3D Feature Localization via Pre-Calibrated Dual-Sensor Mapping
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Solution Overview
Problem
Existing depth-sensing camera systems struggle in environments with high noise levels and computational burdens, leading to inaccurate and inefficient performance in automated welding processes like additive manufacturing.
Innovation Solution
A calibration method that maps an image sensor and a further sensor to a three-dimensional reference system, allowing for precise depth sensing without requiring specific sensor positioning and reducing computational load, using a dual-camera system without signal emission or disparity maps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If depth-sensing camera systems use stereo-vision or signal emission methods, then depth information can be obtained, but computational burden increases and response time decreases
Solution Approach 1:
The patent applies preliminary action by pre-calibrating the sensing system to create a mapping between sensor readings and three-dimensional positions during a setup phase. This pre-established mapping allows the system to directly convert sensor data to depth information without performing complex computational algorithms during real-time operation, thereby reducing computational burden while maintaining depth sensing accuracy
2Measurement precision
If depth-sensing camera systems use stereo-vision or signal emission methods, then depth information can be obtained, but response time decreases due to high computational burden
Solution Approach 1:
The calibration process establishes a lookup table or mapping function in advance that directly correlates sensor readings with three-dimensional positions. During real-time operation, the system simply queries this pre-computed mapping rather than performing complex disparity calculations or deep learning inference, enabling real-time response with maintained accuracy
3Ease of operation
If depth-sensing camera systems operate in environments with external light sources, then sensing can be performed, but measurement precision decreases due to noise
Solution Approach 1:
The patent replaces active depth-sensing mechanisms (signal emission and reflection detection) with a calibration-based approach using standard image sensors. By substituting the physical sensing mechanism with a pre-established mathematical mapping, the system becomes insensitive to environmental light conditions, as it relies on calibrated correlations rather than active optical signals that can be contaminated by external light sources
4Manufacturing precision
If automated welding systems require high accuracy and responsiveness, then quality welded components can be produced, but existing depth-sensing systems are inefficient and unsuitable
Solution Approach 1:
The system performs calibration in advance to establish the mapping between sensor readings and three-dimensional positions. During actual welding operations, the pre-calibrated system can rapidly convert sensor data to precise depth information without computational delays, simultaneously achieving high manufacturing precision and productivity required for quality welded components
Data Source
AI summary
A method of calibrating a sensing system for determining a position of a feature of an object includes defining reference positions within a three-dimensional reference system; determining corresponding positions within an image frame of an image sensor and positions within a sensor frame of a further sensor; and generating a mapping linking the reference positions and the positions. A position of the feature of the object may be determined based on the mapping. There is also provided a method for monitoring a workpiece, the method comprising: obtaining shortwave infrared images; determining a corresponding image position of a feature of the workpiece or of an automated welding system using a machine-learned model; and determining a position of the feature.