Selective LiDAR Mapping Using Passive-Guided Laser Scanning
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Solution Overview
Problem
Existing LiDar-based systems for generating 3D-maps in autonomous vehicles are costly, hazardous due to high-energy laser beams, and lack granularity in resolution, making mass production infeasible and posing risks to pedestrians.
Innovation Solution
An apparatus using an active sensor with a static light directing circuit and a passive sensor to perform selective laser measurements, combined with image processing to generate high-resolution 3D-maps by focusing on suspicious and moving objects, reducing the number of laser beams and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LiDar systems transmit high-energy laser beams to measure maximum range, then measurement precision is improved, but harmful factors to pedestrians and passengers increase
Solution Approach 1:
The system applies different energy levels to different spatial regions by using selective scanning. High-energy beams are directed only at suspicious or moving objects that require detailed measurement, while low-energy or no beams are used in safe zones. This spatial differentiation of energy quality resolves the contradiction between achieving precise measurements and minimizing harm to pedestrians.
Solution Approach 2:
The system dynamically changes the energy parameter of laser beams based on real-time scene analysis. By adjusting beam energy levels according to object classification (suspicious vs. static), the system achieves high measurement precision for critical objects while reducing harmful effects in safe areas, thus resolving the contradiction.
2Measurement precision
If LiDar systems scan the entire scene with multiple laser beams, then measurement completeness is improved, but device complexity and cost increase
Solution Approach 1:
The system segments the scene into different regions of interest based on image processing results. Instead of uniformly scanning the entire scene, the LiDar system focuses measurements only on suspicious or moving objects identified by the image processor. This segmentation approach maintains measurement completeness for critical areas while significantly reducing the number of beams required, thereby lowering device complexity.
Solution Approach 2:
The system performs partial scanning by selectively measuring only the portions of the scene that contain suspicious or moving objects. This partial action approach achieves sufficient measurement completeness for autonomous driving decisions without requiring exhaustive scanning of the entire scene, thus reducing device complexity and beam count.
3Measurement precision
If LiDar systems use a large number of laser beams to render detailed 3D-maps, then measurement precision is improved, but energy consumption increases
Solution Approach 1:
The system applies high measurement density (multiple beams) only to local regions containing suspicious or moving objects where detailed 3D mapping is critical. In safe regions with static objects, the system uses fewer beams or lower resolution scanning. This local differentiation maintains high measurement precision for critical areas while significantly reducing overall energy consumption.
Solution Approach 2:
The system dynamically changes the beam density parameter based on scene content analysis. By adjusting the number of beams directed at different objects according to their classification (suspicious vs. static), the system achieves high detail resolution for critical objects while minimizing energy consumption through reduced beam counts in safe areas.
4Productivity
If LiDar systems transmit numerous laser beams simultaneously, then productivity of scene scanning is improved, but harmful factors and energy consumption increase
Solution Approach 1:
The system achieves high scanning productivity by concentrating multiple beams on suspicious or moving objects that require rapid detailed assessment, while using minimal or no beams in safe zones. This spatial differentiation maintains fast scanning speed for critical areas while reducing the total number of beams transmitted, thereby minimizing harmful effects.
Solution Approach 2:
The system dynamically adjusts the beam count parameter based on real-time scene analysis. By transmitting a high number of beams only when and where needed (at suspicious objects), and reducing beam count in safe areas, the system maintains high scanning productivity for critical detection while reducing overall harmful exposure and energy consumption.
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 cost-effective, safer, and higher-resolution 3D-map generation, minimizing hazardous conditions and enabling widespread adoption of autonomous vehicles.
Implementation Method 1
at least one receiver configured to detect light pulses reflected from the at least one target object
Implementation Method 2
a distance measurement circuit configured to measure a distance to each of the at least one target object based on the emitted light pulses and the detected light pulses
Data Source
AI summary
An active sensor for performing active measurements of a scene is presented. The active sensor includes at least one transmitter configured to emit light pulses toward at least one target object in the scene, wherein the at least one target object is recognized in an image acquired by a passive sensor; at least one receiver configured to detect light pulses reflected from the at least one target object; a controller configured to control an energy level, a direction, and a timing of each light pulse emitted by the transmitter, wherein the controller is further configured to control at least the direction for detecting each of the reflected light pulses; and a distance measurement circuit configured to measure a distance to each of the at least one target object based on the emitted light pulses and the detected light pulses.