Real-time feedback control using artificial magnetotaxis with rapidly-exploring random tree (RRT) for Tetrahymena pyriformis as a microbiorobot
In this paper, we present a control strategy using real-time feedback combined with feasible path planning to manipulate a type of microorganism, Tetrahymena pyriformis (T. pyriformis), as a micro-bio-robot using artificial magnetotaxis. Artificially magnetotactic T. pyriformis cells were created by the internalization of iron oxide nano particles. Following the magnetization of the internalized particles, the cells become controllable using an external time-varying magnetic field. The behavior of artificially magnetotactic T. pyriformis under a magnetic field has been investigated in a manual control experiment. A feasible path planner called rapidly-exploring random tree (RRT) and a feedback control scheme are implemented to guide the cell to a desired position and orientation. Since the motion of T. pyriformis is nonlinear like that of a car, combining the RRT and feedback control allows the cell to be controlled in 3-dimensional (x, y, θ) space. In the results, real-time feedback control of T. pyriformis in 3-dimensional space demonstrated the potential of utilizing T. pyriformis as a micro-bio-robot for microscale tasks.
Tetrahymnea pyriformis Artificial magnetotaxis Real-time feedback control Rapidly-exploring random tree (RRT) Microbiorobot
Dal Hyung Kim Sean Brigandi Anak Agung Julius Min Jun Kim
Department of Mechanical Engineering and Mechanics,Drexel University,Philadelphia,PA 19104,USA Department of Electrical,Computer and Systems Engineering,Rensselaer Polytechnic Institute,Troy,NY 1
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
3183-3188
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）