Autonomous Robot Modeling of Bacterial Motion and Chemotaxis

Overview

Objectives/Goals Some forms of bacteria have flagella to move through water and have two movement phases: straight swim and random tumbling. Certain forms continuously transition between the movement phases, while other bacteria, such as E. coli, employ chemotaxis to decide between movement phases. Chemotaxis is a process in which bacteria direct themselves toward highly favorable areas of food by either straight swimming when conditions are improving or randomly tumbling to reorient themselves when conditions are unfavorable. A comparison between the completely random movement method and chemotaxis movement was made. In addition, an evaluation of how frequently to check food concentrations and decide between transitioning was completed. Finally, the effects of external disturbances on bacteria were explored. Methods/Materials Due to the complexity of creating a bacterial environment with a wide range of food concentrations, a bacterium was modeled using an autonomous robot created with the Arduino platform and programmed in Python. The modeled environment contained a dynamic gradient of light levels that represented food concentrations in a bacterial environment. Results Findings show chemotaxis movement performs better than completely random movement by an average of 57 percent. Furthermore, checking food concentration levels every 0.5 seconds was the optimal frequency and resulted in the highest average light level. Additionally, external disturbances caused detrimental effects on collecting light for the chemotaxis movement while having minimal effects on the completely random movement. Conclusions/Discussion This model demonstrates that random movements are not completely random: there is a clear evolutionary benefit of chemotaxis movement and the frequent checking of concentration levels.

Competition history

• CSEF 2010 Electronics & Electromagnetics · Entry S0999

Resources

• CSEF project summary ↗

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