3D Camera Radar Fusion for Object Detection Reliability
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Solution Overview
Problem
3D cameras in vehicles face challenges in detecting objects with varying reflectivity and distinguishing between hard and soft objects, leading to potential errors in object detection and classification, which can be critical in emergency situations.
Innovation Solution
The integration of a 3D camera with a radar system, where the 3D camera collects and interprets measurement data, and the radar provides supplementary information to enhance object detection and classification, allowing for adjustments in sensor settings to improve detection accuracy and reduce errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a 3D camera is used to detect objects, then object detection capability is provided, but detection reliability deteriorates when objects have varying light reflectivity
Solution Approach 1:
The patent combines a 3D camera and a radar into an integrated detection system. The 3D camera captures visual information and distance data, while the radar provides complementary detection capabilities, especially for objects with varying reflectivity. By merging the detection results from both sensors, the system achieves more reliable and accurate object detection and classification.
2Reliability
If a 3D camera is used to detect objects, then detection is provided, but object classification accuracy deteriorates between hard and soft objects
Solution Approach 1:
The patent integrates detection data from both 3D camera and radar to classify objects as hard or soft. The radar's ability to detect hard objects (vehicles, barriers) complements the 3D camera's visual recognition of soft objects (pedestrians, animals). By combining these different detection modalities, the system achieves accurate object classification that neither sensor could achieve alone.
3Reliability
If a 3D camera is used to detect objects, then detection speed is provided, but detection accuracy deteriorates in emergency situations
Solution Approach 1:
The integrated system performs preliminary detection and classification using both 3D camera and radar simultaneously. By having both sensors operating in parallel and pre-processing their data, the system can quickly classify objects as hard or soft before emergency maneuvers are required, ensuring both speed and accuracy in critical situations.
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 integration enhances the reliability and speed of object detection, enabling earlier warnings and safer responses, such as evasive maneuvers or airbag deployment, by distinguishing between hard and soft objects and improving detection in areas with varying reflectivity.
Implementation Method 1
The 3D camera can determine distances to objects by emitting a modulated lightwave, detecting a corresponding reflected lightwave from the object and measuring the shift of the reflected lightwave in relation to the emitted lightwave
Implementation Method 2
reception of measurement data related to the area, from the radar
Data Source
Figure 1A~1D
Figure 2A~2B
Figure 3
AI summary
A method (400) and a 3D camera (110) for a vehicle for detecting an object (130) in an area (140). The method (400) comprises the collection (401 ) of measurement data related to the area (140) by means of a sensor (310) in the 3D camera (110) using a first sensor setting, reception (402) of measurement data related to the area (140) from a radar (120), and detection (405) of the object (130) based on the interpretation of collected (401) measurement data together with measurement data received (402) from the radar (120).