Vision-assisted miniature unmanned aerial vehicle indoor flight three-dimensional attitude algorithm

Abstract

The invention provides a vision-assisted miniature unmanned aerial vehicle indoor flight three-dimensional attitude algorithm. Pure autonomous calculation of a pitch angle, a roll angle and a course angle during indoor flight of an unmanned aerial vehicle can be realized. When the data of a magnetometer is valid, the three-dimensional attitude of the unmanned aerial vehicle is resolved by utilizing the data of an IMU and the magnetometer, and the resolving of a horizontal attitude angle and the resolving of a course angle are decoupled; when data of the magnetometer fails, only IMU data is used for achieving three-dimensional attitude calculation, the influence of the accelerometer on course angle calculation is cut off, and it is ensured that the precision requirement of course angle calculation within the endurance time is met without assistance of the magnetometer; and when the unmanned aerial vehicle flies in an indoor corridor, a forward-looking monocular camera module is used forachieving narrow channel detection, the angle of the unmanned aerial vehicle deviating from the corridor line is extracted, and the accumulated error of the course angle of the unmanned aerial vehicle is corrected through extended Kalman filtering according to the deviation angle.

Description

technical field [0001] The invention relates to the technical field of unmanned aerial vehicles, in particular to a three-dimensional attitude algorithm for indoor flight of a visually assisted micro unmanned aerial vehicle. Background technique [0002] Due to its small size, light weight and concealment, micro drones are very suitable for flying applications in indoor environments, such as indoor reconnaissance, search and rescue, and environmental detection. However, due to the limitations of its own size, weight and computing power, micro-UAVs cannot use navigation sensors with higher requirements for size, weight and power consumption, and visual navigation algorithms with a large amount of calculation to achieve indoor autonomous flight. At the same time, the indoor magnetic field environment is complex, and the application of the magnetometer in the room is greatly limited. The attitude calculation of the UAV will be disturbed, the accuracy will be reduced, and even t...

AI Technical Summary

Problems solved by technology

However, due to the limitations of its own size, weight and computing power, micro-UAVs cannot use navigation sensors with higher requirements for volume, weight and power consumption, and visual navigation algorithms with a large amount of calculation to achieve indoor autonomous flight.

At the same time, the indoor magnetic field environment is complex, and the application of the magnetometer in the room is greatly limited. The attitude calculation of the UAV will be disturbed, the accuracy will be reduced, and even the heading angle calculation will be wrong.

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