Biological robots can be produced in large numbers, but are often controlled by uniform inputs. This makes position control of multiple robots inherently challenging. This paper uses magnetically-steered ciliate eukaryon {Tetrahymena pyriformis) as a case study. These cells swim at a constant speed, and can be turned by changing the orientation of an external magnetic field. We show that it is possible to steer multiple T. pyriformis to independent goals if their turning - modeled as a first-order system - has unique time constants. We provide system identification tools to parameterize multiple cells in parallel. We construct feedback control-Lyapunov methods that exploit differing phase-lags under a rotating magnetic field to steer multiple cells to independent target positions. We prove that these techniques scale to any number of cells with unique first-order responses to the global magnetic field. We provide simulations steering hundreds of cells and validate our procedure in hardware experiments with multiple cells.

We demonstrate three-dimensional control with the eukaryotic cell Tetrahymena pyriformis (T. pyriformis) using two sets of Helmholtz coils for xy-plane motion and a single electromagnet for vertical motion. T. pyriformis is modified to have artificial magnetotaxis with internalized magnetite. Since the magnetic fields exerted by electromagnets are relatively uniform in the working space, the magnetite exerts only torque, without translational force, which enabled us to guide the cell's swimming direction while the swimming force is exerted only by the cell's motile organelles. A stronger magnetic force was necessary to steer cells to the z-axis, and, as a result, a single electromagnet placed just below our sample area is utilized for vertical motion. To track the cell's positions in the z-axis, intensity profiles of non-motile cells at varying distances from the focal plane are used. During vertical motion along the z-axis, the intensity difference from the background decreases while the cell size increases. Since the cell is pear-shaped, the eccentricity is high during planar motion, but lowers during vertical motion due to the change in orientation. The three-dimensional control of the live organism T. pyriformis as a cellular robot shows great potential to be utilized for practical applications in microscale tasks, such as target transport and cell therapy.

The use of live microbial cells as microscale robots is an attractive premise, primarily because they are easy to produce and to fuel. In this paper, we study the motion control of magnetotactic Tetrahymena pyriformis cells. Magnetotactic T. pyriformis is produced by introducing artificial magnetic dipole into the cells. Subsequently, they can be steered by using an external magnetic field. We observe that the external magnetic field can only be used to affect the swimming direction of the cells, while the swimming velocity depends largely on the cells' own propulsion. Feedback information for control is obtained from a computer vision system that tracks the cell. The contribution of this paper is twofold. First, we construct a discrete-time model for the cell dynamics that is based on first principle. Subsequently, we identify the model parameters using the Least Squares approach. Second, we formulate a model predictive approach for feedback control of magnetotactic T. pyriformis. Both the model fitness and the performance of the feedback controller are verified using experimental data.