A Softer Touch
In the past few years, we’ve
seen a host of soft robots capable of
handling fragile items. Now, there’s
the DLR CLASH Hand: a clever
solution developed within the EU-Project Soma that can grasp various
fruits and vegetables. It has variable
stiffness which can be adapted to the
items the hand is going to pick up.
The CLASH hand has three
fingers and seven degrees of freedom.
It’s driven by eight motors. The
CLASH hand is made at a lower cost
thanks to its modular design and 3D
A main feature of this hand is that it can adapt the compliance of the fingers passively by changing the
pretension of the tendons. The compliance can be actively controlled similar to the DLR Hand II. For example, if
the hand grasps a mango, in the contact phase of the grasp the hand is very soft to reduce the contact forces and
increase the area of contact. In the lift phase, the hand increases the stiffness to get a stable grasp. This mechanism
is inspired by humans hands, where contraction of the muscle leads to an increased hand stiffness.
The DLR Hand II is an anthropomorphic dexterous grasping and manipulation system. It consists of four
identical fingers with four joints and three degrees of freedom each. An additional degree of freedom in the palm
allows the hand to adjust perfectly for either stable grasping or fine manipulation.
Gotta Hand it to You
Smart technology has given us a bunch of new
ways of interacting with the world around us. However,
we still only have two hands to use to get things
done. Well, maybe not for too much longer, if Italian
“augmented human” startup YouBionic has its way.
Having previously created a functioning bionic
hand for people without them, YouBionic has now
developed a Double Hand prosthesis, thereby offering
folks a maximum of four hands per person.
The 3D-printed hands are powered by an Arduino
and come mounted on a sort of gauntlet worn by
the operator. By moving individual fingers at different
speeds, the user can control each robotic hand
separately, making its fingers curl up into a fist or
This is achieved using mounted flex sensors to
identify movements and translate them into actions.
Due to the fact that you’re operating two hands with one, it’s not an exact case of mirroring movement,
but rather learning a series of new gestures, just as you would in order to learn how to operate a new
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