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Self-learning:
The LearningGripper’s four pneumatic fingers ...
... position the ball until the correct side is at the top.
Gripping and positioning through independent learning
The LearningGripper from Festo looks like an abstract form of
the human hand. The four fingers of the gripper are driven by
12 pneumatic bellows actuators with low-level pressurisation.
Thanks to the process of machine learning, it is able to teach itself
to carry out complex actions such as, for example, gripping and
positioning an object.
Smart and intuitive – the LearningGripper principle
In concrete terms, the gripper assigns itself the task of turning a
ball so that a particular point of the ball points upwards. Based on
the trial-and-error principle, the intelligent system thus acquires
the motion sequences required to achieve this. The more time it
spends learning, the more reliably it completes its task.
Reduced programming effort
With its LearningGripper, Festo demonstrates how, in the future,
systems will be able to execute complex tasks independently
without time-consuming programming. When the conventional
procedure is used, the developer has to assign a separate action
to each possible status of the fingers and the ball.
Only the elementary actions and possible positions of the
LearningGripper’s fingers, as well as the function for feedback
from the environment, are defined in advance. The gripper is only
told what to do, but not how to do it. The complex motion strategy
required for this is developed independently by the gripper’s
learning algorithms – without any further programming.
Knowledge transfer to other grippers
By transferring the strategy from one gripper to another, the
second gripper is provided with the first gripper’s previous know
-
ledge which it can use to develop its own strategy more efficiently.
The more similar the hardware is for the two grippers, the more
productive the transfer is. The more previous knowledge is
available, the more quickly the system becomes fully functional.
Potential for the factory of the future
With this principle, self-learning systems like the LearningGripper
could be built into future production lines and autonomously op-
timise their own performance. This is why Festo is already closely
involved with machine learning capabilities.
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Imitation:
As is also the case with its example in nature ...
... the hand helps the LearningGripper to learn.
Flexible:
Three degrees of freedom provide each finger with the basic func
tions of the human index finger.
Pneumatic bellows-kinematic system
The LearningGripper reduces the human hand to four abstract fin
-
gers, each of which possesses three degrees of freedom and the
basic functions of the human index finger. Each degree of freedom
has an angle range of ± 25°. The gripper’s kinematic system is
operated with low pressure between 2.5 and 3.5 bar.
Highly complex coordination
Retracting, advancing or maintaining its current position – by
using proportional valves (MPYE) and the pressure transmitter
(SPTE) from Festo, the 12 pneumatic bellows structures can be
moved to any required intermediate or end position. Each finger
can thus be moved in three directions. Just in its initial state, the
hand has a total of 3¹² actions to choose from in order to reposi-
tion the ball.
Thanks to intelligent coordination of the fingers and the flexible
polyamide bellows structure, the kinematic system is pliable and
can move freely. It can reliably grip, lift and rotate even the most
sensitive objects – just like its example in nature.
The human hand is a highly versatile tool. It can be very powerful,
as well as extremely delicate and sensitive. Many of the character-
istics exhibited by objects are best appreciated with the hands
for example, shape, size and texture, as well as temperature and
weight.
Gripping and learning – intelligent interaction
There are theories stating that human beings are only as intelli-
gent as they are because the hand can carry out so many complex
tasks. Babies start gripping objects very early – for example, their
mothers’ fingers. As soon we learn to correctly grasp an object,
we can turn it and look at it from all sides. Only this enables the
human mind to reconstruct a three-dimensional object. The hand
is thus a learning tool for the human being as well.
And, people learn in two different ways: explicitly and implicitly.
In the case of explicit learning, an exact pattern is provided which
has to be imitated or learned. Implicit learning is understood as
the unconscious or playful acquisition of skills and knowledge
while an activity is being carried out.