Real-Time Lidar-to-Vehicle Alignment Detection from Localization Data
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Solution Overview
Problem
Existing methods for aligning lidar and vehicle coordinate systems are time-consuming and not suitable for real-time application, particularly in dynamic vehicle operations.
Innovation Solution
A system and method for automatically detecting the alignment state between a lidar and vehicle coordinate systems using localization data, involving transformation matrices and deep learning neural networks to project lidar data into a vehicle coordinate system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional alignment methods are used to align lidar and vehicle coordinate systems, then alignment accuracy can be achieved, but the process is time-consuming and not suitable for real-time application
Solution Approach 1:
The system pre-establishes the relationship between lidar coordinate system and vehicle coordinate system through transformation matrices before real-time operation. By preparing the coordinate transformation framework in advance, the system enables rapid alignment detection during actual vehicle operation without performing complex alignment calculations in real-time, thus resolving the contradiction between alignment accuracy and detection speed.
Solution Approach 2:
The patent introduces transformation matrices as an intermediary mathematical tool to bridge the lidar coordinate system and vehicle coordinate system. These matrices serve as a pre-computed intermediary that enables rapid coordinate transformation without requiring real-time iterative alignment calculations, thereby achieving both high alignment accuracy and real-time processing capability.
2Measurement precision
If manual alignment detection is performed to ensure precise lidar-to-vehicle transformation, then alignment accuracy is improved, but the operation becomes complex and time-consuming
Solution Approach 1:
The system implements self-service alignment detection by automatically computing transformation matrices and detecting alignment states without requiring manual intervention. The processing circuitry autonomously performs coordinate transformations and alignment verification using pre-established mathematical models, thereby maintaining high transformation accuracy while eliminating the complexity and time consumption associated with manual alignment operations.
Solution Approach 2:
The patent replaces manual mechanical alignment adjustment with automated computational methods. Instead of physically adjusting sensor positions based on manual measurements, the system uses processing circuitry to compute transformation matrices and detect alignment states algorithmically, substituting complex manual mechanical operations with streamlined computational processes that maintain precision while improving ease of operation.
Data Source
AI summary
A system in a vehicle includes a lidar system to obtain lidar data in a lidar coordinate system, and processing circuitry to obtain the lidar data and localization data. The localization data indicates a location and orientation of the vehicle. The processing circuitry automatically determines an alignment state resulting in a lidar-to-vehicle transformation matrix that projects the lidar data from the lidar coordinate system to a vehicle coordinate system to provide lidar-to-vehicle data. The alignment state is determined using the localization data.