This work presents an approach for the localization and control of helical robots during removal of superficial blood clots inside in vitro and ex vivo models. The position of the helical robot is estimated using an array of Hall-effect sensors and precalculated magnetic field map of two synchronized rotating dipole fields. The estimated position is used to implement closed-loop motion control of the helical robot using the rotating dipole fields. We validate the localization accuracy by visual feedback and feature tracking inside the in vitro model. The experimental results show that the magnetic localization of a helical robot with diameter of 1 mm can achieve a mean absolute position error of 2.35 ± 0.4 mm (n = 20). The simultaneous localization and motion control of the helical robot enables propulsion toward a blood clot and clearing at an average removal rate of 0.67 ± 0.47 mm3/min. This method is used to localize the helical robot inside a rabbit aorta (ex vivo model), and the localization accuracy is validated using ultrasound feedback with a mean absolute position error of 2.6 mm.

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In this letter, we develop a magnetic localization system for an electromagnetic-based haptic interface (EHI). Haptic interaction is achieved using a controlled magnetic force applied via an EHI on a magnetic dipole attached to a wearable finger splint. The position of the magnetic dipole is estimated using two identical arrays of three-dimensional magnetic field sensors in order to eliminate the magnetic field generated by the EHI. The measurements of these arrays are used to estimate the position of the magnetic dipole by an artificial neural network. This network maps the field readings to the position of the magnetic dipole. The proposed system is experimentally validated under four cases of the magnetic field generated by the EHI. These cases are likely to be encountered during the haptic rendering of virtual shapes. In the absence of the magnetic field, the mean absolute position error (MAE) is 0.80 ± 0.30 mm (n = 125). Static and sinusoidal magnetic fields are applied, and the MAEs are 1.26 ± 0.43 mm (n = 125) and 0.91 ± 0.33 mm (n = 125), respectively. A random time-varying magnetic field is applied, and the MAE is 0.86 ± 0.33 mm (n = 125). Our statistical analysis shows that the repeatability of the magnetic localization is acceptable regardless of the field generated by the EHI, at α = 0.05 and 95% confidence level.

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Magnetic actuation of minimally invasive medical tetherless devices holds great promise in several biomedical applications. However, there are still several challenges in noninvasive localization, both in terms of sensing detectable signals of these devices and estimating their states. In this work, a magnetic milli-roller is actuated in a viscous fluid under the influence of a rotating magnetic field. A Lyapunov-based nonlinear state observer is designed and implemented to estimate the position of the roller using a 2D array of Hall-effect sensors. We show that the local stability of the state observer yields convergence to one of the local equilibria, for pre-defined levels of sensor noise, initial conditions, and modeling errors. Performance is quantified using redundant measurements of the fields and we investigate the influence of the number of magnetic field measurements on the observability of the system. Open-loop actuation and state estimation are demonstrated and experimental results show that the localization of a 5 mm diameter roller along sinusoidal, circular and square trajectories achieve a steady-state mean absolute position error of 2.3 mm, 1.67 mm and 1.73 mm, respectively.