Tactile Surface Texture Characterization Using Continuous Transfer Function
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Solution Overview
Problem
Existing methods for tactile characterization of surface textures fail to provide quantitative characterization of tactile characteristics like softness or tackiness and do not establish relationships between different classes, limiting their precision and applicability.
Innovation Solution
A method using a triaxial force sensor with a soft coating, involving a two-step process: learning a calculation algorithm from pre-characterized samples to construct a continuous transfer function, and applying this function to deduce tactile characteristics of new surfaces, allowing for continuous characterization of surfaces using tactile or mechanical descriptors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a triaxial force sensor is used to measure tactile characteristics, then measurement precision is improved, but device complexity increases due to the need for soft coating and continuous transfer function construction
Solution Approach 1:
A soft coating is introduced as an intermediary between the triaxial force sensor and the surface being measured. This coating allows the sensor to gently contact various surface types without damage, enabling precise tactile measurements across different materials while managing the complexity through a standardized intermediate layer
Solution Approach 2:
The patent transforms discrete tactile classifications into continuous parameter measurements by constructing a continuous transfer function. This function maps force sensor readings to continuous tactile descriptor values, enabling precise quantification of tactile characteristics like softness and roughness without being limited to discrete categories
2Device complexity
If discrete classification methods are used to categorize textures, then device complexity is reduced, but measurement precision deteriorates as only categorical values are obtained
Solution Approach 1:
The patent transitions from discrete categorical classification to continuous parameter measurement by implementing a continuous transfer function. This function converts force sensor readings into continuous tactile descriptor values, allowing precise quantification of tactile properties such as softness, roughness, and tackiness rather than limiting measurements to discrete categories
Solution Approach 2:
The patent adds a dimensional transformation by mapping force measurements to a continuous space of tactile descriptors. This dimensional change enables the system to represent tactile characteristics with infinite precision within the continuous range, rather than being constrained to discrete classification levels
3Device complexity
If existing force sensors are used directly, then device complexity is minimized, but measurement precision deteriorates due to inability to mimic human tactile appreciation
Solution Approach 1:
The patent transforms raw force sensor data into human-like tactile perceptions by applying a continuous transfer function that maps mechanical forces to tactile descriptors. This parameter transformation enables the sensor system to characterize surfaces in a way that mirrors human tactile appreciation, capturing nuances such as softness, roughness, and texture
Solution Approach 2:
The patent replaces direct mechanical measurement with a transformed perception system. By substituting raw force data with processed tactile descriptors through the continuous transfer function, the system achieves human-like tactile characterization while maintaining relatively simple hardware architecture
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
Enables precise characterization of surface textures with continuous values for tactile descriptors, closely mimicking human tactile appreciation, and can be applied to various industries and non-flat surfaces, including fluids, with potential for use in robotics and biomimetics.
Implementation Method 1
uses a force sensor, for example triaxial
Implementation Method 2
force sensor, for example triaxial, protected by a soft coating
Data Source
Figure 1~2
Figure 3
AI summary
Tactile surface texture characterization method comprising at least the following steps: at least one force perceived by a force sensor during a relative displacement of said sensor with respect to a surface to be characterized is measured (211); one or more time and/or frequency parameters of an output signal delivered by said sensor, representative of the previously measured force, are calculated (213); and the value of a tactile descriptor is determined (215) from a plurality of tactile descriptors by applying a calculated transfer function, the transfer function being determined beforehand by regression from a learning database associating, for each descriptor, several values of the tactile descriptor in question with several values of one or more time and/or frequency parameters calculated from measurements carried out by the force sensor on several test surfaces representative of values of the tactile descriptor in question.