Acoustic Task Estimation for Transparent Object Handling

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Solution Overview

Problem

Existing techniques struggle to accurately identify and classify tasks involving highly transparent objects due to high transparency or minimal changes in refractive index or reflectance, leading to reduced accuracy in task estimation.

Innovation Solution

An estimation method that uses a computer to analyze task sounds collected during the task, inputting this data into a trained model to determine if a transparent object is being handled, thereby improving task estimation accuracy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If image capturing conditions are changed to improve object identification, then identification capability is improved, but for highly transparent objects with minimal refractive index or reflectance changes, identification accuracy deteriorates

Engineering Contradiction:

Improveobject identification accuracyVSAvoidtransparent object identification reliability

Core Design Contradiction:

Measurement precisionVSReliability

Solution Approach 1:

The patent replaces the optical-based image capturing system with an acoustic-based sound analysis system. Instead of relying on light reflection and refraction properties that fail for transparent objects, the system uses microphones to capture task sounds and analyzes acoustic features to identify transparent object handling tasks, substituting mechanical/optical detection with acoustic detection.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces sound as an intermediary medium to detect transparent object handling. Rather than directly observing transparent objects through imaging, the system uses task sounds produced during handling as an intermediary signal that correlates with transparent object manipulation, enabling indirect but reliable detection.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Productivity

If image-based methods are used to classify tasks, then task classification is achieved, but accuracy deteriorates when handling highly transparent objects

Engineering Contradiction:

Improvetask classification capabilityVSAvoidtask estimation accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The patent substitutes image-based task classification with sound-based task classification. By capturing and analyzing task sounds through microphones and processing them with machine learning models, the system achieves accurate task classification without relying on visual information that is insufficient for transparent objects.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent changes the detection parameter from optical properties (refractive index, reflectance) to acoustic properties (sound frequency, amplitude, temporal patterns). This parameter transformation enables the system to detect transparent object handling based on acoustic characteristics rather than optical characteristics, resolving the accuracy issue.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250111305A1Estimation method and estimation device

Publication Date: 2025.04.03 PANASONIC INTELLECTUAL PROPERTY CORP OF AMERICA

AI summary

An estimation method is an estimation method, performed by a computer, of estimating a task performed by a worker, and includes: obtaining data of a task sound that accompanies the task and that has been collected; and estimating whether the worker is performing a task in which a transparent object is handled, by inputting the data of the task sound into a first model that has been trained.