Visual Vehicle Positioning Fusion with Point Cloud Map Selection
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Solution Overview
Problem
Conventional vehicle positioning technologies, such as GPS, IMU, LiDAR, and cameras, are susceptible to environmental interferences and weather conditions, leading to inaccurate and unreliable positioning, which increases risks in autonomous driving.
Innovation Solution
A visual vehicle-positioning fusion system that integrates an image point cloud map, inertial measurement, and real-time dynamic sensing to enhance accuracy and reliability by fusing multiple sensors' data, using a processing device to select the most accurate location information based on a positioning fusion rule.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single type of positioning sensor (GPS, LiDAR, or camera) is used, then the system cost is reduced or the device complexity is lowered, but the positioning accuracy and reliability deteriorate due to environmental susceptibility
Solution Approach 1:
The patent combines multiple positioning sensors (GPS, LiDAR, and camera) into a unified positioning system that fuses their respective data through a processing device. This merging approach allows the system to leverage the strengths of each sensor type while compensating for their individual weaknesses, thereby improving overall positioning reliability without requiring a single complex sensor
2Measurement precision
If LiDAR is used for positioning, then the positioning precision is improved, but the system cost increases and the device complexity increases
Solution Approach 1:
The patent integrates LiDAR with GPS and camera systems, using the processing device to fuse data from all three sensors. This combination allows the system to achieve high positioning precision through LiDAR's accurate depth measurement while using the other sensors to compensate in conditions where LiDAR performance degrades, thereby maintaining high precision without over-relying on a single complex sensor
3Device complexity
If GPS is used for positioning, then the device complexity is reduced, but the positioning reliability deteriorates due to environmental interference
Solution Approach 1:
The patent combines GPS with LiDAR and camera systems, using the processing device to fuse their data. This allows the system to maintain the simplicity and broad coverage of GPS while using LiDAR and camera data to compensate for GPS signal loss or interference in urban canyons, tunnels, or adverse weather conditions, thereby improving reliability without fully abandoning the simple GPS approach
Data Source
AI summary
A visual vehicle-positioning fusion system and a method thereof is provided. In the method, an image point cloud map stored in a storage device is converted into a longitude and latitude database corresponding to the image point cloud map. Longitude and latitude measurement coordinates received by a positioning device are used as first location information. The longitude and latitude database is compared with the longitude and latitude measurement coordinates to generate the initial location of a vehicle. Feature matching is performed on the initial location and the image point cloud map to generate second location information of the vehicle on the image point cloud map. The first location information or the second location information is selected as a final positioning output information and outputted based on a positioning fusion rule.