TY - JOUR
T1 - Design of AI-Enhanced and Hardware-Supported Multimodal E-Skin for Environmental Object Recognition and Wireless Toxic Gas Alarm
AU - Li, Jianye
AU - Wang, Hao
AU - Luo, Yibing
AU - Zhou, Zijing
AU - Zhang, He
AU - Chen, Huizhi
AU - Tao, Kai
AU - Liu, Chuan
AU - Zeng, Lingxing
AU - Huo, Fengwei
AU - Wu, Jin
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024/12
Y1 - 2024/12
N2 - 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. (Figure presented.)
AB - 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. (Figure presented.)
KW - Artificial intelligence
KW - Multimodal e-skin
KW - Post-earthquake rescue
KW - Stretchable hydrogel sensors
KW - Wireless toxic gas alarm
UR - http://www.scopus.com/inward/record.url?scp=85199966335&partnerID=8YFLogxK
U2 - 10.1007/s40820-024-01466-6
DO - 10.1007/s40820-024-01466-6
M3 - 文章
AN - SCOPUS:85199966335
SN - 2311-6706
VL - 16
JO - Nano-Micro Letters
JF - Nano-Micro Letters
IS - 1
M1 - 256
ER -