Mechanical quantity sensor and robot having the same, method for sensing a mechanical quantity and method for manufacturing a mechanical quantity sensor

JP7876836B2Active Publication Date: 2026-06-22NAT UNIV CORP KYUSHU INST OF TECH (JP)
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Patent Information

Application Number
JP2022071679
Authority / Receiving Office
JP · JP
Patent Type
Patents
Current Assignee / Owner
Filing Date
2022-04-25
Publication Date
2026-06-22
Estimated Expiration
2042-04-25

AI Technical Summary

Technical Problem

Conventional mechanical force sensors are unable to accurately detect the location of applied forces, necessitating numerous tiny sensors on artificial skin, which is economically impractical and limits miniaturization.

Method used

A mechanical quantity sensor utilizing an electrical conductor that elastically deforms and changes resistance, combined with input and output electrodes and a calculation unit employing machine learning to determine the force application location, allowing precise detection without a dense array of sensors.

Benefits of technology

The sensor can pinpoint the location and magnitude of applied forces using machine learning, enabling miniaturization and cost-effective implementation on artificial skin.

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Patent Text Reader

Abstract

To provide a dynamic quantity sensor, a robot having the same, and a dynamic quantity sensing method, capable of detecting a position of an elastic body applied with force.SOLUTION: A dynamic quantity sensor 10 that detects a magnitude of applied force, includes an electrical conductor 11 that is elastically deformed by application of the force to cause electric resistance characteristics to be changed, an input electrode that applies a voltage to the electrical conductor 11, a plurality of output electrodes that take out electric signals from different portions of the electrical conductor 11 being applied with the voltage, respectively, and an arithmetic unit 13 that derives a position of the elastically deformed portion of the electrical conductor 11 being applied with the force by machine learning using a plurality of electric signals taken out from the respective output electrodes as an input value.SELECTED DRAWING: Figure 1
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Citation Information

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