Image-Based Center-of-Gravity Detection for Driving Control
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Solution Overview
Problem
Existing control systems for driving devices often require complex calculations and high-performance sensors to detect objects, making them unreliable and difficult to configure.
Innovation Solution
An information processing device that uses machine learning to detect objects from captured images, specifically identifying the position of the center of gravity, to simplify control configurations and improve reliability by controlling driving devices based on these detection results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-performance sensors and complicated calculations are used to detect objects, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex sensor systems and calculation-based detection with a machine learning model that directly processes captured images to detect objects and their center of gravity positions. The detection unit uses a trained neural network to output detection results without requiring complex sensor arrays or post-processing calculations, thus substituting mechanical/sensor-based detection with an intelligent processing approach.
Solution Approach 2:
The patent changes the detection approach from using multiple sensor parameters requiring complex integration to using a single captured image as input to the machine learning model. The model internally processes the image data and outputs object position and center of gravity information, effectively changing the input parameter structure to simplify the overall detection system.
2Measurement precision
If high-performance sensors and complicated calculations are used to detect objects, then measurement precision is improved, but reliability deteriorates
Solution Approach 1:
The patent replaces sensor-based detection systems with machine learning-based image processing. By using a trained neural network model that has learned to identify objects and their center of gravity from images, the system achieves reliable detection without the variability and failure modes associated with complex sensor systems and calculation algorithms.
Data Source
AI summary
In order to simplify the control configuration for controlling a driving device and improve reliability of the operation of the driving device, an information processing device includes a detection unit and a processing unit. The detection unit detects the detection target from a captured image by using reference data that is a learning result obtained by machine learning of the detection target including the position of the center of gravity of the object in the captured image. The processing unit controls the driving device to be controlled that acts on the object having the center of gravity detected by the detection unit, by using the detection result of the detection unit.