Currently, the most widely used robot on the market is the industrial robot, which is also one of the most mature and well-established. Industrial robots are widely used because they have a variety of control methods. According to different tasks, it can be divided into four control methods:point control method, continuous trajectory control method, force control method and intelligent control method.
1. point control method
This control method only controls the attitude of some discrete points in the workspace of the industrial robot. It is characterized by easy implementation and low positioning accuracy requirements, and is therefore often used for loading and unloading, handling, spot welding and inserting components on circuit boards. It requires only the precise position and attitude of the end-effector at the target point. This method is relatively simple, but it is difficult to achieve a positioning accuracy of 2~3um.
2. continuous trajectory control method
This control method requires strictly in accordance with the predetermined trajectory and speed in a certain range of precision movement, controllable speed, smooth trajectory, stable movement, in order to complete the task. The main technical indicators of the control method is the trajectory tracking accuracy and stability of the industrial robot end-effector attitude. Usually arc welding, painting, deburring and inspection operations robots use this control method.
3. force (torque) control mode
The principle of this control mode is basically the same as the position servo control, except that the input and feedback are not position signals, but force signals, so the system must use powerful sensors. Sometimes adaptive control is also realized by using sensing functions such as proximity and sliding.
4. Intelligent control methods
Intelligent control of robots is done by using sensors to gain knowledge about the surrounding environment and make decisions accordingly based on its internal knowledge base. With intelligent control technology, the robot has strong environmental adaptability and self-learning ability. The development of intelligent control technology depends on the rapid development of artificial intelligence in recent years, such as artificial neural networks, genetic algorithms, genetic algorithms and expert systems.