LiDAR-Camera Synchronization Using Image-Based Offset Detection
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Solution Overview
Problem
Existing autonomous vehicles face synchronization challenges between different types of sensors, such as LiDAR and cameras, leading to perception errors and increased computational demands.
Innovation Solution
A synchronization system that adjusts synchronization parameters based on image analysis from a single sensor type, such as a camera, to align LiDAR and camera data, reducing hardware requirements and computational load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor types (LiDAR and camera) are used for environmental perception, then measurement precision and reliability are improved, but device complexity and computational demands increase
Solution Approach 1:
The patent uses a synchronization pattern (visual marker) as an intermediary object that both LiDAR and camera sensors can detect. This pattern serves as a common reference that facilitates synchronization between the two sensor types without requiring complex direct coordination mechanisms. The pattern acts as a mediator that translates between different sensor modalities, enabling precise temporal and spatial alignment while keeping the synchronization system relatively simple.
2Reliability
If LiDAR and camera sensors are synchronized with high precision, then perception errors are reduced, but computational resources and processing time increase
Solution Approach 1:
The system performs preliminary synchronization by detecting the synchronization pattern before main perception operations. The pattern detection establishes temporal and spatial reference points in advance, allowing subsequent sensor data to be aligned without requiring continuous complex computational synchronization. This preliminary alignment reduces the computational burden during actual perception tasks while maintaining high perception accuracy.
3Reliability
If continuous synchronization monitoring is performed between sensors, then desynchronization issues are detected early, but computational load and processing time increase
Solution Approach 1:
The system implements periodic synchronization monitoring using synchronization patterns at designated intervals rather than continuous monitoring. The patterns are placed at specific locations or time intervals, and the system checks synchronization by detecting these patterns periodically. This approach maintains reliable synchronization detection while significantly reducing computational load and processing time compared to continuous monitoring, as the system only needs to process synchronization data at discrete periodic points.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances sensor synchronization efficiency, reduces computational resources, and increases safety by detecting desynchronization issues, thereby minimizing errors and downtime.
Implementation Method 1
detecting, with a camera, an image including a synchronization pattern corresponding to at least one electromagnetic wave emitted from the rangefinder system
Data Source
AI summary
Provided are methods, systems, and computer program products for image based LiDAR-camera synchronization. An example method may include: obtaining an image from an image sensor; detecting at least one edge of a pattern in the image, the pattern corresponding to at least one electromagnetic wave emitted from a rangefinder system; determining an offset between the pattern and the image based on the at least one edge of the pattern; determining the offset satisfies a synchronization threshold; and based on the determining the offset satisfies a synchronization threshold, adjusting a synchronization parameter of the image sensor or rangefinder system.