Multi-LIDAR Object Recognition Using Segmented Contour Processing
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Solution Overview
Problem
Existing object recognition systems for autonomous vehicles face challenges in accurately identifying the position of objects, particularly in confined spaces like tunnels, due to the disparity in data from multiple LIDAR sensors and the need for reduced computational load.
Innovation Solution
The system employs a processor to identify contour points of stationary objects by processing data from multiple LIDAR sensors, adjusting candidate contour points based on sensor direction and distance, and generating signals to display object locations on a map, thereby enhancing accuracy and reducing computation when identifying specified objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data from multiple LIDAR sensors is processed to increase measurement coverage, then object position identification accuracy is improved, but computational load increases
Solution Approach 1:
The patent segments the contour points into multiple groups, where each group corresponds to a specific LIDAR sensor. The processor then processes each group separately rather than handling all points uniformly, which reduces computational complexity while maintaining the benefits of multi-sensor data fusion for improved position accuracy.
Solution Approach 2:
The patent applies different processing strategies to different groups of contour points based on their source sensors and spatial locations. By treating each sensor's data with appropriate local processing rules and weighting factors, the system optimizes computational efficiency for each region while achieving overall high accuracy through localized quality adjustments.
2Measurement precision
If contour points from multiple LIDAR sensors are integrated to improve location accuracy in confined spaces, then object recognition accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent divides the contour points into groups corresponding to different LIDAR sensors, enabling modular processing. Each group can be processed independently with specific algorithms tailored to that sensor's characteristics, reducing the overall complexity of integrating multi-sensor data while maintaining high location accuracy in confined spaces like tunnels.
Solution Approach 2:
The patent introduces an intermediary processing layer that handles the complexity of multi-sensor data fusion. This intermediary structure manages the coordination between different LIDAR sensors, resolves discrepancies in their data, and synthesizes accurate location information without exposing the complexity of the fusion process to the overall system.
3Productivity
If all contour points are processed to ensure complete object identification, then recognition completeness is improved, but computational time increases
Solution Approach 1:
The patent applies partial processing by selectively processing contour point groups based on their importance and spatial distribution. Instead of uniformly processing all points, the system identifies and processes only the necessary portions of contour data required for complete object recognition, reducing computational time while maintaining recognition completeness through strategic sampling and prioritization.
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 increases the accuracy of object position identification and reduces computational requirements by effectively integrating data from multiple LIDAR sensors and optimizing processing based on object type and location.
Implementation Method 1
The LIDAR may obtain a distance from the LIDAR to the object through an interval between a time point at which the laser is transmitted and a time point at which the laser reflected on the object is received
Implementation Method 2
a time point at which the laser reflected on the object is received
Data Source
AI summary
An apparatus may include a first LIDAR, a second LIDAR, and a processor. The processor may identify contour points of an object by using or changing points obtained through any one of the first LIDAR and the second LIDAR among points obtained through the first LIDAR and included in a specific frame and points obtained through the second LIDAR and included in the specific frame, based on obtaining a signal indicating a limited space where a host vehicle is located, from the map system. The points obtained through the first LIDAR and included in the specific frame may be obtained from a same object as the points obtained through the second LIDAR and included in the specific frame.