LiDAR Ground Detection Using Circular Grid Profiles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing lidar sensors face challenges in efficiently and accurately detecting the ground surface due to the large volume of point data, varying ground environments, and compatibility issues across different sensor types, leading to prolonged processing times and reduced applicability.
Innovation Solution
A method involving a ground detection device that divides lidar point data into a circular grid map, generates profile values for cells, and detects ground points using height comparisons and line fitting functions, irrespective of sensor type.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all lidar points are accessed and clustering and ground detection are performed, then ground detection accuracy is improved, but processing time increases considerably
Solution Approach 1:
The patent divides the point cloud data into multiple subsets based on spatial distribution and processes each subset separately. This segmentation allows parallel processing of different regions, reducing overall processing time while maintaining detection accuracy through comprehensive coverage of all segments
Solution Approach 2:
The patent performs preliminary filtering and classification of points before detailed ground detection. By pre-identifying potential ground points using height thresholds and spatial criteria, the system reduces the data volume requiring intensive processing, thereby decreasing processing time without sacrificing accuracy
2Adaptability or versatility
If ground detection is performed in various ground environments (curves, overpasses, underpasses), then detection versatility is improved, but algorithm complexity increases
Solution Approach 1:
The patent applies different detection parameters and thresholds tailored to specific ground environments. For example, height thresholds are adjusted for overpasses versus flat roads, and curvature parameters are modified for弯道 versus straight sections. This localized adaptation enables versatile detection across diverse environments without requiring a completely different algorithm for each scenario
Solution Approach 2:
The patent dynamically adjusts detection parameters based on the detected ground characteristics and environmental context. The algorithm automatically adapts to curves, overpasses, and underpasses by modifying processing parameters in real-time, providing versatility while maintaining manageable complexity through adaptive rather than static processing
3Measurement precision
If a ground detection method is designed for a specific lidar sensor type, then detection precision for that sensor is improved, but adaptability to other sensor types deteriorates
Solution Approach 1:
The patent designs the ground detection algorithm to accept point cloud data from various lidar sensor types through a unified interface. By implementing sensor-agnostic processing that works with different scanning methods (rotating, solid-state, MEMS) and data formats, the system achieves both precision and broad compatibility across multiple sensor platforms
Data Source
AI summary
A method of detecting a ground that is performed by a ground detection device is provided. The method includes arranging points obtained from a lidar sensor in a plurality of cells included in a circular grid map, generating a profile value for each of the plurality of cells using heights of the points; and detecting around points arranged in each of the plurality of cells using the profile values.