The robot manipulator is a device that controls the robot to complete a certain action or operation mission according to the instructions and sensing information, it is the heart of the robot, determines the quality of the robot function, and can be divided into two structural types: serial and parallel from the processing method of the robot control algorithm.
Serial processing structure
The so-called serial processing structure means that the control algorithm of the robot is processed by the serial machine, for this type of manipulator, from the accounting machine structure, control method to divide, and can be divided into the following types:
(1) single CPU structure, centralized control method with a strong function of the accounting machine to complete all the control functions, in the early stage of the robot, such as Hero-I, Robo t-I, etc., this structure is selected, but the control process needs a lot of accounting (such as coordinate change), so this control structure is slow.
(2) The second-level CPU structure and master-slave control method The first-level CPU is the host, which plays the functions of system management, robot language compilation and human-computer interface, and also uses its operation to complete the coordinate change and track interpolation, and punctually sends the calculation results to the common memory as the increment of joint movement for the second-level CPU to read; The second-level CPU completes the digital control of all joint orientations. There is no connection between the two CPU buses in this type of system, and only the data is exchanged through the shared memory, which is a loosely coupled connection. It is difficult to further spread out the power by selecting more CPUs. The accounting system of the Matoma n robot (5 joints, DC motor drive) produced in Japan in the 70s belongs to this master-slave structure.
(3) Multi-CPU structure and distributed control method
At present, this kind of two-level distributed structure of upper and lower computer is generally selected, and the upper computer is responsible for the management of the whole system, kinematic accounting, track planning, etc. The lower computer is composed of multiple C PU, each CPU controls a joint movement, and these CPUs and the main controller are closely coupled in the form of buses, and the operating speed and control function of the controller of this structure are significantly improved. However, the common feature of these multi-CPU systems is the functionally distributed structure selected for specific problems, that is, each processor has a fixed mission, and most of the world's commercial robot manipulators are now in this structure.
The azimuth control part of the manipulator accounting machine control system almost without exception chooses digital azimuth control.
The above types of manipulators all use serial machines to calculate robot control algorithms, and they have a common weakness: heavy accounting burden and poor real-time performance. Therefore, most of the methods such as offline planning and feedforward compensation decoupling are used to reduce the accounting burden in real-time control, and when the robot is disturbed during operation, its function will be affected, and it is more difficult to ensure the accuracy index required in high-speed movement.
Parallel processing structure
Parallel processing technology is an important and useful method to improve the accounting speed, which can meet the real-time requirements of robot control, from the literature, about the parallel processing technology of robot manipulator, people have studied more parallel algorithms of robot kinematics and dynamics and its end.1982 J. Y. S. Luh first proposed the problem of parallel processing of robot dynamics, which is because the dynamics equations of articulated robots are a set of nonlinear strongly coupled second-order differential equations, and the calculation is very complex. The calculation speed of the robot dynamics algorithm also lays the foundation for the completion of complex control algorithms, such as the accounting moment method, the nonlinear feedforward method, and the adaptive control method. One way to develop parallel algorithms is to modify serial algorithms to parallelize them and then map them to parallel structures. Generally, there are two methods, one is to consider the given parallel processor structure, and develop the parallelism of the algorithm according to the accounting model supported by the processor structure; The second is to first develop the parallelism of the algorithm, and then plan the parallel processor structure that supports the algorithm to achieve the best parallel efficiency.
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