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The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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Motion error analysis of a shield machine tool-changing robot based on a screw-vector method.

Wenxue Qian^1,2, Shuai Song³, Kexin Liu^4,5

¹School of Mechanical Engineering and Automation, Northeastern University, Shenyang, 110819, China. wxqian@mail.neu.edu.cn.

Scientific Reports

|November 28, 2022

Summary

This study introduces a new mathematical model to analyze industrial robot motion errors. The findings help improve robotic kinematic calibration and optimize spatial position accuracy.

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Area of Science:

Robotics
Mechanical Engineering
Applied Mathematics

Background:

Industrial robots are crucial for tasks like handling and welding, with repeat positioning accuracy being a key performance metric.
Absolute accuracy in industrial robots is directly determined by their motion error.
Existing robot design models often overlook dimensional and drive parameter errors, impacting overall precision.

Purpose of the Study:

To develop a mathematical model for analyzing kinematic errors in industrial robots.
To investigate the influence of dimensional and drive parameter errors on robot end-effector motion.
To propose a composite method for analyzing spatial deflection errors in robot joints with clearance.

Main Methods:

A kinematic exponential product model with error screws was proposed for robot design.
Screw theory and a vector method were combined to analyze spatial deflection errors in robot joints.
Mathematical models for axial movement, spatial deflection, and radial movement of joint gaps were established.
Numerical simulations were performed to analyze error distribution within the robot's workspace.

Main Results:

The study analyzed the impact of rod lengths and transmission errors on end-effector motion accuracy.
A composite analysis method based on screw theory and vector methods was developed for joint clearance errors.
Numerical simulations revealed the distribution laws of random errors and plane projection density in the robot's workspace.
The distribution of Euler angle errors was determined by solving the attitude matrix.

Conclusions:

The proposed mathematical models and composite analysis method are simple, correct, and effective.
The derived error distribution characteristics are significant for enhancing robotic kinematic calibration accuracy.
The findings provide valuable insights for optimizing the spatial position error distribution in industrial robots.