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利用四通道昆虫触角电生理传感器定位紧凑型气味源。

Locating a compact odor source using a four-channel insect electroantennogram sensor.

机构信息

Chemical Ecology Laboratory, Department of Entomology, Pennsylvania State University, University Park, 16802, USA.

出版信息

Bioinspir Biomim. 2011 Mar;6(1):016002. doi: 10.1088/1748-3182/6/1/016002. Epub 2010 Dec 15.

Abstract

Here we demonstrate the feasibility of using an array of live insects to detect concentrated packets of odor and infer the location of an odor source (∼15 m away) using a backward Lagrangian dispersion model based on the Langevin equation. Bayesian inference allows uncertainty to be quantified, which is useful for robotic planning. The electroantennogram (EAG) is the biopotential developed between the tissue at the tip of an insect antenna and its base, which is due to the massed response of the olfactory receptor neurons to an odor stimulus. The EAG signal can carry tens of bits per second of information with a rise time as short as 12 ms (K A Justice 2005 J. Neurophiol. 93 2233-9). Here, instrumentation including a GPS with a digital compass and an ultrasonic 2D anemometer has been integrated with an EAG odor detection scheme, allowing the location of an odor source to be estimated by collecting data at several downwind locations. Bayesian inference in conjunction with a Lagrangian dispersion model, taking into account detection errors, has been implemented resulting in an estimate of the odor source location within 0.2 m of the actual location.

摘要

在这里,我们展示了使用一系列活体昆虫来检测浓缩气味包并使用基于朗之万方程的后拉拉格朗日扩散模型推断气味源位置(约 15 米远)的可行性。贝叶斯推断允许量化不确定性,这对于机器人规划很有用。触角电图(EAG)是昆虫触角尖端组织与其基部之间产生的生物电位,这是由于嗅觉受体神经元对气味刺激的大量反应。EAG 信号每秒可以携带数十位信息,上升时间短至 12 毫秒(K A Justice 2005 J. Neurophiol. 93 2233-9)。在这里,包括带有数字罗盘的 GPS 和超声二维风速计在内的仪器已与 EAG 气味检测方案集成在一起,允许通过在几个下风位置收集数据来估计气味源的位置。结合考虑到检测误差的拉格朗日扩散模型的贝叶斯推断,导致气味源位置的估计与实际位置相差 0.2 米以内。

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