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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.


adaptive gripping based on the

principle of the fish tail fin


optimised force-weight ratio

thanks to bird beak kinematics


energy-efficient gripping

using the gecko as a model