An intelligent grasping system and method based on the brain-cerebellum model

Abstract

The invention discloses an intelligent grasping system based on a brain-cerebellum model, comprising: a brain module, a cerebellum module, a binocular camera module, a movement component and a drive module; the cerebellum module is used to control the movement component through the drive module To perform an action, the binocular camera module is used to collect the image of the piece to be grabbed; the moving component is provided with a grabbing piece, and the grabbing piece is connected to the end of the moving component through a flange; the brain module is respectively It is electrically connected with the cerebellum module, the binocular camera module, and the gripper, and the drive module is electrically connected with the cerebellum module and the moving components respectively; the brain module of the present invention is responsible for complex and delicate work such as three-dimensional model training and trajectory planning, and The cerebellum module is responsible for the execution of the robot's actions. The function is simple to operate, and it can effectively realize the automatic identification of the object to be grasped, and complete the trajectory planning according to the grasping starting point and placement point to realize intelligent obstacle avoidance.

Description

An intelligent grasping system and method based on cerebral-cerebellum model technical field The present invention relates to the technical field of intelligent grasping, more specifically to a kind of intelligence based on cerebral-cerebellum pattern Grab system and method. Background technique With the rapid development of industrial robot technology and the improvement of labor costs, industrial robots have gradually increased in recent years. It has been widely used in industrial production, assembly and logistics, greatly liberating productivity, improving production efficiency and productivity. Product quality consistency, while reducing labor costs. Although industrial robots have greatly improved production efficiency, manual participation is still required in some processes. Some process links that require manual participation have become the main reason for slowing down the production rhythm. For example, the sorting process on the production line, the t...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is: unable to identify the three-dimensional posture and coordinate position of the object to be grasped, unable to identify obstacles in the grasping process and autonomously plan the grasping route

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