Integrated Sensing and Acting with Tunable Chemical Sensors

研究目标和方法。 本研究的目的是开发概率方法的主动传感与可调化学传感器。 该方法被制定为一个部分可观察的马尔可夫决策过程，从而系统采取连续的传感行动，以确定一个化学目标。 研究人员将开发算法，以适应两种情况下的传感器调谐：目标识别和背景拒绝。这些算法将在两个可调传感器技术（金属氧化物化学电阻器和红外干涉仪）结合可调预浓缩器进行验证。智力上的优点。主动传感在化学传感器中受到的关注最少，其中大多数工作都集中在离线优化上。 同样，化学计量学技术假设化学品的全谱是可用的。 相比之下，拟议的工作认为，只有最翔实的波长/功能是必要的，这些应该动态选择。 这项研究将导致敏捷系统，可以适应传感参数的飞行，以响应其环境。这项工作还将提供对一系列场景（例如静态与动态刺激）和传感器特性（例如特定与交叉选择）的主动感测的更好理解。 更广泛的影响。 对于从质量控制到环境监测的许多应用，需要快速检测、识别和量化挥发性化合物。 所提出的方法推广到一个大类的化学检测器，并可能使化学传感器的功率感知网络的发展。 该项目将为本科生提供研究机会;自2001年以来，PI已经监督了45个高级设计项目，涉及140多名学生。

AbstractResearch objectives and approaches. The objective of this research is to develop probabilistic methods for active sensing with tunable chemosensors. The approach is formulated as a partially observable Markov decision process, whereby the system takes sequential sensing actions to identify a chemical target. The investigators will develop algorithms to adapt sensor tunings on-the-fly for two types of scenario: target discrimination and background rejection. These algorithms will be validated on two tunable sensor technologies (metal-oxide chemoresistors and infrared interferometers) combined with tunable preconcentrators. Intellectual merit. Active sensing has received minimal attention in chemosensors, where most work has focused on off-line optimization. Likewise, chemometrics techniques assume that a full spectrum of the chemical is available. In contrast, the proposed work argues that only the most informative wavelengths/features are needed, and that these should be selected dynamically. This research will lead to agile systems that can adapt sensing parameters on-the-fly in response to their environments. The work will also provide a better understanding of active sensing across a range of scenarios (e.g. static vs. dynamic stimuli) and sensor characteristics (e.g. specific vs. cross-selective). Broader impacts. For a number of applications, from quality control to environmental monitoring, there is a need to rapidly detect, identify and quantify volatile compounds. The proposed methodology generalizes to a large class of chemical detectors, and may enable the development of power-aware networks of chemical sensors. The project will provide research opportunities for undergraduate students; since 2001, the PI has supervised 45 senior-design projects involving over 140 students.