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LearningGripper:
self-learning gripper system for positioning round objects
Production in a state of flux
Networking is omnipresent in the vision of future production. Cen-
tralised plant control will continue its evolutionary development
and, at the same time, greater use will be made of the opportuni-
ties afforded by decentralised self-organisation. Equipment and
systems will understand their environments in the future and
communicate with each other.
Self-configuring and self-learning systems will lastingly shape
production processes in the factories of tomorrow. Their develop-
ment will lead to quick, simple and reliable commissioning. With
the help of machine learning capabilities, independent execution
of complex tasks will be made possible without the need for
extensive programming.
As a global manufacturer of pneumatic and electric automation
technology, Festo’s core business is helping to shape the factory
of the future and providing its customers with tailor-made solu-
tions to achieve this – as either complete production systems or
individual components.
New perspectives offered by nature
Nature frequently provides us with astonishing inspiration and
new approaches to solutions. This is why Festo founded the
Bionic Learning Network. In collaboration with renowned universi-
ties, institutes and R&D companies, Festo is closely involved
with the testing of possible gripper technologies based on bio-
logical models.
The best known example is the FinGripper which is now part of
Festo’s product range as the adaptive gripper (DHDG). In order to
grip objects, it exploits a natural attribute of the fish fin. Instead
of bending away when pressure is applied at the side, it wraps
around the pressure point. The NanoForceGripper uses the same
effect to ensure that the adhesive gecko film is gently released
from the gripped goods, with minimal energy consumption. The
PowerGripper imitates the kinematic system of a bird’s beak.
The developers have succeeded in taking things one step further
with the LearningGripper as an R&D model: a gripper which is
capable of learning, thus showing great potential for the future.
FinGripper:
adaptive gripping based on the
principle of the fish tail fin
PowerGripper:
optimised force-weight ratio
thanks to bird beak kinematics
NanoForceGripper:
energy-efficient gripping
using the gecko as a model