Datasets Comparison

This research data includes three algorithms designed to enhance robot machining trajectory accuracy by utilizing local error information, along with data for the improvement of mirror surface machining trajectories. Algorithm 1​ calculates the local distance error influence vector for a given trajectory. This vector reflects the local characteristics of the trajectory. Algorithm 2​ filters the measured trajectory points based on the influence vector obtained from Algorithm 1, selecting the error measurement trajectory points that are most meaningful for locally improving the trajectory accuracy. Algorithm 3​ is an iterative compensation algorithm that corrects the trajectory based on the measured local errors. All algorithms were implemented in MATLAB R2024a.

Mechanical Machining, Compensation Method, Manufacturing Robotics

Creative Commons Attribution 4.0 International

This research data includes three algorithms designed to enhance robot machining trajectory accuracy by utilizing local error information, along with data for the improvement of mirror surface machining trajectories. Algorithm 1​ calculates the local distance error influence vector for a given trajectory. This vector reflects the local characteristics of the trajectory. Algorithm 2​ filters the measured trajectory points based on the influence vector obtained from Algorithm 1, selecting the error measurement trajectory points that are most meaningful for locally improving the trajectory accuracy. Algorithm 3​ is an iterative compensation algorithm that corrects the trajectory based on the measured local errors. All algorithms were implemented in MATLAB R2024a.

Mechanical Machining, Compensation Method, Manufacturing Robotics

Creative Commons Attribution 4.0 International