Marker-Based Vehicle Positioning for Real-Time Fixed Parking
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Solution Overview
Problem
Existing automatic parking systems face challenges in achieving accurate and robust vehicle positioning in fixed parking scenarios due to high computational complexity and time consumption in algorithms like RANSAC and ICP, which are not suitable for real-time applications.
Innovation Solution
A vehicle positioning method and system that utilizes marker detection and ICP algorithm enhancement with SVD decomposition to identify pairs of markers, reducing computational complexity by matching specific markers in a fixed parking scenario, and employing a coarse and fine matching process to improve accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If RANSAC algorithm is used for robust parameter estimation, then matching reliability is improved, but computational time increases significantly
Solution Approach 1:
The patent applies preliminary action by performing SVD decomposition on the marker coordinates before the matching process. This pre-computation of the transformation matrix eliminates the need for iterative parameter estimation during runtime, providing both robustness and speed without the computational burden of RANSAC iterations.
2Manufacturing precision
If ICP algorithm is used for accurate point cloud matching, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent extracts only the essential marker points from the complete point cloud data, ignoring unnecessary surrounding points. This selective extraction maintains matching accuracy while dramatically reducing algorithm complexity and computational load compared to processing entire point clouds with ICP.
Solution Approach 2:
The patent changes the parameter representation from 3D point cloud coordinates to 2D marker image coordinates combined with predefined 3D marker models. This parameter transformation simplifies the matching problem from complex point-set registration to straightforward feature point correspondence, reducing algorithm complexity while preserving accuracy.
3Productivity
If feature-based image matching is used to reduce computational complexity, then productivity is improved, but measurement precision deteriorates
Solution Approach 1:
The patent introduces markers as intermediary objects that bridge the gap between simple image features and accurate 3D positioning. These markers serve as mediators that provide easily detectable image features while maintaining precise known 3D coordinates, thus achieving both high processing speed and high positioning accuracy simultaneously.
Data Source
AI summary
The disclosure relates to a vehicle positioning method and system for a fixed parking scenario. The method includes: a marker detection step of detecting markers and identifying a pair of markers; a pose matching step of performing pose matching based on vehicle position information and the pair of markers; a non-pose matching step of performing non-pose matching based on the pair of markers, to obtain latest vehicle position information; and a position update step of updating current vehicle position information based on the latest vehicle position information obtained in the pose matching step or the non-pose matching step.