# Artificial Tactile Perception System for Exploring Internal and External Features of Objects via Time‐Frequency Features

## TL;DR

A new tactile perception system helps robots sense both the outside and inside of objects using time-frequency signal analysis.

## Contribution

A flexible piezoelectric tactile sensor with active perception that improves robotic object recognition through distinct signal modes.

## Key findings

- The tactile system achieves high force sensitivity and wide frequency response for detailed object sensing.
- Sliding and vibration motions enable extraction of external edges and internal content via time and frequency domain analysis.
- The device successfully performs texture recognition and liquid identification on a robotic hand.

## Abstract

Perceiving both external and internal object features is essential for accurate recognition and manipulation of humans and robots. However, relying on a single signal processing paradigm may hinder the extraction of specific tactile information from structurally similar signals, posing challenges in both accuracy and computational efficiency in artificial tactile perception systems. Active contact offers a means to modulate the mechanical interaction between tactile systems and objects, enabling targeted perception of specific properties. This work presents a flexible piezoelectric tactile sensing device with active perception capability. It exhibits high force sensitivity (<0.02 N), multi‐axis responsiveness, a wide frequency response range (upper than 2000 Hz), and high spectral resolution (<1 Hz). With two distinct active exploration motions (sliding and vibration), the system extracts edge features through time‐domain spike characteristics and infers internal contents via frequency‐domain decay trends. The device is integrated on the fingertip of a robotic dexterous hand, demonstrating its effectiveness in tasks such as texture recognition and liquid identification. It also shows promise for handling complex interaction tasks involving multiple subtasks. This study contributes to the advancement of tactile interaction paradigms in robotics and provides a foundation for more intuitive and adaptable robotic perception in human‐centered environments.

By engaging in different active exploration behaviors, the tactile perception system can generate distinct signal modes, enabling the application of targeted decoding strategies for efficient and accurate perception of both external and internal object features. This approach facilitates a more advanced robotic understanding of human‐centered environments and supports learning‐based object recognition and manipulation.