Rail Point Cloud Calibration for Train Sensor Alignment
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Solution Overview
Problem
Existing train sensor systems face challenges in accurately integrating sensor information due to individual sensor parameter errors caused by vehicle body vibrations and the need for costly and maintenance-intensive calibration equipment.
Innovation Solution
A correction device and method that utilizes a rail detection unit to determine the feasibility of calibration based on rail point clouds, correcting sensor information without the need for additional calibration equipment by using linearity evaluation and triaxial rotation/translation adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If calibration equipment (measurement area with reference lines) is provided to correct sensor external parameters, then sensor information integration accuracy is improved, but device complexity and maintenance requirements increase
Solution Approach 1:
The patent introduces rails as an intermediary calibration target that naturally exists in the sensor's field of view. Instead of using complex artificial measurement equipment, the rails serve as a mediator to establish coordinate relationships and calculate external parameters. The rail detection unit detects rail points, and the external parameter calculation unit uses these points to compute transformation parameters, thereby simplifying the calibration system while maintaining accuracy.
Solution Approach 2:
The system uses the existing rail infrastructure in the environment as a self-provided calibration target. The rails automatically serve as the measurement reference without requiring external calibration equipment to be installed or maintained. The sensor system calibrates itself by detecting and processing rail geometric information that is already present in its operational environment.
2Manufacturing precision
If calibration equipment is installed to correct sensor parameter errors, then external parameter correction accuracy is improved, but maintenance cost and time increase due to contamination and loss
Solution Approach 1:
The patent replaces vulnerable artificial calibration targets with durable rail infrastructure as the calibration mediator. Rails are fixed environmental features that do not deteriorate, get contaminated, or get lost like artificial markers might. This eliminates the need for maintenance while providing stable, repeatable calibration references for external parameter calculations.
Solution Approach 2:
Instead of using physical calibration equipment that needs maintenance, the system creates a virtual model of the rails through point cloud detection and processing. The rail geometric information is copied into digital form for calculation purposes, eliminating the need to physically maintain the actual calibration targets while preserving their geometric properties for accurate parameter computation.
3Area of stationary object
If multiple sensors with different monitoring areas are mounted to expand front monitoring area, then object detection rate is improved, but sensor information integration becomes more difficult due to parameter errors
Solution Approach 1:
The patent implements a universal calibration approach using rails that works for all sensors in the multi-sensor system. The same rail-based calibration method can be applied to sensors with different types, positions, and monitoring areas. The external parameter calculation unit computes transformation parameters for each sensor relative to the same rail reference, enabling consistent integration across diverse sensors without requiring sensor-specific calibration procedures.
Data Source
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AI summary
Provided is a correction device including: a rail detection unit 102 which detects a first rail point cloud 30an indicating positions of rails 20Lt and 20Rt based on first sensor information acquired by a first sensor 101a; a calibration feasibility determination unit 103 which determines feasibility of calibration of the first sensor 101a based on a first linearity indicating a degree of a straight line with respect to the first rail point cloud 30an; and a sensor information correction unit 105 which corrects the first sensor information based on the first rail point cloud 30an and a point cloud 30at which is a reference rail point cloud that indicates three-dimensional positions of rails and is different from the first rail point cloud in a case where the calibration feasibility determination unit 103 determines that calibration is possible. Accordingly, a correction device and a correction method capable of performing more accurate calibration without providing calibration equipment are provided.