Vision-Based Road Marking Projection for Signal-Weak Areas
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Solution Overview
Problem
Existing road marking painting machines face positioning accuracy issues in areas where satellite signals are weak, such as tunnels or behind buildings, limiting their usage.
Innovation Solution
A construction assisting device that acquires a captured image of the road surface, determines a position for projecting a road marking based on objects in the image, and uses an optical device to project the marking onto the surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If satellite signal positioning is used for road marking painting, then positioning can be performed in open areas, but positioning accuracy deteriorates in places where satellite signals are weak such as tunnels or behind buildings
Solution Approach 1:
The patent introduces an intermediary positioning system that uses road surface objects (manholes, manhole covers, road markings) as reference points for localization. Instead of relying directly on satellite signals, the system captures images of these intermediaries and uses computer vision algorithms to determine the painting machine's position, thereby resolving the contradiction between availability and precision in signal-denied environments
Solution Approach 2:
The patent replaces the satellite-based electromagnetic positioning system with an optical-mechanical vision system. By substituting satellite signal reception with camera-based image capture and processing, the system achieves reliable positioning in tunnels and urban canyons where satellite signals are blocked, while maintaining measurement precision through object recognition algorithms
2Extent of automation
If satellite positioning is used for automatic painting, then the painting machine can operate automatically in open areas, but the device complexity increases due to signal requirements
Solution Approach 1:
The patent replaces complex satellite signal reception and processing systems with a simpler optical camera system and image processing algorithm. This substitution maintains automatic painting capability while reducing device complexity by eliminating the need for specialized satellite receivers and signal processing hardware
Solution Approach 2:
The system uses naturally present road surface objects (manholes, markings) as self-provided reference points for positioning, eliminating the need for additional positioning infrastructure. This self-service approach reduces device complexity by leveraging existing environmental features rather than requiring complex external signal systems
Data Source
AI summary
A construction assisting method includes acquiring a captured image showing a road surface and an object on the road surface, determining, based on the object on the road surface included in the captured image, a position on the road surface ono which a first image used for painting a road marking on the road surface is projected, and causing an optical device to project the first image onto the position on the road surface.


