Automated Workpiece Inspection Using Depth Sensing and Pose Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Manual and existing automated inspection methods for workpieces are prone to human error, time-consuming, and limited in accessibility and accuracy, especially when dealing with large or complex assemblies, and are not effective for all materials.
Innovation Solution
An automated inspection system that uses a depth sensing device and pose detection system to measure actual depth distance data and compare it to model data, determining if the workpiece meets predetermined criteria, and displaying deviations using an overlay, thereby reducing human error and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection methods are used, then inspectors can use visual and tactile inspections to detect differences, but human error is introduced and inspection is time-consuming
Solution Approach 1:
The patent replaces manual visual and tactile inspection methods with an automated depth sensing system that uses optical or other non-contact sensing technology to measure workpiece geometry. The depth sensing device captures depth data points that are automatically compared to CAD model data, eliminating human inspectors and their potential for error while providing rapid automated measurement.
Solution Approach 2:
The system enables self-inspection by automatically comparing measured depth data from the workpiece against the CAD model without requiring human interpretation. The pose detection system and automated comparison algorithms allow the inspection system to independently determine compliance with specifications.
2Productivity
If automated image processing is used, then inspection speed is improved, but inaccuracies occur when identifying small parts or objects of the same color
Solution Approach 1:
The patent transitions from 2D image processing to 3D depth sensing by measuring the actual depth distance data of pixels relative to the workpiece. This third dimension provides explicit geometric information about surface topology, enabling accurate detection of small parts and features regardless of color similarities, as depth variations are measured directly rather than inferred from 2D images.
3Adaptability or versatility
If X-ray technology is used, then internal inspection capability is improved, but the method is limited to certain materials and still requires visual recognition by inspectors
Solution Approach 1:
The depth sensing system provides universal applicability across different workpiece materials and types by using non-contact optical or other sensing methods that do not depend on material-specific properties like X-ray transparency. The system can inspect diverse workpieces including those with limited accessibility areas through automated positioning and pose detection.
4Reliability
If manual inspection of large assemblies is performed, then inspectors can detect assembly errors, but areas with limited accessibility are difficult to inspect
Solution Approach 1:
The inspection system incorporates dynamic pose detection and automated positioning capabilities that allow the depth sensing device to navigate and inspect areas with limited accessibility. The system can adapt its viewing angles and positions automatically, making previously difficult-to-reach areas accessible for inspection without requiring physical manual access.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A method and a corresponding system for inspecting a workpiece are provided. The method includes inputting model data associated with the workpiece in an inspection system, determining a relative position of a depth sensing device relative to the workpiece, and calibrating a pose view for the inspection system relative to the model based on the position of the depth sensing device relative to the workpiece. The method further includes measuring actual depth distance data of at least one pixel of the depth sensing device relative to the workpiece and determining, based on the actual depth distance data, if the workpiece satisfies predetermined inspection criteria.