LiDAR-Camera Signal Format Conversion for Robust Distance Measurement
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Solution Overview
Problem
Existing distance measurement technologies face challenges in combining signals from different formats, such as LiDAR and stereo cameras, leading to inconsistent performance across various scenes and environments, requiring human intervention to set logic for signal combination.
Innovation Solution
A distance measuring apparatus that uses machine learning to combine signals from different formats by converting the format of LiDAR signals to match that of camera signals, allowing a neural network to learn the correspondence between input data and output distance information without human-set logic, thereby achieving robust distance measurement across various scenes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If LiDAR and stereo camera signals are combined using traditional fusion methods, then distance measurement precision is improved, but the system requires human intervention to set logic for signal combination, reducing adaptability
Solution Approach 1:
The system employs a neural network that automatically learns and determines the optimal logic for combining LiDAR and stereo camera signals without requiring human intervention. The neural network processes the multi-format signals and autonomously generates distance information, enabling the system to adapt to various scenes and environments independently.
2Ease of manufacture
If signals in different formats are combined without format conversion, then device complexity is reduced, but the neural network cannot effectively learn correspondence between input data and output distance information
Solution Approach 1:
The patent introduces a signal conversion unit as an intermediary component that transforms LiDAR signals into a format compatible with stereo camera data. This conversion enables the neural network to effectively process and learn from the combined signals while preserving the essential distance measurement information from both sources.
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 apparatus provides highly robust and precise distance measurement by extracting feature values that exceed human-set logic, enabling consistent performance across diverse scenes and environments without requiring human intervention in logic setting.
Implementation Method 1
the distance to an object is calculated based on the length of time it takes from a point in time when a laser beam is emitted to an object until a point in time when a reflected signal returns from the object
Data Source
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AI summary
A distance measuring apparatus (100) includes a signal conversion unit (22) to match a format of a second signal relating to a distance to an object with a format of a first signal relating to an image; and a distance information output unit (24) to output distance information based on the first signal and the second signal having the format matched with the format of the first signal. The signal conversion unit (22) converts the second signal such that, among length information in directions of a plurality of dimensions held in the first signal and length information in directions of a plurality of dimensions held in the second signal, length information in a direction of at least one of the plurality of dimensions of the first signal represents length information in a direction of at least one of the plurality of dimensions of the second signal.