Chapter 5 - Obstacle avoidance for bacteria-powered microrobots

Abstract

For practical applications that involve microrobots there are several control related challenges. These challenges are often alleviated by constructing ideal environments, which are devoid of potential disturbances that can affect performance. However, in less idealistic working spaces where obstacles exist, microrobotic navigation algorithms must account for these objects. An autonomous control system will be more efficient than manual control to avoid these obstacles. In addition, the autonomous navigation will widen the potential application of microrobots, as autonomous control can supply the optimal motion control depending on the situation. In this chapter, we introduce a static obstacle avoidance algorithm for bacteria-powered microrobots. A bacteria-powered microrobot (BPM) is a hybrid robotic system consisting of an inorganic SU-8 microstructure with bacterial carpets, in which massive arrays of biomolecular flagellar motors work cooperatively. Our obstacle-avoidance method is based on a BPM's response to electric fields; the negatively charged bacteria enable the BPM to follow the electric field lines. In this chapter, the constraint elements to develop the obstacle avoidance method are discussed and demonstrated by experiments with simulation results. In the suggested approach, the methods, such as potential function and configuration-space, popular in macroscale robotics, are applied to microscale robotics. We describe the feasibility of the proposed obstacle avoidance approach through experiments and compare these data with simulation results.