AGV Laser Mapping for Precise Airplane Assembly Positioning
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Solution Overview
Problem
Current factory automation systems for airplane assembly face challenges in achieving accurate and repeatable positional accuracy and navigation of Automated Guided Vehicles (AGVs) due to systematic and random errors in laser scanner sensor measurements, and the ability to use taught node positions across different work cells with varying environments.
Innovation Solution
Perform offline calibrations of laser scanner sensors to determine and correct systematic and random errors, filter out non-target objects, and apply mathematical estimators to generate accurate distance measurements for constructing a 2-D map, enabling precise path planning and navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If laser scanner sensors are used for distance measurement, then the AGV can navigate and map the work cell environment, but systematic and random errors cause measurement inaccuracies that exceed the desired AGV positional accuracy
Solution Approach 1:
The patent implements a feedback mechanism where the AGV repeatedly measures distances to the same target features and uses statistical processing to identify and eliminate outliers. The system continuously refines distance measurements by comparing multiple readings and applying filtering algorithms, thereby improving measurement precision through iterative feedback loops.
Solution Approach 2:
The patent applies partial action by selectively using only the laser scanner sensor that provides the best view of target features, rather than relying on all sensors equally. It also uses excessive action by taking multiple measurements beyond what would be minimally required, then filtering results to achieve the desired accuracy level.
2Adaptability or versatility
If the laser scanner sensor scans across a wide Field of Regard to detect target features, then the AGV can identify and navigate to taught node positions, but other static and dynamic objects within the scan area cause mapping ambiguity and navigation issues
Solution Approach 1:
The patent segments the wide Field of Regard into multiple Field of View areas, each associated with a specific laser scanner sensor. By dividing the scanning environment into discrete segments and assigning them to individual sensors, the system can selectively process data from relevant segments while filtering out irrelevant objects in other segments, thereby reducing mapping ambiguity.
Solution Approach 2:
The patent applies local quality by assigning different functional roles to different parts of the scan area. Target features are identified with high priority and precision, while other objects are treated as background or filtered out. This selective focus ensures that navigation reliability is maintained by emphasizing the quality of target feature detection over comprehensive environmental mapping.
3Adaptability or versatility
If multiple laser scanner sensors are used to improve coverage, then the AGV can detect target features from various angles, but the complexity of coordinating measurements from multiple sensors increases
Solution Approach 1:
The patent applies universality by using the same processing methodology for data from all laser scanner sensors. Each sensor's measurements are handled through the same filtering and validation processes, allowing the system to scale to multiple sensors without proportionally increasing complexity. The universal approach simplifies coordination by treating all sensors uniformly.
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
The solution enhances AGV accuracy and repeatability in returning to taught node positions within a work cell and allows the same node positions to be used across different work cells with similar cradle fixtures and workstands, reducing the need for additional teaching and verification.
Implementation Method 1
The laser scanner sensor being used by the AGV scans across 190 degrees in discrete steps, whereby it measures the distance to the object within its laser beam path using an optical pulse time-of-flight measurement principle.
Data Source
Figure 1A
Figure 1B
Figure 1C~1E
AI summary
Work cell and factory level automation require that an Automated Guided Vehicle (AGV) achieve demanding positional accuracy and repeatability relative to a cradle fixture or workstand within a work cell. The AGV makes distance measurements of objects within the work cell using laser scanner sensors. The distance measurements are filtered of objects that are not target features on the cradle fixture or workstand. Systematic or bias errors of the laser scanner sensor are removed from the filtered distance measurements, and a mathematical filter or estimator is applied to the filtered distance measurements using random errors of the laser scanner sensor to generate estimated distance measurements. A map of the target features is then constructed using the estimated distance measurements, wherein the map is used for path planning and navigation control of the AGV relative to the cradle fixture or workstand within the work cell.