Parallel robots, with their parallel structure of multiple actuators simultaneously driving end effectors, provide high rigidity, large load-bearing capacity, and precise positioning capability. This design not only gives robots significant advantages in dynamic response, but also enables them to shine in high-precision and high-speed application scenarios such as precision assembly and mechanical processing.

Figure 1 Application of Six Degree of Freedom Parallel Robot

Parallel robot configuration synthesis is a systematic design process that involves innovation, analysis, and optimization of robot structures to meet specific application requirements.

The following are the general steps for configuration synthesis of parallel robots:

1. Requirement analysis:

Clarify the application areas, working environments, and job tasks of the robot, and determine its performance indicators such as degrees of freedom, workspace, load capacity, accuracy, and speed.

2. Degree of freedom configuration:

Select the appropriate degree of freedom configuration based on the results of the requirement analysis. Common degrees of freedom include two degrees of freedom, three degrees of freedom, four degrees of freedom, five degrees of freedom, and six degrees of freedom. The configuration of degrees of freedom directly affects the motion ability and flexibility of robots.

3. Sports chain design:

Design a reasonable motion chain structure, including the layout and connection methods of series and parallel branches, to ensure that the motion chain can meet the motion needs of the robot and has good dynamic performance.

4. Joint and drive device selection:

Choose the appropriate joint type and driving device to provide sufficient driving force and accuracy. Joints are usually composed of motors, reducers, encoders, etc., used to control and drive the movement of the arm.

5. Material selection:

Choose high-strength and lightweight materials to reduce the weight of the robot, improve its movement speed and accuracy, while considering the material's corrosion resistance, wear resistance, and other properties.

6. Kinematic analysis:

Perform kinematic analysis on the preliminarily designed robot to verify whether it can achieve the expected motion form, analyze the forward and inverse kinematics of the robot, and address issues such as singular configurations.

7. Dynamics modeling:

Dynamically model the robot and analyze its dynamic performance under various working conditions, considering the influence of factors such as inertia, friction, and gravity on its motion performance.

8. Optimize design:

Based on the results of kinematic and dynamic analysis, optimize the design of the robot, including adjusting the layout of the motion chain, improving joint design, and optimizing material selection.

9. Simulation verification:

Use simulation software to validate the optimized robot and verify whether its motion performance, load capacity, accuracy, and other indicators meet the requirements under various working conditions.

10. Prototype production and testing:

Produce a prototype according to the design drawings and conduct actual testing on the prototype to verify its performance and reliability.

11. Iterative optimization:

Based on the test results, iteratively optimize the robot, continuously improve the design, and enhance the performance and reliability of the robot.

Figure 2 MATLAB simulation of Gough Stewart parallel robot

The main difficulty and challenge faced by the configuration synthesis parallel robot lies in the complexity of its mechanism design and the strong coupling between multiple variables. This requires designers not only to accurately grasp the kinematic characteristics of the robot, but also to deeply explore its dynamic behavior, ensuring breakthroughs in avoiding singular configurations, balancing accuracy and speed, and selecting high-performance materials. Meanwhile, with the continuous advancement of technology, how to integrate innovative elements into design to meet increasingly complex and changing application requirements is also a challenge that cannot be ignored in the process of configuration synthesis.

With the continuous advancement of technology, we foresee that parallel robots will play a more critical role in intelligent manufacturing. They will be the key to unlocking the potential of future manufacturing.

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