Issue

Vol. 16 (2024)

Design of AI-Enhanced and Hardware-Supported Multimodal E-Skin for Environmental Object Recognition and Wireless Toxic Gas Alarm

https://doi.org/10.1007/s40820-024-01466-6
Jianye Li
State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China
Hao Wang
State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China
Yibing Luo
State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China
Zijing Zhou
State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China
He Zhang
Guangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced Manufacturing, Guangzhou 510641, People’s Republic of China
Huizhi Chen
Guangdong Provincial Key Laboratory of Research and Development of Natural Drugs and School of Pharmacy, Guangdong Medical University, Dongguan 523808, People’s Republic of China
Kai Tao
Ministry of Education Key Laboratory of Micro and Nano Systems for Aerospace, School of Mechanical Engineering, Northwestern Polytechnical University, Xi’an 710072, People’s Republic of China
Chuan Liu
State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China
Lingxing Zeng
Engineering Research Center of Polymer Green Recycling of Ministry of Education, College of Environment and Resources, Fujian Normal University, Fuzhou 350007, People’s Republic of China
Fengwei Huo
The Institute of Flexible Electronics (IFE, Future Technologies), Xiamen University, Xiamen 361005, People’s Republic of China
Jin Wu
State Key Laboratory of Optoelectronic Materials and Technologies and the Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou 510275, People’s Republic of China

Corresponding Author: Jin Wu

wujin8@mail.sysu.edu.cn

Nano-Micro Letters, Vol. 16 (2024), Article Number: 256

Abstract

Post-earthquake rescue missions are full of challenges due to the unstable structure of ruins and successive aftershocks. Most of the current rescue robots lack the ability to interact with environments, leading to low rescue efficiency. The multimodal electronic skin (e-skin) proposed not only reproduces the pressure, temperature, and humidity sensing capabilities of natural skin but also develops sensing functions beyond it—perceiving object proximity and NO2 gas. Its multilayer stacked structure based on Ecoflex and organohydrogel endows the e-skin with mechanical properties similar to natural skin. Rescue robots integrated with multimodal e-skin and artificial intelligence (AI) algorithms show strong environmental perception capabilities and can accurately distinguish objects and identify human limbs through grasping, laying the foundation for automated post-earthquake rescue. Besides, the combination of e-skin and NO2 wireless alarm circuits allows robots to sense toxic gases in the environment in real time, thereby adopting appropriate measures to protect trapped people from the toxic environment. Multimodal e-skin powered by AI algorithms and hardware circuits exhibits powerful environmental perception and information processing capabilities, which, as an interface for interaction with the physical world, dramatically expands intelligent robots’ application scenarios.


Highlights:
1 A novel organohydrogel-based multimodal e-skin with excellent sensing performance for temperature, humidity, pressure, proximity, and NO2 is proposed for the first time, showing powerful sensing capabilities beyond natural skin.
2 The developed multimodal e-skin exhibited extraordinary sensing performance at room temperature, including fast pressure response time (0.2 s), high temperature sensitivity (9.38% °C-1), a wide range of humidity response (22%–98% RH), high NO2 sensitivity (254% ppm-1), a low detection limit (11.1 ppb NO2) and the abilities to sense the proximity of objects accurately, which are yet achieved by previous e-skins.
3 The multimodal e-skin was combined with the deep neural network algorithm and wireless alarm circuit to achieve zero-error classification of different objects and rapid response to NOx leak incidents, proving the feasibility of the e-skin-assisted rescue robot for post-earthquake rescue.

Keywords

Stretchable hydrogel sensors Multimodal e-skin Artificial intelligence Post-earthquake rescue Wireless toxic gas alarm
Li, Jianye, Hao Wang, Yibing Luo, Zijing Zhou, He Zhang, Huizhi Chen, Kai Tao, Chuan Liu, Lingxing Zeng, Fengwei Huo, and Jin Wu. 2024. “Design of AI-Enhanced and Hardware-Supported Multimodal E-Skin for Environmental Object Recognition and Wireless Toxic Gas Alarm”. Nano-Micro Letters 16 (July):256. https://doi.org/10.1007/s40820-024-01466-6.
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