Soft surgical robots which are able to trace their way through the human body — known as "continuum medical robots" — now have their own form of GPS, thanks to a system of magnets which does away with potentially dangerous radiation exposure required of previous tracking methods.
"Continuum medical robots work really well in highly constrained environments inside the body," explains Professor Tania Morimoto, in background to the work of a team at the University of California San Diego. "They're inherently safer and more compliant than rigid tools. But it becomes a lot harder to track their location and their shape inside the body. And so if we are able track them more easily that would be a great benefit both to patients and surgeons."
A common method for tracking the location and shape of these robots is to use a radioactive tracer, but this has health risks involved — something that the team's solution, which uses a magnet embedded in the robot and four magnetometers spaced around the operating area, does not.
The team demonstrated the magnet-tracking system using a growing robot, "which is a robot made of a very thin nylon that we invert," lead author Connor Watson elaborates, "almost like a sock, and pressurize with a fluid which causes the robot to grow." By measuring the strength of the magnetic field at each of the four points, the team was able to accurately track the position of the robot's tip — and the entire rig, including the robot, magnet, and localisation system, cost around $100.
Once the concept had been proven, the team took it a step further: The development of a neural network which was able to detect inaccuracies in the system and correct for them, improving the accuracy still further. "Ideally we are hoping that our localisation tools can help improve these kinds of growing robot technologies," says Morimoto. "We want to push this research forward so that we can test our system in a clinical setting and eventually translate it into clinical use."
The team's work has been published in the journal IEEE Robotics and Automation Letters.