UAV Visual Marker Decoding Under Occlusion in Warehouse Navigation
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Solution Overview
Problem
Current inventory management systems using Unmanned Aerial Vehicles (UAVs) face difficulties in navigating through warehouses with boxes of varying sizes and occluded visual markers, where partial or full invisibility of markers due to stacking affects data reading and navigation.
Innovation Solution
A processor-implemented method for UAVs to capture images of visual markers, determine if the entire area is covered, recover missing information using parity codes, and reconstruct the binary code to enable navigation, even when parts of the marker are obscured.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple boxes are stacked in the warehouse, then the storage capacity is improved, but the visual markers on boxes in the back rows become occluded and invisible
Solution Approach 1:
The patent applies error correction coding (parity codes) to the visual marker data in advance. This preliminary encoding ensures that even if parts of the marker are occluded, the original information can be recovered through decoding and error correction, eliminating the need for complete marker visibility.
Solution Approach 2:
The patent converts the harmful effect of occlusion into a beneficial scenario by using redundant parity code information. The occlusion that would normally prevent reading becomes a manageable condition where the system can reconstruct the original data through error correction algorithms, turning a failure mode into a recoverable situation.
2Measurement precision
If the UAV navigates to read visual markers on stacked boxes, then the inventory management accuracy is improved, but the navigation fails when markers are occluded
Solution Approach 1:
The system performs preliminary error correction encoding on the visual marker data before it is displayed. This advance preparation ensures that the marker contains redundant information capable of withstanding occlusion, allowing the UAV navigation system to reliably read markers even when partially blocked, thus maintaining both accuracy and reliability.
Solution Approach 2:
The patent implements a feedback mechanism where the UAV attempts to read the marker, detects occlusion through failed reading, and then uses the error correction decoding process to recover the original information. This feedback loop ensures that navigation reliability is maintained by continuously adapting to the actual visibility conditions.
3Ease of manufacture
If manual inventory verification is performed, then the process is simple to implement, but the time consumption and labor cost increase significantly
Solution Approach 1:
The patent enables the visual marker system to be self-sufficient by incorporating error correction codes directly into the marker. The marker automatically contains the information needed to correct its own occlusion-related errors, eliminating the need for complex external correction systems and maintaining implementation simplicity while enabling automated UAV reading.
Solution Approach 2:
The patent replaces manual inventory verification with an automated UAV-based optical reading system. The UAV equipped with image processing capabilities automatically captures and decodes visual markers, substituting human labor with automated optical-mechanical systems, thereby reducing time consumption while maintaining ease of implementation through standardized marker protocols.
Data Source
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AI summary
System and method for visual marker decoding for occlusion management in Unmanned Aerial Vehicle (UAV) navigation for inventory management is provided. When the UAV has to be navigated based on navigation information embedded in visual markers on different items in the inventory, and if one or more of the visual markers are not completely visible due to occlusion, then the UAV automatically recovers data that is missing due to the occlusion, and accordingly navigates the UAV.