Multi-Sensor Sampling Alignment for Autonomous Vehicle Fusion
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Solution Overview
Problem
Existing sensor synchronization methods for autonomous vehicles fail to accurately align data from sensors of different modalities due to differing intrinsic properties, leading to sampling offsets and reduced accuracy in fused representations.
Innovation Solution
A sensor synchronization system that determines a global sampling point based on extrinsic properties and corrects for intrinsic properties of individual sensors, aligning data capture times across various sensor modalities to a common time base.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are synchronized using conventional methods, then data acquisition can proceed, but sampling offsets occur due to differing intrinsic properties of sensors
Solution Approach 1:
The patent changes the timing parameters of each sensor by calculating specific offset values based on their intrinsic properties (exposure time, rolling shutter duration, trigger latency). These parameter adjustments align the effective sampling moments of different sensors to a common global sampling point, resolving the sampling offset issue while maintaining system simplicity.
Solution Approach 2:
The system performs preliminary calibration to determine the intrinsic properties of each sensor before operation. Based on this pre-acquired information, offset values are calculated in advance, allowing sensors to be triggered at different times but effectively sample data at the same global sampling point, thereby eliminating sampling offsets without complex real-time synchronization.
2Measurement precision
If post-processing corrections are applied to compensate for sampling offsets, then alignment accuracy can be improved, but computational resources are consumed
Solution Approach 1:
The patent performs the alignment correction in advance by calculating offset values based on sensor intrinsic properties before data acquisition. This preliminary action ensures that sensors effectively sample at aligned time points without requiring resource-intensive post-processing corrections, thus reducing computational energy consumption while maintaining high alignment accuracy.
3Adaptability or versatility
If sensors have different intrinsic properties (exposure time, shutter duration, trigger latency), then each sensor can be optimized for its function, but sampling alignment becomes difficult
Solution Approach 1:
The patent accepts and utilizes the different intrinsic properties of various sensor modalities (camera exposure time, LIDAR shutter duration, RADAR trigger latency) by calculating specific offset values for each. This approach maintains sensor optimization for their respective functions while achieving precise sampling alignment through parameter adjustment, thus resolving the contradiction between adaptability and measurement precision.
Data Source
AI summary
Disclosed are systems and methods for a sensor synchronization system. Sensors of an autonomous vehicle (AV) are synchronized to cause sampling of a first sensor of the sensors to occur in alignment with sampling of a second sensor of the sensors. A sampling time point for the first sensor is determined based on the synchronizing the sensors, the sampling time point comprising a time when the first sensor is in alignment with the second sensor. The sampling time point is provided to the first sensor. A controller circuit of the first sensor determines an offset of the first sensor to apply to a local system time of the first sensor to cause a data acquisition of the first sensor to occur at the sampling time point. The data acquisition is performed at the first sensor using the sampling time point and the offset.