Visual Odometer Road Track Acquisition in GNSS Blocked Areas
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Solution Overview
Problem
Existing methods for collecting road data in areas with blocked GNSS signals, such as parks and underground parking lots, suffer from low positioning accuracy and inability to link collected road tracks to the existing network, due to high implementation costs and prolonged GNSS signal lock-lose times.
Innovation Solution
A method and device utilizing a visual odometer to acquire real-time spatial relative coordinates, which are then converted to geodetic coordinates and sent to a second device to generate road tracks in areas with blocked GNSS signals, eliminating the need for integrated navigation devices and reducing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an integrated navigation device is used to collect road data in areas with blocked GNSS signals, then positioning accuracy is improved, but implementation cost increases significantly
Solution Approach 1:
The navigation system is divided into two segments: GNSS positioning for open areas and visual odometer for blocked signal areas. This segmentation allows each component to be used only where it is most effective, avoiding the need for expensive integrated navigation devices in all scenarios.
Solution Approach 2:
A server acts as an intermediary to receive coordinate information from both GNSS positioning devices and visual odometers, perform coordinate system transformations, and generate road track data. This intermediary approach allows different positioning methods to work together without requiring expensive integrated devices at the collection point.
2Device complexity
If a general GNSS positioning device is used in areas with blocked signals, then device complexity is reduced, but positioning accuracy deteriorates and road tracks cannot be linked to the existing network
Solution Approach 1:
The patent replaces the electronic GNSS signal reception system with a visual odometer system that uses image processing and feature recognition. The visual odometer captures images, extracts feature points, and calculates position based on visual features rather than satellite signals, enabling operation in blocked signal areas.
Solution Approach 2:
The system changes the positioning parameter from satellite signal strength to visual feature matching accuracy. By transforming the coordinate system and using visual feature points for position calculation, the system maintains positioning capability in areas where traditional GNSS parameters fail.
3Area of stationary object
If GNSS signal lock-lose time becomes longer, then the area covered increases, but positioning accuracy reduces and road tracks cannot be linked to the existing network
Solution Approach 1:
The system performs preliminary actions by establishing a coordinate transformation relationship between the visual odometer's local coordinate system and the geographic coordinate system before actual positioning. This preliminary coordinate system calibration ensures that even after prolonged lock-lose periods, the accumulated position data can be accurately transformed and linked to the existing road network.
Data Source
AI summary
The present disclosure discloses a method and device for acquiring a road track, and a storage medium. The method includes: acquiring, by a visual odometer, when moving in a collecting area, coordinate information of a location of the visual odometer in real time, and the collecting area being an area where GNSS signals are blocked; and sending, by the visual odometer, the coordinate information to a second device, causing the second device to generate a road track in the collecting area according to the acquired coordinate information.