Unmanned aerial vehicle three-dimensional environment modeling method based on vision-assisted laser radar

Abstract

The invention discloses an unmanned aerial vehicle three-dimensional environment modeling method based on a vision-assisted laser radar. The method comprises the following steps: calibrating a binocular camera based on a Zhang Zhengyou calibration method; then, adopting an external parameter calibration method on the camera / laser radar based on a 3D marker method; and finally, using the binocularvision odometer as high-frequency assistance of the laser radar odometer, providing off-site point rejection and a relative pose initial value for the laser radar odometer so that the laser radar odometer operates at a low frequency, and movement is further optimized by utilizing the relative pose initial value provided by the binocular vision odometer. According to the invention, high-precision modeling of the flight environment of the unmanned aerial vehicle is realized, a foundation is laid for autonomous obstacle avoidance of the unmanned aerial vehicle, safe flight of the unmanned aerialvehicle is ensured, a reliable channel is provided for acquisition of intelligence and resource information, and the combat effectiveness is improved.

Description

technical field [0001] The invention relates to the field of image processing and control of unmanned aerial vehicles, in particular to a three-dimensional environment modeling method for unmanned aerial vehicles based on visual aided laser radar. Background technique [0002] The multi-UAV formation cooperative combat mode can give full play to combat effectiveness and enhance combat effectiveness, and has gradually become a hot research topic today. It is said that the U.S. Defense Advanced Research Projects Agency has planned to launch highly intelligent drones that can be used in actual combat in 2025. Intelligent UAV formation requires UAVs to be able to identify and monitor obstacles that may be encountered on the flight path in real time, so as to formulate reasonable avoidance strategies, and finally complete established tasks, such as transporting materials, detecting terrain and striking targets Wait. Therefore, UAVs must have the ability to model the surrounding...

AI Technical Summary

Problems solved by technology

However, the binocular vision sensor also has shortcomings such as limited image accuracy, depth direction error gradually increases with distance, resulting in limited depth perception distance, and inability to work in scenes where feature points are missing.

The image feature point selection strategy of the laser sensor is relatively simple, and there may be many mismatching points, but its measurement accuracy is high, and the depth observation range is wide, and there is a strong complementarity with the visual sensor.

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