LiDAR Point Cloud Merging via Timestamp Synchronization
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Solution Overview
Problem
Existing LiDAR systems struggle to accurately merge data from multiple devices with different physical locations, starting angles, and frequencies, leading to inconsistencies and potential occlusions that affect the precision of environmental perception in autonomous vehicles.
Innovation Solution
A system that synchronizes data from multiple LiDAR devices by using timestamp information to coordinate their point clouds, allowing for the merging of data even when devices have staggered starting angles and frequencies, ensuring that information is recent and usable for navigation and obstacle detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple LiDAR devices with different starting angles and frequencies are used to improve environmental perception coverage, then the coverage area is improved, but the data merging accuracy deteriorates due to synchronization difficulties
Solution Approach 1:
The patent introduces timestamp information as an intermediary element to mediate the synchronization between multiple LiDAR devices with different starting angles and frequencies. Each point cloud data is tagged with timestamp information indicating when the data was captured, allowing the system to correlate and merge data from different devices by matching timestamps or time ranges, thereby resolving the synchronization difficulty while maintaining high merging accuracy
Solution Approach 2:
The patent transforms the synchronization problem from a spatial/angular parameter matching problem to a temporal parameter matching problem. By changing the reference frame from starting angles to timestamps, the system can easily synchronize data from LiDAR devices with different configurations, as timestamps provide a universal time reference that is independent of device-specific parameters like starting angle and frequency
2Speed
If LiDAR devices operate at different frequencies to improve detection speed, then the detection speed is improved, but the data consistency deteriorates making merging difficult
Solution Approach 1:
Timestamp information serves as a mediator that bridges data from LiDAR devices operating at different frequencies. Instead of requiring frequency synchronization, the system uses timestamps to identify corresponding data points from different devices, ensuring data consistency while allowing each device to operate independently at its optimal frequency
Solution Approach 2:
The patent implements a dynamic data merging approach where the system adaptively matches data from different frequency sources based on timestamp proximity rather than requiring fixed frequency alignment. This dynamic matching allows the system to handle varying frequencies while maintaining data consistency through flexible temporal correlation
3Area of stationary object
If LiDAR devices have staggered starting angles to improve field of view coverage, then the coverage is improved, but the temporal alignment of data deteriorates
Solution Approach 1:
The patent changes the alignment parameter from angular position (starting angle) to temporal position (timestamp). This transformation allows the system to handle staggered starting angles effectively, as the timestamp provides a common reference frame that is independent of the angular offset between devices
Solution Approach 2:
Timestamp information acts as an intermediary that decouples the temporal alignment problem from the angular configuration. The system can merge data from devices with any starting angle configuration by using timestamps to establish temporal correspondence, thereby preserving full field of view coverage while achieving proper temporal alignment
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 the accuracy and reliability of LiDAR data merging, enabling better environmental perception and navigation by ensuring that data from multiple sources is coordinated and up-to-date, even in scenarios with rapid changes or occlusions.
Implementation Method 1
at least two LiDAR devices configured to detect light reflected from objects proximate to the vehicle and generate LiDAR point cloud information based on the detected light
Data Source
AI summary
Among other things, a method includes receiving first LiDAR point cloud information from a first LiDAR device and second LiDAR point cloud information from a second LiDAR device, generating third point cloud information according to merging the first and second LiDAR point cloud information, and operating the vehicle based upon the third LiDAR point cloud information.