LiDAR Object Movement Detection Memory Optimization
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Solution Overview
Problem
Solid-state LiDAR systems face challenges in providing sufficient memory for calculating and storing histograms of time of flight data, which is crucial for generating accurate 3D environmental maps and detecting object movement, particularly in reducing memory usage while maintaining resolution for both close and distant objects.
Innovation Solution
The LiDAR system employs a controller to selectively record detected shots based on object distance, using a smaller subset for closer objects and a larger subset for farther objects, allowing for efficient memory usage by compressing data and determining object velocity, acceleration, and direction in one frame.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If histograms of time of flight data are calculated and stored for all detected shots, then accurate 3D environmental mapping and object movement detection are achieved, but memory requirements become excessively large
Solution Approach 1:
The patent segments the field of view into multiple depth ranges (e.g., near, mid, far zones) and processes detected shots differently based on their distance. For each depth range, separate histograms are calculated and stored with appropriate memory allocation. This segmentation allows the system to maintain high measurement precision for environmental mapping while significantly reducing total memory requirements by not uniformly storing all detected shots across the entire field of view.
Solution Approach 2:
The patent applies local quality by using different data processing strategies for different spatial regions. Close objects receive higher resolution processing with more detailed histogram storage, while distant objects use coarser processing with reduced memory allocation. This localized approach ensures that memory-critical regions (distant objects) are optimized without compromising the overall accuracy needed for safe autonomous operation.
2Quantity of substance
If a smaller subset of detected shots is recorded for closer objects, then memory usage is reduced, but resolution for close objects may be compromised
Solution Approach 1:
The patent implements dynamic memory allocation where the number of detected shots stored in histograms varies based on object distance. For close objects, a larger subset of shots is retained to maintain high resolution, while for distant objects, a smaller subset suffices. This dynamic approach adjusts memory usage in real-time based on spatial requirements, ensuring that close objects always receive adequate processing resources while optimizing overall system memory efficiency.
3Measurement precision
If a larger subset of detected shots is recorded for farther objects, then resolution for distant objects is improved, but memory requirements increase
Solution Approach 1:
The patent applies partial action by storing only a sufficient subset of detected shots for distant objects rather than all shots. Since distant objects inherently require less detail for safe detection and classification, storing a partial set of shots at reduced resolution is adequate for autonomous operation. This approach provides exactly enough measurement precision for distant objects without the excessive memory consumption that would result from storing complete high-resolution data for all ranges.
4Loss of information
If all detected shots are stored in memory, then complete environmental data is available, but data processing time and memory bandwidth increase
Solution Approach 1:
The patent extracts and stores only the essential features from detected shots in histogram form, rather than storing complete raw shot data. By converting time of flight measurements into binned histogram representations, the system retains the critical information needed for environmental mapping and object detection while dramatically reducing data volume. This extraction approach maintains sufficient environmental data completeness for autonomous operation while minimizing memory bandwidth requirements and processing time.
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 effectively reduces memory requirements while maintaining resolution for close objects and increasing it for distant objects, enabling accurate environmental mapping and object movement detection with reduced data storage needs.
Implementation Method 1
The time of flight of reflected photons detected by the photodetector is used to determine the distance of the object that reflected the light
Implementation Method 2
a photodetector, or an array of photodetectors, that is fixed in place relative to a carrier... Light is emitted into the field of view of the photodetector and the photodetector detects light that is reflected by an object
Data Source
AI summary
A LiDAR system includes alight emitter, a light detector, and a controller. The controller is programmed to: activate the light emitter to emit a series of shots into a field of view of the light detector; activate the light detector to detect shots reflected from an object in the field of view; record the detected shots from a first subset of the series of shots; group a second subset of the series of shots not in the first subset; and based on the detected shots from the second subset of the series of shots, identify an object moving in the field of view