Multi-mechanical-arm collaborative grinding force compliance control method and system

Abstract

The invention provides a multi-mechanical-arm collaborative grinding force compliance control method and a multi-mechanical-arm collaborative grinding force compliance control system. The control method comprises the steps of (1) giving a reference position, expected grabbing internal force and expected grinding force of a target object; 2) conducting position decomposition on a closed chain formed by cooperation of two grabbing mechanical arms, and establishing a closed chain dynamics position constraint equation; 3) acquiring acting force signals of the tail ends of the two grabbing mechanical arms on the target object through a force sensor, and conducting Kalman filtering processing on the acting force signals; and 4) establishing a dynamic adaptive impedance control equation, obtaining position compensation of the tail ends of the two grabbing mechanical arms according to the real internal force and the expected internal force, and obtaining position compensation of the tail end of a grinding mechanical arm according to the acting force signal of the tail end of the grinding mechanical arms on the target object and the expected grinding force. According to the method and the system, the clamping force at the tail end of the mechanical arm can be controlled within the range of an expected value while the cooperative operation of multiple mechanical arms is ensured, and theconstant grinding force control is realized.

Description

technical field [0001] The invention belongs to the field of multi-robot cooperative control, and in particular relates to a multi-robot cooperative grinding force compliance control method and a multi-robot cooperative grinding force compliance control system. Background technique [0002] In recent years, in order to promote the development of intelligent manufacturing, more and more companies have introduced robots into the grinding operation, which greatly improves the production efficiency compared with the original manual grinding, and the robot has good force control performance and high repeatability. Positioning accuracy, compared with a skilled worker, can ensure higher surface accuracy of the workpiece to be polished. [0003] The traditional robot grinding method is to use a mechanical arm to grind the workpiece fixed on the workbench. Due to the limited working space of the robot, generally only a single surface can be polished. The adjustment of the workpiece ...

AI Technical Summary

Problems solved by technology

When the grinding robot is performing grinding operations, due to the high-speed rotation of the electric spindle, it will bring a lot of random noise, making the force control algorithm of the robot unstable

In order to solve the random noise interference problem in grinding, it is necessary to filter the data collected by the force sensor, and the data obtained by the commonly used mean filter often has many small peaks, it is difficult to obtain a smooth curve, which affects the force tracking effect

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