Robotic Arm Calibration Using 3D Vision Pose Alignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional calibration methods for robotic arm systems are time-consuming and sensitive to operator experience, making it difficult to achieve high accuracy in aligning the visual device's coordinate system with the robotic arm's coordinate system, which affects the precision of work piece positioning.
Innovation Solution
A calibration method and device that utilize a visual device to capture images of a calibration object on the robotic arm, obtaining three-dimensional feature data to compute the relative relationships between the visual device, the robotic arm's pedestal, and the calibration object, thereby calibrating position errors without requiring multiple images or operator-dependent processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images of the calibration plate are acquired with various poses following specific manner, then the accuracy of relative poses between coordinate systems is improved, but the calibration time is increased and the process becomes more complex
Solution Approach 1:
The calibration plate is pre-fixed to the robotic arm front end with a known fixed relative relationship, establishing the coordinate transformation in advance. This preliminary setup eliminates the need for multiple iterative image acquisitions during calibration, reducing calibration time while maintaining accuracy through the pre-established geometric relationship.
Solution Approach 2:
The calibration plate serves as an intermediary object that bridges the visual device coordinate system and the robotic arm coordinate system. By capturing a single image of this intermediary with known geometric relationships, the system can compute the relative pose transformation without requiring multiple images or complex iterative procedures.
2Measurement precision
If multiple images of the calibration plate are acquired with various poses, then the accuracy of relative poses between coordinate systems is improved, but the calibration process complexity is increased and becomes sensitive to operator experience
Solution Approach 1:
The system uses the robotic arm's own motion capabilities to automatically position the calibration plate in the visual device's field of view. The robotic arm autonomously adjusts its pose to capture the calibration image, eliminating the need for operator intervention to manually position the calibration plate, thereby reducing process complexity and operator dependency.
Solution Approach 2:
The patent replaces the manual mechanical positioning process with an automated computational approach. Instead of requiring operators to manually adjust the calibration plate to multiple poses, the system uses image processing and coordinate transformation algorithms to compute the relative pose from a single image, substituting mechanical complexity with computational simplicity.
3Manufacturing precision
If conventional calibration methods are used to achieve high accuracy, then the precision of work piece positioning is improved, but the calibration process becomes difficult to integrate into automation systems
Solution Approach 1:
The system implements a feedback loop where the visual device captures images of the calibration plate, the computing device processes these images to determine the robotic arm's pose, and this information is used to calibrate the coordinate systems. This automated feedback mechanism enables high precision positioning while being easily integrable into automation systems, as the entire calibration process can be controlled and monitored through software.
Data Source
AI summary
A calibration method for a robotic arm system is provided. The method includes: capturing an image of a calibration object fixed to a front end of the robotic arm by a visual device, wherein a pedestal of the robotic arm has a pedestal coordinate system, and the front end of the robotic arm has a first relative relationship with the pedestal, the front end of the robotic arm has a second relative relationship with the calibration object; receiving the image and obtaining three-dimensional feature data of the calibration object according to the image by a computing device; and computing a third relative relationship between the visual device and the pedestal according to the three-dimensional feature data, the first relative relationship, and the second relative relationship to calibrate a position error between a physical location of the calibration object and a predictive positioning-location generated by the visual device.