Object Detection With Attitude-Adaptive Velocity Filtering
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Solution Overview
Problem
Existing object detection systems face challenges in accuracy due to individual differences among detectors and environmental disturbances, leading to detection errors.
Innovation Solution
An object detection device that utilizes a combination of cameras, millimeter-wave radar, and Lidar to acquire an object's attitude and velocity, employing filters with varying smoothing levels based on the object's attitude to improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single filter with fixed smoothing level is applied to velocity detection, then the device complexity is low, but the measurement precision deteriorates due to inability to adapt to different object attitudes
Solution Approach 1:
The filter processing unit dynamically adjusts the filter type and smoothing level based on the detected attitude of the target object. When the object is detected at an oblique angle, a filter with higher smoothing level is applied; when detected at a standard angle, a filter with lower smoothing level is used. This dynamic adaptation resolves the contradiction by making the system flexible rather than fixed, improving measurement precision without requiring multiple permanent filter configurations.
Solution Approach 2:
The system changes the filter parameters (smoothing level) based on the object's attitude parameters. By monitoring the attitude detection results and adjusting the filter characteristics accordingly, the system optimizes velocity detection accuracy for different object orientations while maintaining a single filter processing unit, thus resolving the contradiction between precision and complexity.
2Reliability
If detector individuality and environmental disturbances are not addressed, then the device complexity remains low, but the reliability of detection deteriorates due to errors
Solution Approach 1:
The filter processing unit uses feedback from the attitude detection results to adjust the filtering applied to velocity data. By continuously monitoring object attitude and adapting the filter characteristics in response, the system compensates for detection errors caused by individual detector variations and environmental disturbances, thereby improving reliability without requiring additional hardware.
Data Source
AI summary
An object detection device is provided. The object detection device includes an acquisition unit that uses a detection result concerning a target object to acquire an attitude and a velocity of the target object, and a filter processing unit that sets a filter applied to the velocity depending on the acquired attitude of the target object to perform filter processing.