18 SERVO 11.2015
BEND IT LIKE SILICONE
Robots have many strong suits, but delicacy traditionally hasn’t been one of them. Rigid limbs and digits make it
difficult for them to grasp, hold, and manipulate a range of
everyday objects without dropping or crushing them.
Recently, researchers from MIT’s Computer Science and
Artificial Intelligence Laboratory (CSAIL) have discovered
that the solution may be to turn to a substance more
commonly associated with new buildings and Silly Putty:
silicone. At a recent conference, researchers from CSAIL
Director Daniela Rus’ Distributed Robotics Lab
demonstrated a 3D printed robotic hand made out of
silicone rubber that can lift and handle objects as delicate as
an egg and as thin as a compact disc.
Just as impressively, its three fingers have special sensors
that can estimate the size and shape of an object accurately
enough to identify it from a set of multiple items.
“Robots are often limited in what they can do because of
how hard it is to interact with objects of different sizes and
materials,” Rus says. “Grasping is an important step in being
able to do useful tasks; with this work, we set out to develop
both the soft hands and the supporting control and planning
systems that make dynamic grasping possible.”
The gripper — which can pick up such items as a tennis
ball, a Rubik’s cube, and a Beanie Baby — is part of a larger
body of work out of Rus’ lab at CSAIL aimed at showing the
value of so-called “soft robots” made of unconventional
materials such as silicone, paper, and fiber.
Researchers say that soft robots have a number of
advantages over “hard” robots, including the ability to handle
irregularly-shaped objects, squeeze into tight spaces, and
readily recover from collisions.
“A robot with rigid hands will have much more trouble
with tasks like picking up an object,” graduate student, Bianca
Homberg said. “This is because it has to have a good model of
the object and spend a lot of time thinking about precisely
how it will perform the grasp.”
Soft robots represent an intriguing new alternative.
However, one downside to their extra flexibility (or
“compliance”) is that they often have difficulty accurately
measuring where an object is, or even if they have successfully
picked it up at all.
That’s where the CSAIL team’s “bend sensors” come in.
When the gripper hones in on an object, the fingers send
back location data based on their curvature. Using this data,
the robot can pick up an unknown object and compare it to
the existing clusters of data points that represent past
objects. With just three data points from a single grasp, the
robot’s algorithms can distinguish between objects as similar
in size as a cup and a lemonade bottle.
Researchers control the gripper via a series of pistons
that push pressurized air through the silicone fingers. The
pistons cause little bubbles to expand in the fingers, spurring
them to stretch and bend.
The hand can grip using two types of grasps: “enveloping
grasps,” where the object is entirely contained within the
gripper; and “pinch grasps,” where the object is held by the
tips of the fingers.
Outfitted for the popular Baxter manufacturing robot,
the gripper significantly outperformed Baxter’s
default gripper, which was unable to pick up a
CD or piece of paper, and was prone to
completely crushing items like a soda can.
Like Rus’ previous robotic arm, the fingers
are made of silicone rubber which was chosen
because of its qualities of being both relatively
stiff, but also flexible enough to expand with
the pressure from the pistons. Meanwhile, the
gripper’s interface and exterior finger molds
are 3D printed, which means the system will
work on virtually any robotic platform.
In the future, Rus says the team plans to
put more time into improving and adding more
sensors that will allow the gripper to identify a
wider variety of objects.
All of the objects grasped by MIT’s soft robotic hand. (Photo courtesy of MIT/CSAIL.)