基于点线视觉/惯性 SLAM 和目标检测的测距方法

Aiming at the problem that the unmanned platform is self-positioning in an unknown environment and the accuracy of long-distance target ranging is not high, a vision/inertial navigation and positioning system is composed of a monocular camera and an inertial device, and the "dynamic baseline + triangulation ranging" method is proposed in combination with target detection to realize self-positioning and target ranging. Firstly, a vision/inertial system model based on point-line fusion is established to improve the positioning accuracy of the system itself and give the relative pose changes before and after movement. Secondly, the target detection algorithm is used to detect and identify the target, and the parallax of the object to the image plane before and after motion is obtained. Finally, high-precision ranging of the target is realized by triangulation. The experimental test results of the common dataset show that the average localization root mean square error (RMSE) of the vision/inertial system with line features is 0.15 m. The unmanned platform mounted system to conduct ranging experiments on the target shows that the error of the system in measuring the target within 100 meters is less than 2% of the ranging distance.