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Operation of the Collaborative Composite Manufacturing (CCM) System

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Published on: October 1, 2019

Improve the robot calibration accuracy using a dynamic online fuzzy error mapping system.

Ying Bai¹, Dali Wang

¹Department of Computer Science and Engineering, Johnson C. Smith University, Charlotte, NC 28216, USA. ybai@jcsu.edu

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|September 21, 2004

Summary

This summary is machine-generated.

This study introduces a novel fuzzy interpolation method to enhance robot calibration accuracy. This new approach significantly improves position error compensation compared to traditional bilinear interpolation methods.

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Area of Science:

Robotics
Control Systems
Artificial Intelligence

Background:

Traditional robot calibration relies on model and modeless methods.
Modeless methods compensate position error using bilinear interpolation based on workspace measurements.
Existing methods face limitations in achieving high compensation accuracy.

Purpose of the Study:

To introduce a novel fuzzy interpolation method for robot calibration.
To improve the accuracy of position error compensation in robot systems.
To develop a dynamic online fuzzy inference system for real-time applications.

Main Methods:

Implemented a novel fuzzy interpolation technique.
Utilized a dynamic online fuzzy inference system for real-time calibration.
Employed measurement devices (e.g., cameras) to determine position errors.

Main Results:

The fuzzy interpolation method demonstrated significantly improved compensation accuracy.
Simulated results validated the enhanced performance over bilinear interpolation.
The dynamic online fuzzy inference system proved effective for fast, real-time control.

Conclusions:

The proposed fuzzy interpolation method offers superior accuracy for robot calibration.
This approach is suitable for real-time control systems and calibration environments.
Fuzzy interpolation presents a promising advancement over traditional modeless calibration techniques.