Target posture-based deep learning tracking acquisition method, learning system and storage medium

Abstract

The invention relates to the technical field of robots. The invention discloses a tracking and collecting method based on target posture deep learning. The learning system and the storage medium are used for controlling a robot to learn teaching actions, and the deep learning tracking and collecting method based on the target posture comprises the following steps that a plurality of reference points of the teaching actions are selected, the movement of each reference point is tracked, and teaching tracking data is recorded; Analyzing each teaching tracking data, and fitting into at least two functions through a movement and time relationship: an attitude function used for describing the change of the target attitude along with time and a displacement function used for describing the changeof the target position along with time; And generating a control program to enable the robot to realize the teaching action according to the attitude function and the displacement function. The driving program is generated by collecting the teaching action of the target, the requirement degree of manual participation is reduced, and the method has the advantages of being high in intelligent degree, high in imitation reduction degree and the like.

Description

technical field [0001] The present invention relates to the technical field of robots, and in particular to a tracking acquisition method, a learning system and a storage medium based on deep learning of target posture. Background technique [0002] A robot (Robot) is a high-tech product with a preset program or principled program inside. After receiving a signal or instruction, it can judge and take actions to a certain extent, such as moving, picking up, and swinging limbs. The task of the robot is mainly to assist or even replace the work of humans in some occasions. The actions and information judgments involved in the actual work scene are often very complicated, and it is difficult to record them all in the robot in the form of a program in advance. Knowledge, self-learning to improve adaptability and intelligence level, that is, robot learning, has become a very hot research focus in the robot industry. [0003] In the prior art, the process of the robot simulating t...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a deep learning tracking acquisition method based on target posture, a learning system and a storage medium, aiming to solve the problem of low degree of motion restoration, large amount of calculation for taking points, and manual labor when robots in the prior art simulate human teaching actions. The problem of more participation and less intelligence

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