LiDAR Occlusion Detection via Echo Data Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current LiDAR systems face challenges in detecting occlusion without affecting transmittance or increasing manufacturing costs, as existing methods like pressure sensors and visual processing units can compromise ranging accuracy and increase costs.
Innovation Solution
A method and apparatus for real-time LiDAR occlusion detection using echo data, where distance information from the echo data is compared to a preset distance range to determine occlusion, without requiring additional sensors or altering the LiDAR's transmittance or manufacturing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a pressure sensor or other sensors are added to detect LiDAR occlusion, then occlusion detection capability is improved, but transmittance of the radome is affected and laser energy is reduced
Solution Approach 1:
The LiDAR system uses its own echo data to detect occlusion, without requiring external sensors. The processing unit analyzes the echo data returned by the transmitting unit to determine occlusion status, allowing the system to serve its own detection needs and eliminate the energy loss associated with additional sensors.
Solution Approach 2:
The occlusion detection function is extracted from the main ranging function by analyzing specific characteristics of the echo data. The processing unit identifies occlusion by detecting abnormal echo patterns or distance information that differ from normal ranging returns, separating the detection function from the measurement function.
2Reliability
If a visual processing unit is added to detect LiDAR occlusion, then occlusion detection capability is improved, but manufacturing cost of the LiDAR is increased
Solution Approach 1:
The processing unit is designed to perform multiple functions: both normal ranging operations and occlusion detection. By making the processing unit universal, the system eliminates the need for separate visual processing units or additional detection hardware, thereby reducing manufacturing costs while maintaining detection capability.
Solution Approach 2:
The LiDAR system uses its own echo data to detect occlusion, without requiring external sensors. The processing unit analyzes the echo data returned by the transmitting unit to determine occlusion status, allowing the system to serve its own detection needs and eliminate the cost of additional sensors.
3Reliability
If additional sensors are added to detect LiDAR occlusion, then occlusion detection capability is improved, but device complexity is increased
Solution Approach 1:
The occlusion detection function is merged with the normal ranging operation. The same transmitting unit generates both ranging laser beams and detection laser beams, and the same processing unit handles both ranging data and occlusion detection analysis. This merging eliminates the need for separate detection hardware and reduces overall system complexity.
Solution Approach 2:
The processing unit is designed to perform multiple functions: both normal ranging operations and occlusion detection. By making the processing unit universal, the system eliminates the need for separate visual processing units or additional detection hardware, thereby reducing manufacturing costs while maintaining detection capability.
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
Enables real-time occlusion detection in LiDAR systems without affecting transmittance or increasing manufacturing costs, ensuring accurate detection and maintaining ranging accuracy.
Implementation Method 1
a transmitting unit configured to transmit a laser beam to a target to be measured and obtain a reflected signal from the target
Implementation Method 2
obtain distance information of each point in the echo data; comparing the distance information with a preset distance range
Data Source
AI summary
The present application discloses a LiDAR occlusion detection method and apparatus, a storage medium, and a LiDAR. The method includes: obtaining detected echo data, obtaining distance information of each point in the echo data, comparing the distance information with a preset distance range, and in response to the distance information being within the preset distance range, determining that the LiDAR is occluded. In the present application, it can be detected in real time whether the LiDAR is occluded, without affecting transmittance of the LiDAR or increasing manufacturing costs of the LiDAR.


