Odor Space Navigation Using Multisensory E-Nose
電子鼻技術用于空間環境氣味掃描識別追蹤
V. V. Krylov
Alekseev Nizhny Novgorod State Technical University, Nizhny Novgorod, Russia
: vkrylov
Received May 11, 2016
Abstract—A spatial odor distribution in an environment can be used for navigation, goal search, localization and mapping, like by video, ultrasonic, temperature and other sensors. Modern e-noses(Cyranose 320) can perform the selective detection of different gases with an extremely low concentration but the source localization algorithms of a selected gas against the background of other odors are still underinvestigated. This paper studies an odor field representation in terms of an e-nose based on an array of low-selective sensors. Using a simulation model, we show how the vector measurements of a field of several odor sources can be processed to navigate for reaching a selected odor source. In addition, we demonstrate that the source having a high level of odor intensity can interfere with the search of another odor source of a low intensity. The well-known class of matching receivers does not solve this problem. However, a solution can be obtained by distributed measurements. As shown below, the spatial structure of an odor field allows to implement vector selection. Using deep learning machines, we may reach a high resolution of odor sources in the space. Our future research will be focused on augmented odor reality and autonomous e-nose (e-dog) design.
環境中的空間氣味分布可用于導航、目標搜索、定位和繪圖，如視頻、超聲波、溫度和其他傳感器。電子鼻(Cyranose 320)可以對濃度極低的不同氣體進行選擇性檢測，但在其他氣味的背景下，對所選氣體的源定位算法仍缺乏研究。本文研究了一種基于低選擇性傳感器陣列的電子鼻氣味場表示方法。利用一個模擬模型，我們展示了如何處理多個氣味源場的矢量測量，從而導航到選定的氣味源。此外，我們還證明，氣味強度高的來源會干擾尋找另一種低強度的氣味來源。*的匹配接收機并不能解決這個問題。然而，可以通過分布式測量獲得解決方案。如下圖所示，氣味場的空間結構允許實現向量選擇。使用深度學習機器，我們可以在空間中獲得高分辨率的氣味源。我們未來的研究將集中在增強氣味現實和自主移動電子鼻(e-dog)設計上。
Keywords:odor, e-nose, sensors, odor space, space based selection, navigation, computer simulation,nonnegative matrix factorization
DOI: 10.1134/S0005117918010149
