Magnetic Soft Catheters (MSCs) are capable of miniaturization due to the use of an external magnetic field for actuation. Through careful design of the magnetic elements within the MSC and the external magnetic field, the shape along the full length of the catheter can be precisely controlled. However, modeling of the magnetic-soft material is challenging due to the complex relationship between magnetic and elastic stresses within the material. Approaches based on traditional Finite Element Methods (FEM) lead to high computation time and rely on proprietary implementations. In this work, we showcase the use of our recently presented open-source simulation framework based on the Material Point Method (MPM) for the computational design of magnetic soft catheters to realize arbitrary shapes in 3D, and to facilitate follow-the-leader shape-forming insertion.

Localization of magnetically actuated medical robots is essential for accurate actuation, closed loop control and delivery of functionality. Despite extensive progress in the use of magnetic field and inertial measurements for pose estimation, these have been either under single external permanent magnet actuation or coil systems. With the advent of new magnetic actuation systems comprised of multiple external permanent magnets for increased control and manipulability, new localization techniques are necessary to account for and leverage the additional magnetic field sources. In this letter, we introduce a novel magnetic localization technique in the Special Euclidean Group SE(3) for multiple external permanent magnetic field actuation and control systems. The method relies on a milli-meter scale three-dimensional accelerometer and a three-dimensional magnetic field sensor and is able to estimate the full 6 degree-of-freedom pose without any prior pose information. We demonstrated the localization system with two external permanent magnets and achieved localization errors of 8.5 ? 2.4 mm in position norm and 3.7 ? 3.6? in orientation, across a cubic workspace with 20 cm length.

The ability to have multiple magnetic robots operate independently in the same workspace would increase the clinical potential of these systems allowing collaborative operation. In this work, we investigate the feasibility of actuating two magnetic robots operating within the same workspace using external permanent magnets. Unlike actuation systems based on pairs of electromagnetic coils, the use of multiple permanent magnets comes with the advantage of a large workspace which better suits the clinical setting. In this work, we present an optimization routine capable of generating the required poses for the external magnets in order to control the position and orientation of two magnetic robots. We show that at a distance of 15cm, minimal coupling between the magnetic robots can be achieved (3.9\% crosstalk) each embedded with 5mm diameter, 5mm length NdFeB magnets. At smaller distances, we observe that the ability to independently control the robot torques decreases, but forces can still achieve independent control even with alignment of the robots. We test our developed control system in a simulation of two magnetic robots following pre-planned trajectories in close proximity (60 mm) showing a mean positional error of 8.7 mm and mean angular error of 16.7 degrees.

A robot that can perform colonoscopies may make the procedure simpler and less unpleasant. Pietro Valdastri at the University of Leeds in the UK and his colleagues have developed a robotic arm that uses a machine learning algorithm to move a flexible probe along the colon. The probe is a magnetic endoscope, a tube with a camera lens at the tip, that the robot controls via a magnet external to the body. The system can either work autonomously or be controlled by a human operator using a joystick, which pushes the endoscope tip further along the colon. The system also keeps track of the location and orientation of the endoscope inside the colon.

A robot that can perform colonoscopies may make the procedure simpler and less unpleasant. Pietro Valdastri at the University of Leeds in the UK and his colleagues have developed a robotic arm that uses a machine learning algorithm to move a flexible probe along the colon. The probe is a magnetic endoscope, a tube with a camera lens at the tip, that the robot controls via a magnet external to the body. The system can either work autonomously or be controlled by a human operator using a joystick, which pushes the endoscope tip further along the colon. The system also keeps track of the location and orientation of the endoscope inside the colon.

A tiny robotic capsule that can be guided through the colon to take micro-ultrasound images of the gut is being developed by a UK-led consortium. The Sonopill, being developed by researchers at Leeds, Glasgow, Edinburgh, Heriot-Watt and Dundee Universities, alongside Vanderbilt University in the US, could ultimately replace the need for patients to undergo a potentially painful endoscopic examination, in which a long, semi-rigid scope is passed into the bowel. The robotic device, which has successfully completed feasibility studies and is described in the journal Science Robotics, is based on a technique called intelligent magnetic manipulation, according to Pietro Valdastri, chair in robotics and autonomous systems at Leeds University. A robotic arm equipped with a series of magnets is passed over the patient. "We are trying to create a system that could replace colonoscopy with a painless alternative," Valdastri said.

This might be a tough pill to swallow, but the future of medicine is all about ingestible sensors. Things like cameras to scope out your bowels and electronics that detect if you've taken your medicine (recently FDA-approved, by the way). Researchers at MIT have developed a frozen gizmo made of pig intestine that you drop down the hatch. As it thaws in your stomach, it unfolds. Using a magnetic field, a doctor could theoretically lead the device to something you've gone and swallowed but really shouldn't have--batteries aren't as tasty as they look--and hurry the offending object out of your system.