Electric Field Control of Bacteria-Powered Microrobots Using a Static Obstacle Avoidance Algorithm

Abstract

A bacteria-powered microrobot (BPM) is a hybrid robotic system consisting of an SU-8 microstructure with active surfaces or bacterial carpets, in which massive arrays of biomolecular flagellar motors work cooperatively. This paper suggests an obstacle-avoidance method based on a BPM's response to electric fields. The negatively charged bacteria enable the BPM to follow electric fields. In our previous demonstration of the single BPM controllability, we observed a vast change in the control dynamics when obstructions distorted the applied electric field and affected BPM steering and control. In this paper, we demonstrate an obstacle avoidance method that takes the electric field distortion into account to navigate a BPM through multiple static obstacles in real time. We used an artificial potential field and configuration space in our algorithm to generate an objective function for the electric field distortion and collision around/with obstacles, respectively. In addition, finite-element modeling through COMSOL Multiphysics engineering software was used to simulate charged-particle trajectories in a distorted electric field. Finally, we describe the feasibility of our proposed obstacle avoidance approach through experiments and compared these data with simulation results.