Multi-unmanned aerial vehicle cooperative navigation method and device based on inertia and binocular vision

Abstract

The invention relates to a multi-unmanned aerial vehicle cooperative navigation method and a device based on inertia and binocular vision. The method comprises the following steps: establishing a cooperative navigation system state model of multiple unmanned aerial vehicles based on an inertial navigation error model of each unmanned aerial vehicle, predicting a system state of the multiple unmanned aerial vehicles based on inertial navigation calculation and the cooperative navigation system state model, and updating the system state according to binocular vision relative position observation data of the unmanned aerial vehicles, obtaining the inertial navigation calculation error estimation of each unmanned aerial vehicle, and correcting the inertial navigation calculation result, so that multi-unmanned aerial vehicle collaborative navigation is realized. According to the method, the inertial navigation system error of each unmanned aerial vehicle is corrected based on binocular vision relative position observation, and the cooperative navigation precision higher than that of distance measurement or relative azimuth measurement is achieved by utilizing the characteristic that binocular vision position observation information simultaneously contains the distance and the relative azimuth between the unmanned aerial vehicles. In addition, inertial navigation error models are respectively established for the unmanned aerial vehicles, so that the method is suitable for the condition that inertial navigation systems of the multiple unmanned aerial vehicles are different in precision.

Description

technical field [0001] The present application relates to the technical field of platform cooperative navigation, in particular to a multi-UAV cooperative navigation method and device based on inertial and binocular vision. Background technique [0002] At present, drones generally use inertial / satellite integrated navigation technology. However, on the one hand, satellite navigation signals will be blocked in environments such as urban roadways and canyons, and on the other hand, they are easily interfered. Therefore, UAVs cannot rely solely on satellites as a means of navigation, but need to achieve autonomous navigation based on technologies such as inertial navigation in an environment where satellite navigation signals cannot be obtained, so as to adapt to various complex working environments. [0003] For UAV clusters, the cooperative navigation technology of relative observation between UAVs can be used to improve the inertial navigation positioning accuracy of UAVs....

AI Technical Summary

Problems solved by technology

At present, the cooperative navigation technology for UAV clusters has the following characteristics: First, most of them are limited to specific application scenarios such as cooperative air refueling and ground target tracking. The number of UAVs is mostly two, and most of the attention is on UAVs. The relative navigation information among them; second, UAV swarms are still not completely separated from the dependence on satellite navigation, and even realize cooperative navigation based on satellite navigation function, which is not suitable for the working environment without satellite signals; third, UAV The relative observation between them is measured by distance or relative azimuth. The common distance measurement sensor is an ultra-wideband ranging sensor, and the relative azimuth measurement sensor is a monocular camera, which can provide navigation data with low accuracy.

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