Harvard-Developed Tentacle Robot Can Gently Grasp Fragile Objects
By HARVARD JOHN A. PAULSON SCHOOL
OF ENGINEERING AND APPLIED SCIENCES
Close-up of the gripper’s filaments wrapping around an object. A jellyfish-like soft gripper simulates the mechanics of curly hair. Credit: Harvard Microrobotics Lab/Harvard SEAS
Most of today’s robotic grippers use a combination of the
operator’s skill and embedded sensors, intricate feedback loops, or
cutting-edge machine-learning algorithms to grasp fragile or irregularly shaped
items. However, scientists at Harvard’s John A. Paulson School of Engineering and Applied Sciences
(SEAS) have shown that there is a simpler method.
Taking inspiration from nature, scientists created a new type of
soft, robotic gripper that employs a network of thin tentacles to entangle and
grab objects, similar to how jellyfish collect their prey. Individual
filaments, or tentacles, are not very strong on their own. However, when used
as a group, the filaments can firmly grip and hold things of all shapes and
sizes. The gripper doesn’t need sensing, planning, or feedback control; it
relies on simple inflation to wrap around items.
The study was published in the journal Proceedings of the National Academy of Sciences (PNAS).
“With this research, we wanted to reimagine how we interact with objects,” said Kaitlyn Becker, former graduate student and postdoctoral fellow at SEAS and first author of the paper. “By taking advantage of the natural compliance of soft robotics and enhancing it with a compliant structure, we designed a gripper that is greater than the sum of its parts and a grasping strategy that can adapt to a range of complex objects with minimal planning and perception.”
Becker is currently an Assistant Professor of Mechanical
Engineering at MIT.
The gripper’s strength and adaptability come from its ability to
entangle itself with the object it is attempting to grasp. 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 pigtail or
like straightened hair on a rainy day.
The curls knot and entangle with each other and the object, with each entanglement increasing the strength of the hold. While the collective hold is strong, each contact is individually weak and won’t damage even the most fragile object. To release the object, the filaments are simply depressurized.
The researchers used simulations and experiments to test the
efficacy of the gripper, picking up a range of objects, including various
houseplants and toys. The gripper could be used in real-world applications to
grasp soft fruits and vegetables for agricultural production and distribution,
delicate tissue in medical settings, and even irregularly shaped objects in
warehouses, such as glassware.
This new approach to grasping combines Professor L. Mahadevan’s
research on the topological mechanics of entangled filaments with Professor
Robert Wood’s research on soft robotic grippers.
“Entanglement enables each highly compliant filament to conform
locally with a target object leading to a secure but gentle topological grasp
that is relatively independent of the details of the nature of the contact,”
said Mahadevan, the Lola England de Valpine Professor of Applied Mathematics in
SEAS, and of Organismic and Evolutionary Biology, and Physics in FAS and
co-corresponding author of the paper.
“This new approach to robotic grasping complements existing
solutions by replacing simple, traditional grippers that require complex
control strategies with extremely compliant, and morphologically complex
filaments that can operate with very simple control,” said Wood, the Harry
Lewis and Marlyn McGrath Professor of Engineering and Applied Sciences and
co-corresponding author of the paper. “This approach expands the range of
what’s possible to pick up with robotic grippers.”
Reference: “Active entanglement enables stochastic, topological
grasping” by Kaitlyn Becker, Clark Teeple, Nicholas Charles, Yeonsu Jung,
Daniel Baum, James C. Weaver, L. Mahadevan and Robert Wood, 10 October
2022, Proceedings of the National Academy of Sciences.
DOI:
10.1073/pnas.2209819119
The study was funded by the Office of Naval Research, the National
Science Foundation, the Simons Foundation, and the Henri Seydoux Fund.