For over a decade, surgeons have been using joystick-operated robots to navigate inside the body. But for the first time, a team of bioengineers at Boston Children’s Hospital demonstrated a robot that can navigate autonomously inside the human body.

In an animal model of cardia valve repair, the team programmed a robotic catheter to find the way along the walls of a beating, bluttered heart to a leaky valve — without the assistance of a surgeon.

According to Science Robotics, the small robots can control the body through external forces such as magnetism. This is the first report by senior investigador Pierre Dupont, Ph.D., Chief of Pediatric Cardiac Bioengineering at Boston Children, of the equivalent to the desired destination in the body, adding that autonomous robots help surgeons in complex operations and can reduce tiredness and free surgeons to focus on the most difficult maneuvers and improve results.

“The right way to think about it is by analogying a fighter pilot with a fighter plane. The fighter plane takes on routine tasks such as flying the plane, so the pilot can concentrate on the mission’s higher levels tasks,” he added.

The robotic catheter in Dupont’s laboratory navigated with an optical touch sensor, informed about cardiac anatomy and preoperative scanning by a map. The touch sensor uses artificial intelligence and image processing algorithms to help the catheter figure out where he or she is at heart and where he or she needs to go.

For the demonstration, the team performed a technically demanding procedure called a paravalvular aortic leak closure, in which repairs heart replacement valves that have begun to leak around the edges. Once the robot catheter reached the location of the leak, an experienced cardiac surgeon took over and inserted the plug to close the leak.

The robotic catheter has successfully navigated to the heart valve leaks in repeated trials approximately the same period as the surgeon (with either a hand tool or a joystick-controlled robot). The robotic catheter’s optical touch sensor sampled its environment at regular intervals using a navigation technique called’ the following wall,’ much like insect antennas or rodent whiskers sampling the surroundings to build mental maps of unfamiliar dark environments. The sensor told the catheter whether it was touching the blood, the cardiac wall or a valve and how hard it was pushing (to prevent the heart from being damaged).

Preoperative imagery and machine learning algorithms contributed to the catheter’s interpretation of visual features. Thus, the robotic catheter advanced from the base of the heart along the left ventricle wall and the leaky valve up to the leak location. Although the autonomous robot took a bit longer to reach the leaky valve than the surgeon, its wall-following technique meant it took the longest path.

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