Unmanned aerial vehicle control method based on gesture recognition and gesture recognition remote control unmanned aerial vehicle

Abstract

The invention discloses an unmanned aerial vehicle control method based on gesture recognition. The method comprises the following steps of (1) presetting a gesture recognition remote control unmannedaerial vehicle, (2) acquiring target gesture 3D point cloud data by using a first radar chip, (3) regenerating a target gesture image, (4) providing feature information of the target gesture image, (5) obtaining a target gesture action, and (6) comparing the target gesture action with the gesture sample so as to recognize a new gesture instruction, and (7) carrying out flight action control on the unmanned aerial vehicle body or carrying out shooting action control on the camera according to the new gesture instruction. The invention further discloses the gesture recognition remote control unmanned aerial vehicle for implementing the method. The unmanned aerial vehicle control method is relatively far in control range, relatively strong in obstacle avoidance function and suitable for long-distance flight control and shooting. According to the gesture recognition remote control unmanned aerial vehicle, the gesture action is recognized through the radar chip, and compared with existinggesture visual recognition, the gesture recognition distance, speed and precision are improved.

Description

technical field [0001] The invention relates to the technical field of drones, in particular to a gesture recognition-based drone control method and gesture recognition remote-controlled drones. Background technique [0002] At present, drones have become more commonplace. Most families have purchased drones for daily use. With the development of drone technology, some companies have developed technology to control drones through gesture recognition. , but they are all based on visual recognition, image acquisition, 3D sensing, ultrasonic, etc., but the effect is not very ideal. Dust, rain, fog, etc. may cause the camera to fail, and it is impossible to obtain effective pictures, and the relatively subtle gesture recognition effect is not good. Not good; at the same time, the range of gesture operation is not large. Due to the short board of the 3D sensing system, the sensing range is not large, and the obstacle avoidance function is relatively weak. It can only be used for Se...

AI Technical Summary

Problems solved by technology

[0002] At present, drones have become more commonplace. Most families have purchased drones for daily use. With the development of drone technology, some companies have developed technology to control drones through gesture recognition. , but they are all based on visual recognition, image acquisition, 3D sensing, ultrasonic, etc., but the effect is not very ideal. Dust, rain, fog, etc. may cause the camera to fail, and it is impossible to obtain effective pictures, and the relatively subtle gesture recognition effect is not good. Not good; at the same time, the range of gesture operation is not large. Due to the short board of the 3D sensing system, the sensing range is not large, and the obstacle avoidance function is relatively weak. It can only be used for Selfie, not suitable for long-distance flight; Therefore, for a gesture recognition drone that can realize long-distance aerial photography and high recognition accuracy, it is a major direction for the development of gesture recognition drones.

[0003] In the p

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