Pallet Corner Detection Using Image Row Analysis
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Solution Overview
Problem
Positioning a forklift carriage to pick up or put away palletized materials becomes increasingly difficult at higher elevations due to reduced visual perspective, requiring extensive training and increasing the time needed for efficient use of materials handling vehicles.
Innovation Solution
A method and system that utilize a computer to analyze grayscale images, identify pallet corners, and trace lines by positioning windows over image rows and columns to determine the location of pallets, allowing the forklift to accurately position itself for pallet retrieval or placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual perspective is used to position forklift carriage at high elevations, then the operator can identify pallet locations, but the accuracy and ease of positioning deteriorates due to reduced visual clarity
Solution Approach 1:
The patent replaces the mechanical/visual positioning system with an optical detection and image processing system. A camera captures images of pallets, and a processor automatically analyzes the images to determine pallet locations and dimensions, eliminating the need for operators to visually estimate positions at high elevations. This substitution of mechanical visual estimation with optical detection and digital processing directly resolves the contradiction by providing accurate measurement without requiring operator skill or visual clarity.
Solution Approach 2:
The patent introduces an intermediary system consisting of a camera and image processing software that mediates between the operator and the pallet positioning task. Instead of the operator directly visually identifying and positioning the forklift carriage, the camera captures images and the processing system automatically determines pallet locations, serving as an intermediary that bridges the gap between the operator's control and the positioning task, thereby improving both accuracy and ease of operation.
2Measurement precision
If extensive training is provided to operators for high elevation pallet positioning, then positioning accuracy improves, but the time required for operation increases
Solution Approach 1:
The patent implements a self-service positioning system where the camera and image processing software automatically perform the positioning analysis without requiring operator intervention or skill. The system independently captures images, processes them to identify pallet locations and dimensions, and provides positioning information to the operator or controls the forklift carriage automatically, eliminating the need for extensive operator training and reducing operation time simultaneously.
Solution Approach 2:
The patent substitutes the human operator's trained visual estimation and manual positioning process with an automated optical detection and digital processing system. The camera and image processing software perform the analysis that would otherwise require extensive operator training, thereby achieving high positioning accuracy without the time cost of training and reducing the time required for actual operation.
3Measurement precision
If multiple image processing steps are applied to trace lines and identify pallet features, then the precision of pallet location improves, but the computational complexity and processing time increase
Solution Approach 1:
The patent applies segmentation by dividing the image processing task into distinct functional steps: capturing images, preprocessing to enhance contrast and identify edges, tracing horizontal and vertical lines from detected corners, and analyzing intersections to identify pallet features. Each step focuses on a specific aspect of the problem, making the overall complex task manageable and systematic. This segmentation allows the system to achieve high precision through coordinated simple operations rather than a single complex algorithm.
Solution Approach 2:
The patent employs preliminary action by performing image preprocessing steps before the main analysis. The system first enhances image contrast, identifies potential edges and corners, and pre-processes the image data to highlight relevant features. This preliminary processing simplifies subsequent line-tracing and feature identification steps, reducing the computational complexity required for the main analysis while maintaining high precision in pallet feature identification.
Data Source
AI summary
A method is provided for tracing a line from a possible corner of a pallet. The method may comprise: providing a Ro image; identifying, using a computer, a possible pallet corner in the Ro image; positioning, using the computer, a J×K window over at least respective portions of a plurality of rows in the Ro image including at least a portion of a row containing the possible corner; calculating, using the computer, an average of pixel values for each row in the J×K window; determining, using the computer, one of the rows in the J×K window having an average pixel value nearest a current pixel location being considered for inclusion in a line being traced and defining the one row as a nearest row; and deciding, using the computer, whether the nearest row is over a pallet.