Bi-modal Point Cloud Visualization for 4D LIDAR Hazard Avoidance
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Solution Overview
Problem
Current methods for visualizing point cloud data from LIDAR systems lack the ability to utilize multi-color compositions in real-time for 4D applications, particularly for hazard avoidance without prior position information, and fail to effectively display time sequences of point clouds.
Innovation Solution
A bi-modal coloring method and system that divides point cloud data into zones based on range and height, using two separate color compositions to visualize point clouds in real-time, with one composition indicating hazards or vertical obstructions and the other representing height variations, employing RGB or HSI color spaces and calculating color indices based on distance and altitude.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a single color composition is used to color point clouds based on height, then the visualization is simple, but the ability to distinguish hazards and provide real-time situational awareness is insufficient
Solution Approach 1:
The patent divides the point cloud data into multiple zones based on range intervals, with each zone assigned a specific color composition. Close objects within a threshold range use a first color composition (e.g., red/yellow) to indicate hazards, while distant objects use a second color composition (e.g., green/blue) for normal terrain representation. This segmentation allows simultaneous display of hazard information and height information without overwhelming complexity.
Solution Approach 2:
Different regions of the point cloud are assigned different color compositions based on their range from the sensor. The coloring is not uniform but varies locally according to the object's distance and significance. This allows the visualization to provide context-appropriate information: hazard warnings for close objects and topographical information for distant objects.
2Reliability
If multi-color compositions are used for real-time 4D point cloud visualization, then hazard avoidance capability is improved, but the processing complexity and computational load increase
Solution Approach 1:
The system pre-calculates range intervals and establishes threshold values for hazard detection before processing the point cloud data. The zones are defined in advance based on expected hazard distances, and the color compositions are pre-assigned to each zone. This preliminary setup reduces real-time computational complexity while maintaining reliable hazard detection capability.
Solution Approach 2:
The patent changes the parameter of color composition based on the range parameter of points. By using range as a key parameter to determine which color composition to apply, the system efficiently categorizes points into hazard zones or normal zones. This parameter-based approach simplifies the decision-making process in real-time visualization.
3Measurement precision
If point cloud data is colored based on height only, then the visualization method is simple, but the distinction between close and distant objects is insufficient for safety-critical applications
Solution Approach 1:
The patent adds a range dimension to the traditional height-based coloring approach. Instead of using only the z-coordinate (height) for color assignment, the system incorporates the range (distance from sensor) as an additional dimension. This creates a bi-modal coloring system where both height and range influence the final color, enabling precise distinction between close and distant objects while maintaining operational simplicity through automated zone-based assignment.
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 visualization of point clouds for hazard avoidance and situational awareness, improving pilot decision-making in obscured conditions by clearly distinguishing close objects from more distant ones, enhancing safety in aerial operations.
Implementation Method 1
These systems are capable of operating in the same way as a video camera operates, at 30 frames per second
Implementation Method 2
receiving point cloud data, including range data between a range sensor and multiple points in the point cloud
Data Source
AI summary
A system is provided for alerting a crew in an airborne platform. The system includes a module for receiving point cloud data from a LIDAR system, including range data between the LIDAR system and multiple points in the point cloud. The system also includes a module for placing the multiple points into first and second zones, wherein the first zone has range data of points in the point cloud located within a first distance from the airborne platform, and the second zone has range data of points located further than the first distance. The first distance is predetermined by an operational environment of the airborne platform. The system further includes a color module for coloring the points in the first zone with a first color composition and coloring the points in the second zone with a second color composition. A color display is provided for displaying the colored points in the first and second zones.