Dynamic Simulation-Guided Design of Tumbling Magnetic Microrobots

Tumbling microrobots can perform such tasks as drug delivery, tissue biopsies, or toxin neutralization in our bodies. They can be accentuated by a rotating external magnetic field. Currently, the design of such robots is based on trial and error.

Therefore, a recent study suggests a simulation tool for the motion of microrobots of different geometry. It addresses the problem of computing the adhesive forces, which change during motion based on the contact between robot and substrate.

The simulation shows that spiked ends geometry results in the best overall performance locomotion tests and inclined plane tests. Physical versions of the spike-shaped robots and spiked ends-shaped robots were manufactured. However, some manufacturing limitations were encountered. The authors of the study show how manufacturing errors can be included in the simulation to model the actual motion of the robots.

Design of robots at the small scale is a trial-and-error based process, which is costly and time-consuming. There are few dynamic simulation tools available to accurately predict the motion or performance of untethered microrobots as they move over a substrate. At smaller length scales, the influence of adhesion and friction, which scales with surface area, becomes more pronounced. Thus, rigid body dynamic simulators, which implicitly assume that contact between two bodies can be modeled as point contact are not suitable. In this paper, we present techniques for simulating the motion of microrobots where there can be intermittent and non-point contact between the robot and the substrate. We use these techniques to study the motion of tumbling microrobots of different shapes and select shapes that are optimal for improving locomotion performance. Simulation results are verified using experimental data on linear velocity, maximum climbable incline angle, and microrobot trajectory. Microrobots with improved geometry were fabricated, but limitations in the fabrication process resulted in unexpected manufacturing errors and material/size scale adjustments. The developed simulation model is able to incorporate these limitations and emulate their effect on the microrobot’s motion, reproducing the experimental behavior of the tumbling microrobots, further showcasing the effectiveness of having such a dynamic model.


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