LIDAR Translucent Matter Detection via Secondary Return Distance Difference
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Solution Overview
Problem
Existing LIDAR sensors struggle to detect translucent matters such as vapor, steam, and fog due to weak light reflections, which can hinder the perception and navigation of autonomous vehicles in inclement weather conditions.
Innovation Solution
The system utilizes secondary returns from LIDAR or TOF sensors to determine the presence of translucent matters by calculating the distance difference between primary and secondary returns and comparing it to a threshold, allowing for improved detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LIDAR sensors use primary returns for detection, then detection speed is maintained, but detection accuracy of translucent matters deteriorates due to weak light reflections
Solution Approach 1:
The system performs preliminary detection using primary returns to identify potential translucent matter regions, then pre-processes and enhances the corresponding secondary return signals before final classification. This preliminary action allows the system to focus computational resources on relevant regions, improving detection accuracy while maintaining overall system speed.
Solution Approach 2:
The patent introduces secondary returns as an intermediary detection mechanism. Instead of relying solely on weak primary reflections from translucent matter, the system uses secondary returns (light reflected from objects behind the translucent matter) as a mediator to indirectly detect the presence of translucent matter. This intermediary approach converts the weak direct reflection problem into a stronger indirect detection signal.
2Reliability
If LIDAR sensors increase laser power to improve translucent matter detection, then detection capability improves, but energy consumption increases
Solution Approach 1:
The system applies partial action by selectively increasing laser power only in directions and time periods where translucent matter is suspected, rather than continuously increasing power across all operations. The processor identifies regions with characteristics suggestive of translucent matter and directs enhanced detection resources only to those specific regions, achieving improved detection capability while minimizing overall energy consumption.
Solution Approach 2:
The system dynamically changes laser parameters (power, pulse duration, frequency) based on detected conditions. When translucent matter is detected or suspected in a particular direction, the system adjusts laser parameters for subsequent pulses in that direction to optimize detection. This parameter adaptation allows the system to maintain high detection capability when needed while consuming minimal energy during normal operation.
3Measurement precision
If LIDAR sensors process only primary returns, then processing speed is maintained, but detection completeness deteriorates for translucent matters
Solution Approach 1:
The detection process is segmented into distinct stages: primary return processing for initial scene understanding, secondary return processing for translucent matter detection, and integrated classification. Each stage processes specific types of data with appropriate algorithms, avoiding the need to process all data through all stages. This segmentation improves detection completeness while managing processing complexity through staged analysis.
Solution Approach 2:
The system performs partial processing of secondary returns by focusing computational effort only on regions where translucent matter is suspected based on primary return analysis. Instead of processing all secondary returns with full complexity, the system applies simplified processing to most regions and enhanced processing only to relevant regions, achieving detection completeness while controlling overall processing 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 enhances the detection accuracy of translucent matters, thereby improving the perception and navigation systems of autonomous vehicles, especially in adverse weather conditions.
Implementation Method 1
a primary return comprising a first portion of the light-based ranging sensor beam reflected from a matter along a first path of the first portion of the light-based ranging sensor beam
Implementation Method 2
measuring the time for light reflected from the surface to return to the LIDAR
Data Source
AI summary
Systems and techniques are provided for detecting a translucent matter based on light detection and ranging (LIDAR) returns. An example method can include receiving at least two LIDAR returns associated with a LIDAR beam transmitted by a LIDAR device. The two LIDAR returns include a primary return comprising a first portion of the LIDAR beam reflected from a matter and a secondary return comprising a second portion of the LIDAR beam reflected from additional matter. The example method can further include determining a distance difference between a first position of the matter along the first path and a second position of the additional matter along the second path, comparing the distance difference with a threshold, and based on the comparison between the distance difference and the threshold, determining whether the additional matter is a non-translucent matter or a translucent matter.