The present invention provides an indoor mobile robot glass detection and map updating method based on depth image inpainting. The method comprises: first screening, based on laser radar intensity data, a region in which glass is suspected to be present; determining, based on an RGB image of the suspected region and by using a convolutional neural network, whether glass is really present; if glass is really present, extracting a glass region boundary, determining a defect point of a depth image, and performing depth information supplementing on the defect point based on the glass region boundary; and finally, performing plane sampling on the depth image, inpainting and updating a missing glass obstacle in an original map, and outputting a grid map for planning. Therefore, a problem, that the existing mapping algorithms and devices are prone to glass perception failure due to the characteristics of glass transmission, refraction, polarization, etc., affecting the map integrity and navigation safety, is solved. The present invention has advantages of a low system perception cost and a safe and stable navigation function.

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First Claim