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Localization of chemical sources using E. Coli chemotaxis

机译:使用大肠杆菌趋化性对化学源进行定位

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This paper furthers the application of chemotaxis to small-scale robots by simulating a system that localizes a chemical source in a dynamic fluid environment. This type of system responds to a chemical stimulus by mimicking, for example, the way that E. Coli bacteria move toward attractants (nutrients) and away from repellents. E. Coli use the intracellular signaling pathway to process the temporal change in the chemical concentration to determine if the cells should run or tumble. Previous work has shown that this process can be simulated with robots and used to localize chemical sources based upon a fixed nutrient gradient. Our work furthers this study by simulating the injection of an effluent of chemical at a specified location in an environment and uses computational fluid dynamics to model the interactions of the robot with the fluid while performing chemotaxis. The interactions between the chemical and fluid are also modelled with the advection diffusion equation to determine the concentration gradient. This method allows us to compute, over a lattice, the chemical concentration at all points and feed these results into an existing E. Coli controller for the robot, which results in the robot executing a tumble or a run according to a probabilistic formula. By simulating the robot in this complex environment, our work facilitates refinement of the chemotaxis controller while proving the ability of chemotactic robots to localize specific chemicals in environments that more closely resemble those encountered in the wide-ranging types of locations in which this robotic system might be deployed.
机译:本文通过模拟在动态流体环境中定位化学源的系统,进一步将趋化性应用于小型机器人。这种类型的系统通过模仿例如大肠埃希氏菌细菌向诱引剂(营养物)移动并远离驱避剂的方式来对化学刺激作出反应。 E. Coli使用细胞内信号传导途径来处理化学浓度的时间变化,以确定细胞是否应该运转或翻滚。先前的工作表明,可以使用机器人模拟此过程,并基于固定的营养梯度将其用于定位化学源。我们的工作通过在环境中的指定位置模拟化学流出物的注入来进一步推进这项研究,并使用计算流体动力学来模拟执行趋化性时机器人与流体的相互作用。还使用对流扩散方程对化学物质和流体之间的相互作用进行建模,以确定浓度梯度。这种方法使我们能够在晶格上计算所有点的化学浓度,并将这些结果输入到现有的机器人大肠杆菌控制器中,从而使机器人根据概率公式执行翻转或运行。通过在复杂的环境中模拟机器人,我们的工作有助于优化趋化性控制器,同时证明趋化性机器人能够将特定化学物质定位在与该机器人系统可能在广泛位置类型中遇到的环境更相似的环境中的特定化学物质。被部署。

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