Soft jellyfish-like clip mimics the mechanics of curly hair

If you’ve ever played the claw game in an arcade, you know how difficult it is to grab and hold objects using robotic claws. Imagine how much more stressful that game would be if, instead of stuffed animals, you were trying to grab a fragile piece of endangered coral or a priceless artifact from a sunken ship.

Most of today’s robotic grippers rely on embedded sensors, complex feedback loops, or advanced machine learning algorithms, combined with operator skill, to grab fragile or irregularly shaped objects. But researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have shown an easier way.

Taking inspiration from nature, they designed a new type of soft robotic claw that uses a collection of slender tentacles to entangle and grab objects, similar to how jellyfish grab stunned prey. Alone, the individual tentacles, or filaments, are weak. But together, the collection of filaments can safely grab and hold heavy and oddly shaped objects. The gripper relies on simple inflation to wrap objects and requires no sensing, planning, or feedback control.

The research was published in the Proceedings of the National Academy of Sciences (PNAS).

“With this research, we wanted to reimagine how we interact with objects,” said Kaitlyn Becker, a former graduate student and postdoctoral fellow at SEAS and first author of the paper. “By harnessing the natural compliance of soft robotics and enhancing it with a compatible structure, we designed a gripper that is greater than the sum of its parts and a gripping strategy that can adapt to a variety of complex objects with minimal planning and perception. . .”

Becker is currently an assistant professor of mechanical engineering at MIT.

The force and adaptability of the pincer come from its ability to become entangled with the object it is trying to grab. The foot-long filaments are hollow rubber tubes. One side of the tube has thicker rubber than the other, so when the tube is pressurized, it curls like a ponytail or straightened hair on a rainy day.

The curls knot and tangle with each other and with the object, with each tangle increasing the strength of the grip. While the collective grip is strong, each contact is individually weak and will not damage even the most fragile object. To release the object, the filaments simply depressurize.

The researchers used simulations and experiments to test the clamp’s effectiveness, picking up a variety of objects, including various houseplants and toys. The gripper could be used in real-world applications to grip soft fruits and vegetables for agricultural production and distribution, delicate tissues in medical settings, even irregularly shaped objects in warehouses such as glassware.

This new grasping approach combines Professor L. Mahadevan’s research on the topological mechanics of entangled filaments with Professor Robert Wood’s research on soft robotic grippers.

“Entanglement allows each highly compatible strand to fit locally to a target object, leading to a secure but smooth topological grip that is relatively independent of the details of the nature of the contact,” said Mahadevan, Lola Professor of Applied Mathematics. England de Valpine in SEAS, and of Organismic and Evolutionary Biology, and Physics in FAS and co-corresponding author of the article.

“This new approach to robotic grasping complements existing solutions by replacing simple, traditional grippers that require complex control strategies with extremely compatible and morphologically complex filaments that can operate with very simple control,” said Wood, Harry Potter Professor of Engineering. Lewis and Marlyn McGrath. and Applied Sciences and corresponding co-author of the article. “This approach broadens the range of what is possible to pick with robotic grippers.”

Co-authors of the research were Clark Teeple, Nicholas Charles, Yeonsu Jung, Daniel Baum, and James C. Weaver. It was supported in part by the Office of Naval Research, under grant N00014-17-1-206 and the National Science Foundation under grants EFRI-1830901, DMR-1922321, DMR-2011754, DBI-1556164, and EFMA-1830901 and the Simons Foundation and the Henri Seydoux Fund.

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