Robot TCP Calibration via Vision-Based Iterative Deviation Correction
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Solution Overview
Problem
Current methods for calibrating the Tool Center Point (TCP) of robot manipulators are time-consuming and lack precision, with automated systems being costly and laborious, making them impractical for widespread use.
Innovation Solution
A vision correction method that uses a multi-axis drive mechanism and vision lens to capture images from different orientations, establishing coordinate systems and calculating deviations to accurately adjust the TCP position, allowing for iterative corrections until maximum allowable precision is achieved.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual visual guidance method is used for TCP calibration, then operational flexibility is maintained, but calibration time is excessive and precision is not guaranteed
Solution Approach 1:
The patent replaces the manual visual guidance method with an automated vision-based measurement system. The vision lens captures images of the TCP at multiple orientations, and a controller automatically calculates the TCP position and deviation, eliminating the need for manual visual alignment while significantly reducing calibration time and improving precision.
Solution Approach 2:
The patent uses image capture to create a visual copy of the TCP position at different orientations. By capturing images and analyzing the TCP's position in these visual copies, the system can automatically determine the actual TCP position and calculate deviations without physical manual measurement, thereby reducing calibration time while maintaining high precision.
2Measurement precision
If automated calibration systems using light beams are used, then calibration precision is improved, but system cost and setup complexity increase significantly
Solution Approach 1:
The patent extracts only the essential function of automated measurement from complex light beam systems. Instead of using elaborate light beam apparatus, the invention uses a simple vision lens to capture images of the TCP at different orientations, achieving automated calibration precision while dramatically reducing system complexity and cost.
Solution Approach 2:
The patent replaces expensive, complex automated calibration systems with a simpler, more economical vision-based approach. The use of standard imaging components instead of specialized light beam equipment provides a cost-effective solution that achieves comparable precision without the high setup and operational costs of traditional automated systems.
3Measurement precision
If multiple orientation measurements are taken for accurate TCP calibration, then measurement precision is improved, but calibration process time increases
Solution Approach 1:
The patent implements continuous automated image capture at multiple orientations without manual intervention between steps. The robot manipulator automatically positions the tool at different orientations while the vision lens continuously captures images, allowing rapid sequential measurement that maintains precision while minimizing the time lost between measurements through automated transitions.
Solution Approach 2:
The patent pre-plans the measurement sequence and automatically executes it without manual setup. The controller预先 determines the required orientations and automatically positions the tool and captures images in the optimal sequence, eliminating the time-consuming manual setup and orientation adjustment required in traditional methods while maintaining the precision benefits of multi-orientation measurement.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method significantly reduces the time and cost associated with TCP calibration, providing high precision and convenience by iteratively refining the TCP position through image capture and mathematical calculations, enhancing the positional accuracy of robot manipulators.
Implementation Method 1
a vision lens is positioned to one side of the tool and configured for taking a plurality of different images of the tool
Data Source
AI summary
A vision correction method for establishing the position of a tool center point (TCP) for a robot manipulator includes the steps of: defining a preset position of the TCP; defining a preset coordinate system TG with the preset position of the TCP as its origin; capturing a two-dimensional picture of the preset coordinate system TG to establish a visual coordinate system TV; calculating a scaling ratio λ of the vision coordinate system TV relative to the preset coordinate system TG; rotating the TCP relative to axes of the preset coordinate system TG; capturing pictures of the TCP prior to and after rotation; calculating the deviation ΔP between the preset position and actual position of the TCP; correcting the preset position and corresponding coordinate system TG using ΔP, and repeating the rotation through correction steps until ΔP is less than or equal to a maximum allowable deviation of the robot manipulator.