The robot manipulator is a device that controls the robot to complete a certain action or operation task according to the instructions and sensing information, it is the heart of the robot, which determines the performance of the robot, and can be divided into two structural types: serial and parallel from the processing method of the robot control algorithm.
1. 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 accounting machine to complete all the control functions, in the early robots, such as Hero-I, Robo t-I, etc., this structure is selected, but the control process requires 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 serves as the system management, robot language compilation and human-machine interface functions, and also uses its computing power to complete coordinate change and orbit interpolation, and regularly sends the calculation results to the common memory as the increment of joint movement for the second-level CPU to read; The secondary CPU completes the digital control of all joint orientations. In this type of system, there is no communication between the two CPU buses, and only data is exchanged through the common memory, which is a loosely coupled contact. It is difficult to use more CPUs to further dissipate the functionality. The accounting system of the Matoma n robot (5 joints, DC motor driven) produced in Japan in the 70s belongs to this master-slave structure.
(3) Multi-CPU structure and distributed control method
At present, the two-level distributed structure of the upper and lower computer is widely 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 CPUs, each CPU controls a joint movement, and these CPUs and the main controller are tightly coupled through the bus, and the operating speed and control performance of the controller of this structure have been significantly improved. However, the common feature of these multi-CPU systems is the functionally distributed architecture chosen for specific problems, that is, each processor undertakes a fixed task, which is the structure of most commercial robot manipulators in the world today.
The azimuth control part of the control system of the controller computer is simply the digital azimuth control without exception.
The above types of manipulators all use serial machines to calculate robot control algorithms, and they have a common weakness: accounting load 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 its performance will be affected when the robot is disturbed during operation, and it is more difficult to ensure the accuracy indicators required in high-speed movement.
2. Parallel processing structure
Parallel processing skills are an important and useful means to improve the speed of accounting, which can meet the real-time requirements of robot control, from the literature, about the parallel processing skills of robot manipulators, people have studied more parallel algorithms of robot kinematics and dynamics and their completion, in 1982 J. Y. S. Luh first proposed the problem of parallel processing of robot dynamics, because the dynamics equations of articulated robots are a set of nonlinear strongly coupled second-order differential equations, and the accounting is very messy. The calculation speed of the robot dynamics algorithm also lays the foundation for the completion of messy control algorithms, such as the accounting moment method, the nonlinear feedforward method, and the adaptive control method.
One of the ways to develop parallel algorithms is to transform the serial algorithm to make it parallel, and then map the algorithm to the parallel structure, there are generally 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 power.
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