Simultaneous In-Hand Shape and Temperature Recognition Using Flexible Multilayered Sensor Arrays for Sense-Based Robot Manipulation

Seong-Min Im, Byeong-Sun Park, Jaehwan Jang, Sungeun Hong, Changjoo Nam, Young Tack Lee, Min-gu Kim
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Abstract

Artificial tactile systems play a pivotal role in advancing human-machine interaction technology by enabling precise physical interaction with objects and environments. Tactile information, such as pressure and temperature, allows robots to manipulate objects accurately and interact safely with humans. To facilitate this, a robotic skin integrating flexible pressure and temperature sensor arrays has been developed. The capacitive pressure sensor, inspired by human skin and utilizing a micro-dome structure, demonstrates fast, stable, and sensitive performance under applied pressure. Also, the resistive temperature sensor, based on reduced graphene oxide, exhibits highly sensitive responses to temperature changes, characterized by rapid and linear behavior. These sensors are vertically integrated into a multilayered system capable of simultaneously detecting real-time pressure and temperature distribution. This integrated sensor system, when incorporated into a robotic gripper, enables accurate identification of object shapes and surface temperatures during manipulation tasks. By pairing the sensor system with a camera that captures macroscopic visual information, including areas not directly visible, robots achieve enhanced manipulation capabilities through the synergy of visual context and detailed tactile input. This development represents a fundamental technology for multimodal tactile recognition and highlights its potential applications in artificial intelligence-driven visual-tactile fusion technologies.

Abstract Image

基于传感机器人操作的柔性多层传感器阵列手部形状和温度同时识别
人工触觉系统通过实现与物体和环境的精确物理交互,在推进人机交互技术方面发挥着关键作用。触觉信息,如压力和温度,使机器人能够准确地操纵物体,并安全地与人类互动。为了实现这一点,一种集成柔性压力和温度传感器阵列的机器人皮肤已经开发出来。电容式压力传感器的设计灵感来自人体皮肤,利用微圆顶结构,在施加压力下表现出快速、稳定和敏感的性能。此外,基于还原氧化石墨烯的电阻式温度传感器对温度变化表现出高度敏感的响应,具有快速和线性的特征。这些传感器垂直集成到一个多层系统中,能够同时检测实时压力和温度分布。这种集成的传感器系统,当被集成到一个机器人抓手中时,可以在操作任务中准确识别物体形状和表面温度。通过将传感器系统与捕捉宏观视觉信息(包括不直接可见的区域)的摄像头配对,机器人通过视觉环境和详细触觉输入的协同作用增强了操作能力。这一进展代表了多模态触觉识别的基础技术,并突出了其在人工智能驱动的视触觉融合技术中的潜在应用。
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