The accuracy of parallel robots is one of their most important characteristics, especially in high-precision fields such as aerospace, automotive manufacturing, and medical surgery. The way to achieve high precision involves mechanical design, optimization of control systems, precise manufacturing, and rigorous calibration processes.

The following are several key aspects for achieving high precision in parallel robots:

1. Mechanical design

Rigid design: Parallel robots typically have high structural rigidity because all actuators directly support the load platform. This design reduces the offset and deformation during loading and movement, improving accuracy.

Low quality moving parts: The moving parts of parallel mechanisms are usually lighter than those of serial robots, which reduces errors caused by inertial forces.

Optimized kinematic design: By carefully designing the configuration of joints and linkages, the workspace and motion characteristics of the robot can be optimized, reducing singular points and interference during motion, thereby improving accuracy.

2. Precision manufacturing and assembly

High quality components: Using high-precision parts and components such as precision bearings, actuators, and sensors can significantly improve the overall system performance.

Precise assembly: Ensure strict alignment of all components during the assembly process to reduce mechanical errors.

3. Control system optimization

Advanced control strategies: Adopting advanced control algorithms such as model predictive control, adaptive control, and robust control can effectively address the nonlinearity and model uncertainty of the system.

Real time feedback system: Using high-resolution sensors for real-time position and velocity feedback, the input of the actuator can be adjusted in a timely manner to correct trajectory deviations and external disturbances.

Closed loop control: Parallel robots typically use closed-loop control systems to ensure precise position and posture of end effectors through continuous monitoring and adjustment.

In addition, the calibration process also plays an important role in the accuracy implementation of parallel robots, by adjusting the geometric and dynamic models of the robots through the calibration process to compensate for manufacturing and assembly errors. Through precise calibration, it can be ensured that the robot's movements are more in line with expectations, which is particularly important for high-precision applications.

Generally, kinematic calibration is performed on robots, which involves measuring and adjusting the physical dimensions and positional parameters of the robot, including joint positions, link lengths, and other structural characteristics. These parameters directly affect the kinematic model of the robot and the precise positioning of its end effectors. Kinematic calibration typically uses specialized measuring equipment such as laser trackers, optical tracking systems, or contact measuring instruments to accurately measure and calibrate the differences between the actual dimensions of robot components and theoretical models.

Laser trackers can provide very high measurement accuracy and are commonly used to measure the position of robot joints and end effectors. During the calibration process, the laser tracker is fixed at a point, and the spatial position of each component of the robot is determined by emitting a laser beam and measuring the reflected beam. This method is particularly suitable for the calibration of large robot systems. The model-based calibration method uses a preset mathematical model and a series of known test position data to calibrate the robot. By comparing the difference between the actual position of the robot and the predicted position of the model, adjust the parameters in the mathematical model (such as link length, joint angle, etc.) until the minimum error is reached. This method is often combined with optimization algorithms to automate the calibration process.

Dynamics calibration focuses on the performance of robots in dynamic operations, mainly their response to velocity and acceleration. This includes adjusting its control parameters to ensure that its dynamic model (such as mass, friction, and torque) accurately reflects the performance during actual operation. Dynamic calibration usually involves a series of test runs, through which data are collected, and then control algorithms are adjusted to optimize performance.

Through the calibration process, system errors of robots in specific positions and postures can be identified, which may originate from mechanical errors, temperature changes, or other environmental factors. Once these errors are mapped and quantified, error compensation strategies can be implemented in the robot control system to reduce or eliminate the impact of these biases. Calibration is not just a single step, but a continuous process involving software and hardware integration. Through calibration, the physical and mathematical models of the robot can be better integrated, improving the overall reliability and performance of the system.