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Bionic sensing array to lend a “land” to disaster rescue
Professor Tiger H. Tao and colleagues at SIMIT (Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences) have developed a tactile-olfactory sensing array to facilitate search and rescue work in darkness or buried scenarios caused by geological disasters.

The design of the bionic sensing array, inspired by the natural sense-fusion system of star-nose mole, can enable real-time acquisition of the local topography, stiffness, and odor of a variety of objects in non-visual environments. Star-nosed moles have evolved the capability of object recognition using only tactile and olfactory perception, allowing it to survive in the lightless underground environment. The tactile-olfactory information is processed by a bio-inspired machine-learning algorithm, essentially mimicking the biological fusion procedures in the neural system of the star-nose mole. In a simulated rescue scenario at a fire department test site, the tactile-olfactory intelligent sensing system could classify 11 typical objects with an accuracy of 96.9 percent. The tactile-olfactory bionic sensing system required no visual input and showed superior tolerance to environmental interference, according to the article.

The paper entitled “A star-nose-like tactile-olfactory bionic sensing array for robust object recognition in non-visual environments” has been published in Nature Communications (DOI: 10.1038/S41467-021-27672-Z). This work was supported by National Science and Technology Major Project from the Minister of Science and Technology of China, National Science Fund for Excellent Young Scholars, National Natural Science Foundation of China, Shanghai Outstanding Academic Leaders Plan, Shanghai Sailing Program, Key Research Program of Frontier Sciences, CAS, the Strategic Priority Research Program of Chinese Academy of Science and the Guangdong Provincial Key Research and Development Plan.

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Figure. Bioinspired tactile-olfactory associated intelligent sensory system

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