Multi-Sensor Time Alignment for Camera-LiDAR Perception Fusion
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Solution Overview
Problem
Different types of sensors, such as cameras and LiDAR, struggle to achieve accurate time synchronization due to differences in sensor types, characteristics, manufacturers, and application schemes, leading to challenges in synchronizing sensed data.
Innovation Solution
A method for synchronizing multiple types of sensors by aligning data sensing times using a common trigger source and synchronization signal generators, adjusting sensing times to a unified reference point, and compensating for individual sensor delays to ensure temporal alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple types of sensors (cameras, LiDAR) are used to obtain diverse sensed data, then the comprehensiveness of environmental perception is improved, but achieving accurate time synchronization between these sensors becomes difficult due to differences in sensor types, characteristics, manufacturers, and application schemes
Solution Approach 1:
The patent introduces a back-end synchronization algorithm as an intermediary mechanism that processes and synchronizes data from multiple sensor types after data acquisition. This mediator handles the temporal alignment challenges between cameras, LiDAR, and other sensors by applying correction algorithms in the back-end processing stage, thus resolving the synchronization difficulty without requiring hardware modification of diverse sensors
Solution Approach 2:
The patent performs preliminary time synchronization calibration during the sensor setup and data collection phase. By pre-calibrating time offsets and synchronization parameters before actual sensing operations, the system establishes a foundation for accurate temporal alignment that simplifies subsequent processing and improves overall synchronization accuracy across different sensor types
2Measurement precision
If back-end synchronization algorithms are used to compensate for time misalignment, then time synchronization accuracy is improved, but the complexity of back-end processing increases
Solution Approach 1:
The patent applies partial synchronization by focusing correction efforts on the most critical time alignment requirements rather than attempting to synchronize all possible temporal aspects of multi-sensor data. This selective approach achieves sufficient synchronization accuracy for the application while avoiding the excessive complexity that would result from comprehensive synchronization of all data dimensions
Data Source
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AI summary
The disclosure relates to a method for sensing synchronization between a plurality of types of sensors, a sensor time synchronization control system, a computer-readable storage medium, an autonomous driving system, and a vehicle. The method includes: S1: aligning the first data unit sensed by each of the one or more first sensors at a first data sensing time; S2: aligning the second data unit sensed by each of the one or more second sensors at a second data sensing time; and S3: adjusting the first data sensing time and/or the second data sensing time to align the two, where at the first data sensing time after alignment, the first data unit sensed by at least one of the one or more first sensors represents a first environmental space, and the second data unit of corresponding at least one of the one or more second sensors represents a second environmental space, and the first environmental space and the second environmental space at least partially overlap.