Grabbing force self-adaptive adjusting manipulator grabbing method and system based on large language model

According to the grabbing force self-adaptive adjusting mechanical arm grabbing system and method based on the large language model, the semantic understanding capacity of the large language model, structural analysis of a machine vision algorithm model on the environment, the flexible control capacity of a mechanical gripper and the real-time pressure feedback detection mode of a flexible pressure sensor are combined; and dynamic intelligent grabbing of targets with different hardness degrees is realized. The method comprises the following steps: firstly, analyzing a target area image based on a machine vision target detection algorithm model, and identifying environment and target attributes; then, the environment and target attributes are understood through a large language model, and an operation command of the mechanical gripper is given; thirdly, the mechanical arm operating system compiles a high-level instruction given by the large language model into bottom-layer codes for controlling all components,