Hybrid Ground Clearance Detection Using Radar and Camera Fusion
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Solution Overview
Problem
Existing systems fail to accurately determine the ground clearance of horizontal structures over a path of travel, particularly for vehicles with trailers, as the height of the trailer may exceed the vehicle, and existing sensors like ultrasonic and radar sensors do not reliably provide sufficient information to prevent collisions with low-clearance structures.
Innovation Solution
A method and apparatus using a combination of image information from a camera and radar information to detect ground clearance by removing noise from radar reflection points, extracting visual features with a convolutional neural network, projecting radar points onto images, generating region proposals, and determining the distance to stationary horizontal structures, thereby distinguishing between moving and stationary objects and calculating the necessary clearance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If ultrasonic sensors or radar sensors are used to detect ground clearance, then the detection range is extended, but the measurement precision deteriorates due to noise and inability to distinguish moving from stationary objects
Solution Approach 1:
The patent combines radar sensor data with camera image data to create a hybrid detection system. The radar provides long-range detection capability while the camera provides precise visual information for verifying object presence and distinguishing stationary structures from moving objects, thereby resolving the contradiction between extended detection range and measurement precision
Solution Approach 2:
The camera acts as an intermediary verification tool for the radar detection system. When radar detects potential obstacles, the camera captures images to confirm whether they are stationary horizontal structures or moving objects, eliminating false positives and improving measurement accuracy without sacrificing detection range
2Area of stationary object
If radar reflection points are used to detect horizontal structures, then the detection area is expanded, but the reliability deteriorates due to noise from moving objects
Solution Approach 1:
The system extracts and removes noisy reflection points from moving objects by comparing radar data across multiple time points. Reflection points that appear transiently or move with the vehicle are identified and eliminated, retaining only stable reflection points from stationary horizontal structures, thereby improving detection reliability while maintaining expanded detection area
Solution Approach 2:
The system performs preliminary noise filtering by analyzing radar reflection points across multiple time points before final detection. Objects detected at a threshold number of consecutive time points are identified as potential stationary structures, while transient reflections are discarded, improving reliability before the final detection decision
3Measurement precision
If a combination of camera and radar is used, then the measurement precision is improved, but the device complexity increases
Solution Approach 1:
The camera serves multiple functions: it verifies radar-detected objects, distinguishes stationary structures from moving objects, and provides visual confirmation for ground clearance measurement. This multi-functionality justifies the added complexity by delivering superior measurement precision through a single additional sensor rather than requiring multiple specialized sensors
Solution Approach 2:
The camera acts as an intermediary verification layer that processes radar data, reducing false positives and improving reliability. By using the camera to confirm radar detections rather than relying solely on radar, the system achieves higher measurement precision with manageable complexity through intelligent data fusion
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 determines the ground clearance, enabling vehicles to safely navigate under horizontal structures by accurately differentiating between moving and stationary objects and providing reliable distance measurements, thus preventing potential collisions.
Implementation Method 1
receiving the first reflection point information from a radar configured emit radio waves at an area and generate the first reflection point information of the area based on the emitted radio waves
Implementation Method 2
receiving the image from a camera configured to capture an image of the area
Data Source
AI summary
A method and apparatus for determining ground clearance of a structure are provided. The method includes removing reflection points caused by noise from first reflection point information based on temporal persistency and generating second reflection point information, extracting visual features from an image of a camera based on convolutional neural network, projecting the second reflection point information onto the image, generating region proposals based on the projected second reflection point information and the image, the region proposals indicating potential horizontal structures above a path, detecting stationary horizontal structure above a path based on the generated region proposals, and determining distance between ground and the detected stationary horizontal structure based on the projected reflection point information and the image.