This paper presents the design, development and implementation of a novel, high power hexapole magnetic tweezer system for 3D micromanipulations. Six tapering-tipped magnetic poles are deployed in a tilted Cartesian coordinate system, with an electromagnetic coil on each for actuation, connected by two 3D printed magnetic yokes to form a double layer structure. The power source is integrated to the magnetic tweezer system through a control algorithm on the software level; image processing was used for experiment analysis. Because of the high magnetic field that the magnetic coils can generate, the working space in the system is relatively larger than other similar designs, which provides better performance on microscale robotic swimmer manipulations. Simulations and experiments performed in this paper demonstrate the agile and powerful manipulation of microswimmers with desired control input to follow complex trajectories, avoid obstacles and move against micro-flow in the samples. We prove that the developed hexapole magnetic tweezer has enough power and controllability to guide microswimmers in Newtonian and Non-Newtonian fluid environments. The system will be optimized continuously and implemented into cell penetration experiments. Finally, the application will be deployed into in vivo based environments.

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.

As microscale robots are becoming increasingly popular due to their potential for medical and industrial applications, various designs of microscale robotic system have been developed. However, there has not been much work on autonomous control algorithms for microscale robots in microfluidic environments. In this paper, we introduce an autonomous navigation algorithm for the bacteria-powered microrobots (BPMs) in a workspace with moving obstacles. A BPM consists of a rigid inorganic body with bacteria attached on the surface. The attached bacteria provide propulsive force and are controllable using electric fields, which had been demonstrated in previous work. We take the controllability of BPMs and the unpredictable motion of dynamic obstacles into account to develop a dynamic obstacle avoidance approach. Moreover, we use finite element simulation to observe an electric field around a moving obstacle to model the field's deformation. Demonstration of dynamic obstacle avoidance approach through simulation results and experimental data are presented in the paper.