FLAGELLATED BACTERIA AS SELF-NAVIGATOR NANO/BIO-ROBOTS
In this paper, we experimentally investigated the navigation system of the nonpathogenic strain of E. coli (AW405), and we developed a simulator for the locomotion performance of these swimming nanorobots. The swimming behavior of these robotic cells is sensitive to the chemical gradients in their medium. Tissue and disease cells might produce chemical signals in their surroundings. These chemicals have the potential to affect the locomotion behavior of the bacterial cells. Therefore, bacterial cells can be considered as self-navigator nanorobots that are able to discriminate between disease cells such as cancer. We exploit Bayesian decision theory as a framework in predicting the locomotion behavior of the E. coli robotic cells. Obvious agreement has been achieved between the experimental performance of our moving robotic cells and its corresponding simulation. Our current experimental and theoretical work is considered as a platform to this novel idea of early detection of problematic diseases.