From 1 to 5 April 2019, Festo will be showcasing the new Future and Bionic Concepts along with further product innovations for factory and process automation at its main booth at Hannover Messe.
copyright by www.ien.eu
From 1 to 5 April 2019, Festo will be showcasing the new Future and Bionic Concepts along with further product innovations for factory and process automation at its main booth at Hannover Messe.
How does anticipatory machine maintenance work? How is artificial intelligence advancing automation? And how can Germany as an industrial location benefit from these activities? Answers to these questions were provided by Dr Frank Melzer , Member of the Management Board Product and Technology Management; Tanja Krüger, Managing Director of Resolto Informatik GmbH (a company of the Festo Group); Dr Elias Knubben, Head of Corporate Research and Innovation; and Dionysios Satikidis, Digital Strategy and Business Model.
Newborn babies and deep learning
Will automation become autonomous thanks to artificial intelligence? This question was put forward by Dionysios Satikidis , a software engineer and expert in artificial intelligence , in his opening presentation. He used the example of newborn babies to explain various learning methods in artificial intelligence that can ultimately lead to autonomy. Babies first of all perceive objects, and this enables them to recognise differences – which is exactly what algorithms can do in machine learning , for example when recognising anomalies or clusters.
When systems also remember what they perceive, this is known as deep learning . They can then recognise objects or understand speech. If this memory is connected with a task and practised, one then speaks of reinforcement learning. In this case, it involves learning a skill. “Once artificial intelligence finally becomes capable of transferring acquired knowledge to unknown tasks, we will have arrived at transfer learning, which in the final stage can lead to autonomous automation,” said the expert with a view to the future.
BionicSoftHand – a pneumatic gripper with AI based on the human model
Dr Elias Knubben showed an example of how Festo can use reinforcement learning for automation engineering: the Head of Corporate Research and Innovation presented the BionicSoftHand, the new Future Concept from the field of bionics. The natural model for this gripper is the human hand. The BionicSoftHand is pneumatically operated so that it can interact safely and directly with people. Its fingers consist of flexible bellows structures with air chambers and other soft materials. This makes it light, flexible, adaptable and sensitive, yet capable of exerting strong forces. By means of artificial intelligence, the bionic robot hand learns to independently solve gripping and turning tasks similar to the human hand in interaction with the brain (see press release on the 2019 bionic projects).[…]
read more – copyright by www.ien.eu
From 1 to 5 April 2019, Festo will be showcasing the new Future and Bionic Concepts along with further product innovations for factory and process automation at its main booth at Hannover Messe.
copyright by www.ien.eu
How does anticipatory machine maintenance work? How is artificial intelligence advancing automation? And how can Germany as an industrial location benefit from these activities? Answers to these questions were provided by Dr Frank Melzer , Member of the Management Board Product and Technology Management; Tanja Krüger, Managing Director of Resolto Informatik GmbH (a company of the Festo Group); Dr Elias Knubben, Head of Corporate Research and Innovation; and Dionysios Satikidis, Digital Strategy and Business Model.
Newborn babies and deep learning
Will automation become autonomous thanks to artificial intelligence? This question was put forward by Dionysios Satikidis , a software engineer and expert in artificial intelligence , in his opening presentation. He used the example of newborn babies to explain various learning methods in artificial intelligence that can ultimately lead to autonomy. Babies first of all perceive objects, and this enables them to recognise differences – which is exactly what algorithms can do in machine learning , for example when recognising anomalies or clusters.
When systems also remember what they perceive, this is known as deep learning . They can then recognise objects or understand speech. If this memory is connected with a task and practised, one then speaks of reinforcement learning. In this case, it involves learning a skill. “Once artificial intelligence finally becomes capable of transferring acquired knowledge to unknown tasks, we will have arrived at transfer learning, which in the final stage can lead to autonomous automation,” said the expert with a view to the future.
BionicSoftHand – a pneumatic gripper with AI based on the human model
Dr Elias Knubben showed an example of how Festo can use reinforcement learning for automation engineering: the Head of Corporate Research and Innovation presented the BionicSoftHand, the new Future Concept from the field of bionics. The natural model for this gripper is the human hand. The BionicSoftHand is pneumatically operated so that it can interact safely and directly with people. Its fingers consist of flexible bellows structures with air chambers and other soft materials. This makes it light, flexible, adaptable and sensitive, yet capable of exerting strong forces. By means of artificial intelligence, the bionic robot hand learns to independently solve gripping and turning tasks similar to the human hand in interaction with the brain (see press release on the 2019 bionic projects).[…]
read more – copyright by www.ien.eu
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