All-weather unmanned autonomous working platform in unknown environment

Abstract

The invention discloses an unmanned autonomous working platform based on an all-weather unknown environment, and belongs to the field of artificial intelligence and visual navigation. The platform comprises five modules: a stereoscopic vision positioning module, an infrared visible light fusion module, an image recognition module, a map construction module and a loop-back and return detection module. The visual positioning module and the image recognition module share a graph convolutional neural network framework, the visual positioning module selects key frames to perform feature matching and visual positioning, the image recognition module performs semantic classification on a point cloud local map, and the map construction module performs point cloud splicing to form a global depth dense semantic map. The deep neural network is introduced to improve the feature extraction effect and save the extraction time. Monocular vision distance measurement is adopted, so that the multi-parallax registration time is saved. Multi-spectral fusion of key frame images is carried out, all-weather efficient work is achieved, and the detection rate of shielded targets is increased.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence and visual navigation, in particular to an all-weather unknown environment unmanned autonomous working platform based on V-SLAM (stereo vision real-time positioning and mapping) and multi-spectral image fusion technology. Background technique [0002] For the complex and unknown environment where the geographical environment changes greatly in a short period of time, such as disaster areas and fire scenes after earthquakes, there is currently no efficient search and rescue and map construction equipment. [0003] In view of the above situation, the current map construction work is mainly carried out in coordination with helicopters and satellite positioning systems. Among them, the helicopter solution has poor maneuverability, high search costs, and requires ground base stations to plan paths in real time; while the satellite mapping method has a large amount of data and high calcu...

AI Technical Summary

Problems solved by technology

[0009] In order to solve the defects of poor precision, insufficient autonomy, and poor environmental adaptability in unknown environment detection and disaster area search and rescue tools in the above background technology, the present invention provides an all-weather unknown environment unmanned vehicle based on V-SLAM technology and multi-spectral image fusion technology. Autonomous working platforms, which can take the form of drones, unmanned rovers, or detection robots

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