A star-nose-like tactile-olfactory bionic sensing array for robust object recognition in non-visual environments.

Mengwei Liu, Yujia Zhang,Jiachuang Wang, Nan Qin,Heng Yang, Ke Sun,Jie Hao, Lin Shu,Jiarui Liu, Qiang Chen, Pingping Zhang,Tiger H Tao

Nature communications(2022)

引用 42|浏览35
暂无评分
摘要
Object recognition is among the basic survival skills of human beings and other animals. To date, artificial intelligence (AI) assisted high-performance object recognition is primarily visual-based, empowered by the rapid development of sensing and computational capabilities. Here, we report a tactile-olfactory sensing array, which was inspired by the natural sense-fusion system of star-nose mole, and can permit real-time acquisition of the local topography, stiffness, and odor of a variety of objects without visual input. The tactile-olfactory information is processed by a bioinspired olfactory-tactile associated machine-learning algorithm, essentially mimicking the biological fusion procedures in the neural system of the star-nose mole. Aiming to achieve human identification during rescue missions in challenging environments such as dark or buried scenarios, our tactile-olfactory intelligent sensing system could classify 11 typical objects with an accuracy of 96.9% in a simulated rescue scenario at a fire department test site. The tactile-olfactory bionic sensing system required no visual input and showed superior tolerance to environmental interference, highlighting its great potential for robust object recognition in difficult environments where other methods fall short.
更多
查看译文
关键词
Electrical and electronic engineering,Mechanical engineering,Science,Humanities and Social Sciences,multidisciplinary
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要