3D LIDAR Clear Path Detection via Ground Plane Estimation
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Solution Overview
Problem
Current autonomous driving systems face challenges in efficiently processing complex road conditions to identify a clear path for vehicle navigation, requiring significant computational power and often bulky equipment to distinguish between various objects and road features.
Innovation Solution
A method utilizing a vehicle LIDAR system to generate a three-dimensional scan of the surrounding area, estimating a ground plane, and comparing this data with the scan to detect a clear path, thereby focusing on the likelihood of road availability rather than individual object identification, reducing the need for extensive processing of object classifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If object classification and separation methods are used to identify clear path, then object identification accuracy is improved, but processing time increases and device complexity increases
Solution Approach 1:
The patent extracts only the essential ground plane information from the full 3D LIDAR point cloud data, separating the ground surface estimation from detailed object classification. By taking out only the necessary ground plane parameters (normal vector, position) and comparing them directly with LIDAR measurements, the system achieves clear path identification without the time-consuming process of classifying and separating individual objects, thus resolving the contradiction between identification accuracy and processing time
Solution Approach 2:
The patent segments the complex task of clear path identification into two distinct parts: (1) ground plane estimation using a simplified mathematical model, and (2) direct comparison of LIDAR data with the estimated ground plane. This segmentation eliminates the need for comprehensive object classification while maintaining accurate clear path detection, thereby reducing processing time without sacrificing identification accuracy
2Measurement precision
If comprehensive object classification is performed to identify clear path, then navigation accuracy is improved, but computational power requirements increase
Solution Approach 1:
The patent extracts only the critical ground plane characteristics (surface normal, position, orientation) from the environmental data, discarding unnecessary object classification information. By focusing computation solely on ground plane estimation and comparison rather than comprehensive object analysis, the system maintains high navigation accuracy while dramatically reducing computational power requirements
Solution Approach 2:
Instead of the conventional approach of identifying objects and then determining clear paths around them, the patent inverts the logic by directly comparing LIDAR measurements with the estimated ground plane. This inversion eliminates the need for complex object classification algorithms, reducing computational power while preserving navigation accuracy through direct ground surface analysis
3Measurement precision
If detailed object recognition systems are used to detect clear path, then path identification accuracy is improved, but device complexity and equipment size increase
Solution Approach 1:
The patent extracts only the essential ground plane parameters from the LIDAR point cloud data using a simplified mathematical model, eliminating the need for bulky object recognition hardware. By taking out only the necessary ground surface information (normal vector, position, orientation) and comparing it directly with measured data, the system achieves accurate path identification with minimal device complexity
Solution Approach 2:
The patent replaces complex mechanical/optical object recognition systems with a mathematical ground plane estimation approach. Instead of using sophisticated cameras and processors to identify and classify objects, the system uses mathematical modeling to estimate the ground surface and directly compares LIDAR measurements with this model, achieving the same navigation goal with significantly reduced device complexity
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient detection of a clear path by analyzing the ground plane and its anomalies, reducing computational load and enabling effective navigation in complex environments without the need for extensive object classification, thus enhancing the processing speed and accuracy of autonomous driving systems.
Implementation Method 1
generating a datastream corresponding to a three-dimensional scan of a target area surrounding the vehicle from a vehicle LIDAR system
Data Source
AI summary
A method for detecting a clear path of travel for a vehicle includes generating a datastream corresponding to a three-dimensional scan of a target area surrounding the vehicle from a vehicle LIDAR system, estimating a ground plane for a present vehicle location using the datastream corresponding to the three-dimensional scan of the target area surrounding the vehicle, and comparing the datastream corresponding to the three-dimensional scan of the target area surrounding the vehicle with the estimated ground plane to detect a clear path of vehicle travel.