Obstacle Detection Using Planar Sensor Geo-Referencing
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Solution Overview
Problem
Existing obstacle detection systems for vehicles face challenges in distinguishing sensor returns from terrain features as legitimate obstacles, especially in uneven terrain, leading to false detections and reduced accuracy in collision avoidance.
Innovation Solution
A computer-implemented method and system that uses planar sensors like LIDAR or RADAR to transform sensor data from a sensor-relative representation to a geo-referenced representation, analyzing changes in vehicle pitch and roll to classify obstacles, and employing correlation algorithms to filter out ground clutter, thereby improving detection accuracy and reducing false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor data is processed using traditional obstacle detection methods, then detection speed is maintained, but false detections increase due to inability to distinguish terrain features from legitimate obstacles
Solution Approach 1:
The patent transforms obstacle candidate profiles from sensor-relative representation to geo-referenced representation, adding a spatial dimension (geo-referenced coordinate system) to the data processing. This dimensional transformation enables the system to distinguish between terrain features and legitimate obstacles by comparing their positions in the geo-referenced frame across multiple frames, thereby improving detection accuracy without excessively increasing processing complexity
Solution Approach 2:
The patent performs preliminary transformation of obstacle candidate profiles from sensor-relative to geo-referenced representation before conducting obstacle detection. By pre-processing the data in this manner, the system establishes a consistent spatial reference frame that facilitates accurate obstacle identification and reduces false detections caused by terrain variations
2Reliability
If traditional obstacle detection methods are used, then processing speed is maintained, but false alarms increase due to terrain feature misclassification
Solution Approach 1:
The patent segments the obstacle detection process into distinct stages: (1) receiving sensor data and identifying obstacle candidate profiles, (2) transforming profiles from sensor-relative to geo-referenced representation, (3) comparing profiles across multiple frames, and (4) detecting obstacles based on coincidence. This segmentation allows the system to process data efficiently at each stage while improving overall accuracy through the geo-referenced comparison mechanism
3Ease of operation
If sensor data is analyzed without geo-referenced transformation, then processing simplicity is maintained, but detection reliability decreases in uneven terrain
Solution Approach 1:
The patent introduces geo-referenced representation as an intermediary coordinate system between the sensor-relative data and the final obstacle detection decision. This intermediary transformation provides a stable spatial reference that mediates the comparison of obstacle candidates across multiple frames, enabling reliable detection in uneven terrain while maintaining relatively simple processing through standardized transformation algorithms
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
The system effectively detects obstacles by differentiating between obstacles and terrain features, enhancing collision avoidance capabilities in various terrains and reducing false alarms, thereby improving vehicle safety and operational reliability.
Implementation Method 1
The system uses sensors having a primarily planar field-of-view (such as a LIDAR (Light Detection and Ranging or Laser Imaging Detection and Ranging)
Implementation Method 2
The system uses sensors having a primarily planar field-of-view (such as a LIDAR (Light Detection and Ranging or Laser Imaging Detection and Ranging) or RADAR (RADAR (Adio Detection And Ranging))
Data Source
AI summary
A computer-implemented method and system for automatically detecting an obstacle from a moving vehicle using a planar sensor mounted on the vehicle.