Biomedical microrobots have the potential to be functionalized to perform therapies in the body, such as chemotherapy and hyperthermia, which are targeted in a small region to avoid damage to healthy surrounding tissue and to avoid side-effects. These "microrobots" are likely to be microstructures with no computational intelligence on board, which are controlled within the patient's body by magnetic fields generated outside the body. Much of the work on magnetic microrobots to date has focused on microswimmers that use a helical propeller to swim using a method inspired by bacteria. However, promising laboratory results to date have utilized small numbers of microswimmers and have relied on imaging techniques such as cameras to track individual microswimmers, which is not practical for medical applications. This award supports fundamental research to enable swarms of microswimmers to be controlled in a complex fashion, in the absence of medical images with enough resolution to track individual microswimmers. The outcome of this award will be knowledge that will bring minimally invasive biomedical microrobots one step closer to clinical reality. The award will also provide research opportunities for graduate and undergraduate students, and will broaden participation of underrepresented groups in engineering education.
This research will test the conjecture that the inherent dynamics of magnetic microswimmers in rotating magnetic dipole fields make it possible to shepherd a swarm of microswimmers in the absence of localization of individuals. The term "shepherding" is borrowed because the intent is to perform the same type of tasks that would be done when herding sheep. The goal is to develop basic manipulation primitives such as "move the aggregate swarm to a location," "spread out the swarm," "gather the swarm together," and "split the swarm into smaller swarms and move them to separate locations." Specific tasks include: modeling the dynamics of single swimmers; characterizing shepherding control primitives assuming identical and non-interacting swimmers; characterizing shepherding control primitives that take advantage of population variation within a swarm; modeling magnetic and hydrodynamic interactions between swimmers; and synthesizing the relative contribution of the above effects to enable complex shepherding maneuvers with actual swarms of magnetic microswimmers.
