LAUSR

Swarm magnetic control is a promising technology for use in nanorobotics. However, automated control schemes for small and large populations of nanoparticles are not effective due to the complexity of real blood vessels, the lack of technologies for motion control feedback of individual particles, and the inaccuracy of the mathematical models. It is quite difficult to control unexpected magnetic particle movements in a real vessel. Specifically, when magnets are used to guide the particles, the sticking of particles to vessel walls causes the dispersion of particles, which is the main reason for low steering efficiency that may cause the occurrence of side effects in non-targeted areas. In addition, when the aggregation of particles occurs inside the vessels, it can cause clogging of the vessel and the randomness of aggregation makes it difficult for the user to control the particles precisely. In the presented work, we suggest a novel intuitive shared guidance scheme for 3D steering of magnetic nanoparticles (MNPs) in a realistic vessel model. We have performed simulation based user studies with different guidance modes (visual feedback (V), shared control (S), shared control and forbidden region mode (S-F), shared control and adaptive forbidden region mode (S-AF)). The results of these studies show that the suggested S-AF mode can significantly ( ${p}$ -value < 0.01) increase the delivery rate of MNPs to the target region while significantly ( ${p}$ -value < 0.01) reducing the sticking rate of MNPs inside the vessel. The proposed intelligent navigation scheme for MNPs can in the future be combined with real-time magnetic particle imaging (MPI) for targeted drug delivery.