Abstract: A method for processing fused “underground+ground” data in deep formation exploration includes: collecting underground multi-source data by an underground intelligent probing rod, preprocessing the multi-source data to obtain an original digital signal, storing the original digital signal in an underground memory, obtaining continuous depth data by a ground device; performing high-bitrate and low-bitrate compression on the original digital signal, and modulating compressed signals; driving modulated signals by power, so the modulated signal is transmitted in a drilling stem with cable in a form of a power line carrier and then output, or first transmitted in a first section of the drilling stem with cable, re-collected in a short drill pipe with repeater, re-emitted to a second section of the drilling stem with cable, and then output; when a transmission line is disconnected, synchronizing and fusing data; and finally using fused data and the data output by the transmission line as final output data.

Abstract: A method for aligning a laser point cloud and an image based on deep learning includes: collecting data by using a laser ladar and a camera, to obtain laser point cloud data and a two-dimensional (2D) image respectively; dividing preprocessed point cloud data into triangular meshes to obtain a three-dimensional (3D) mesh model of the point cloud data; determining a relative location relationship between a laser radar and the multi-function camera, and constructing a virtual camera in the 3D mesh model to capture a simulated 2D image at a same location and angle as those of the camera; and aligning, by using a convolution neural network (CNN), the 2D image captured by the camera and the simulated 2D image captured by the virtual camera to generate aligned images that map onto each other.

Abstract: The present disclosure relates to a distribution station for serving an unmanned logistics distribution vehicle and distribution method.

Abstract: The present disclosure relates to a distribution station for serving an unmanned logistics distribution vehicle and distribution method.