3D Loading Container Corner Recognition Under Variable Lighting
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Solution Overview
Problem
Existing image-based systems for detecting the edges and corners of loading containers face challenges in handling varying shapes, colors, and lighting conditions, leading to reduced robustness and accuracy.
Innovation Solution
An arrangement using a stereo camera or electro-optical device with a machine learning system that generates a three-dimensional distance image and a two-dimensional estimate of the container's corners, employing semantic segmentation and multi-task learning to improve detection accuracy and robustness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional image-based systems are used to detect edges and corners of loading containers, then the system can identify container positions, but the detection accuracy and robustness deteriorate under varying shapes, colors, and lighting conditions
Solution Approach 1:
The patent transitions from traditional 2D image-based detection to 3D point cloud data processing. By capturing spatial coordinates in three dimensions and projecting them onto 2D image planes, the system achieves more robust detection that is invariant to lighting conditions, container colors, and shape variations while maintaining precise corner position identification.
2Reliability
If complex image processing algorithms are used to handle varying container shapes and lighting conditions, then detection robustness improves, but computational complexity and processing time increase
Solution Approach 1:
The patent replaces complex traditional image processing algorithms with a geometric approach based on point cloud data. Instead of using computationally intensive computer vision techniques to interpret visual information, the system directly processes spatial coordinates from time-of-flight sensors, significantly reducing computational complexity while improving robustness to lighting and color variations.
3Measurement precision
If multiple sensors and complex processing systems are deployed to improve detection accuracy, then measurement precision improves, but system complexity and cost increase
Solution Approach 1:
The patent makes the point cloud acquisition system perform multiple functions: it simultaneously captures container edges, identifies corners, calculates 3D positions, and provides data for both visual and structural analysis. This multi-functionality eliminates the need for separate sensors and processing systems, reducing overall system complexity while maintaining high measurement precision.
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 system provides robust and accurate image-based recognition of loading containers, capable of controlling the unloading process with minimal computational effort and high precision, even under diverse conditions.
Implementation Method 1
an electro-optical device directed or directional towards the loading container, configured to provide an image signal containing distance information
Data Source
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AI summary
An arrangement for image-based detection of the position of a loading container (18) comprises an electro-optical device (126) directed or directional towards the loading container (18) and configured to provide an image signal containing distance information, and an electronic evaluation device configured to generate, from the image signal, a distance image with respect to the spatial location of the edges of the loading container (18) and a two-dimensional estimate of the position (144) of the corners of the loading container (18) within the image, and to provide, from the distance image and the estimate, a position signal with respect to the spatial position of the corners of the loading container (18).