Surface Quality Determination Using Curvature Approximation
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Solution Overview
Problem
Existing sensor arrangements for transportation vehicles are inadequate in measuring the condition of unpaved roadways, often resulting in intense measurement noise and errors, which can lead to unreliable detection of potholes, slopes, and obstacles, especially in automatic driving scenarios.
Innovation Solution
A method and device that generate three-dimensional surface coordinates using a sensor arrangement, which approximate the curvature contour of the surface to accurately characterize its condition by defining a two-dimensional point lattice and using spline curves to create a smooth curve that represents the surface, allowing for reliable detection of negotiable regions and obstacles despite measurement noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing sensor arrangements are used to measure surface conditions, then the measurement process is simple, but the measurement precision deteriorates due to intense measurement noise and errors
Solution Approach 1:
The sensor arrangement is segmented into multiple sensors positioned at different locations (front, rear, left, right) of the vehicle. Each sensor captures surface coordinates from its specific viewpoint, and the evaluation unit processes each sensor's data separately before integrating them to form a complete surface model, thereby reducing measurement noise through distributed sensing
Solution Approach 2:
The system transitions from two-dimensional surface measurements to three-dimensional surface coordinate capture. By adding the vertical dimension (z-coordinate) to the horizontal plane measurements, the system can accurately represent surface topology including potholes, slopes, and obstacles, significantly improving measurement precision for unpaved road conditions
2Reliability
If three-dimensional surface coordinates are generated using multiple sensors, then the reliability of surface detection improves, but the device complexity increases
Solution Approach 1:
The evaluation unit is designed as a multi-functional processing system that handles data from multiple sensor types (cameras, laser scanners, sonar) and performs multiple tasks: generating 3D coordinates, approximating curvature contours, classifying surface conditions, and identifying negotiable regions. This universal processing approach improves detection reliability without proportionally increasing device complexity
Solution Approach 2:
The evaluation unit acts as an intermediary between the multiple sensors and the vehicle control system. It consolidates and processes the raw data from all sensors, creating a unified surface model that reliably represents the terrain, thereby improving detection reliability while managing the complexity through centralized processing
3Measurement precision
If curvature contour approximation is used to characterize surface condition, then the measurement precision improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The system performs preliminary actions by first generating the three-dimensional surface coordinates from sensor data before proceeding to curvature contour approximation. This pre-processing step organizes the raw measurement data into a structured 3D coordinate system, making the subsequent curvature analysis more manageable and precise
Solution Approach 2:
The system explicitly models surface curvature by approximating curvature contours from the 3D surface coordinates. By directly calculating and analyzing curvature characteristics (using derivatives of the surface coordinates), the system achieves precise surface condition characterization, identifying features like potholes and slopes based on their curvature signatures
Data Source
AI summary
A method for determining a quality of a surface in the surroundings of a transportation vehicle, wherein three-dimensional surface coordinates of the surface are generated using a sensor assembly. In the method, an approximation of the course of the curvature of the surface in at least one direction is obtained based on the surface coordinates and the surface coordinates are classified to characterize the quality of the surface using the course of the curvature and/or vertical distances of the approximation of the course of the curvature from the three-dimensional surface coordinates. A device for carrying out the method.