2021/06/29
ID: 3766

Better gripping with intelligent picking robots

Researchers from Germany and Canada work on new AI methods for picking robots

Production, warehouse, shipping - where goods are produced, stored, sorted or packed, picking also takes place. This means that several individual goods are removed from storage units such as boxes or cartons and reassembled. With the FLAIROP (Federated Learning for Robot Picking) project Festo and researchers from the Karlsruhe Institute of Technology (KIT), together with partners from Canada, want to make picking robots smarter using distributed AI methods. To do this, they are investigating how to use training data from multiple stations, from multiple plants, or even companies without requiring participants to hand over sensitive company data. 

We are investigating how the most versatile training data possible from multiple locations can be used to develop more robust and efficient solutions using artificial intelligence algorithms than with data from just one robot," says Jonathan Auberle from the Institute of Material Handling and Logistics (IFL) at KIT. In the process, items are further processed by autonomous robots at several picking stations by means of gripping and transferring. At the various stations, the robots are trained with very different articles. At the end, they should be able to grasp articles from other stations that they have not yet learned about. "Through the approach of federated learning, we balance data diversity and data security in an industrial environment," says the expert.

Powerful algorithms for industry and logistics 4.0

Until now, federated learning has been used predominantly in the medical sector for image analysis, where the protection of patient data is a particularly high priority. Consequently, there is no exchange of training data such as images or grasp points for training the artificial neural network. Only pieces of stored knowledge - the local weights of the neural network that tell how strongly one neuron is connected to another - are transferred to a central server. There, the weights from all stations are collected and optimized using various criteria. Then the improved version is played back to the local stations and the process repeats. The goal is to develop new, more powerful algorithms for the robust use of artificial intelligence for industry and Logistics 4.0 while complying with data protection guidelines.

In the FLAIROP research project, we are developing new ways for robots to learn from each other without sharing sensitive data and company secrets. This brings two major benefits: we protect our customers' data and we gain speed because the robots can take over many tasks more quickly. In this way, the collaborative robots can, for example, support production workers with repetitive, heavy, and tiring tasks”, explains Jan Seyler, Head of Advanced Develop. Analytics and Control at Festo SE & Co. KG

During the project, a total of four autonomous picking stations will be set up for training the robots: Two at the KIT Institute for Material Handling and Logistics (IFL) and two at the Festo SE company based in Esslingen am Neckar.

Start-up DarwinAI and University of Waterloo from Canada are further partners

“DarwinAI is thrilled to provide our Explainable (XAI) platform to the FLAIROP project and pleased to work with such esteemed Canadian and German academic organizations and our industry partner, Festo. We hope that our XAI technology will enable high-value human-in-the-loop processes for this exciting project, which represents an important facet of our offering alongside our novel approach to Federated Learning.  Having our roots in academic research, we are enthusiastic about this collaboration and the industrial benefits of our new approach for a range of manufacturing customers”, says Sheldon Fernandez, CEO, DarwinAI.

Festo è sia un attore globale che un'azienda indipendente a conduzione familiare con sede a Esslingen am Neckar in Germania. Fin dagli inizi Festo ha stabilito degli standard nella tecnologia dell'automazione industriale e nella formazione tecnica, contribuendo così allo sviluppo sostenibile dell'ambiente, dell'economia e della società. L'azienda fornisce tecnologia di automazione pneumatica ed elettrica a 300.000 clienti dell'automazione di fabbrica e di processo in oltre 35 industrie. Il settore LifeTech con la tecnologia medica e l'automazione di laboratorio sta diventando sempre più importante. I prodotti e i servizi sono disponibili in 176 paesi del mondo. In tutto il mondo, circa 20.000 dipendenti in 61 paesi con oltre 250 filiali hanno generato un fatturato di circa 2,84 miliardi di euro nel 2020. Di questo, circa l'8% viene investito annualmente in ricerca e sviluppo. Nell'azienda che apprende, le misure di formazione e sviluppo rappresentano l'1,5% del fatturato. Festo Didactic SE è un fornitore leader di istruzione e formazione tecnica e offre ai suoi clienti in tutto il mondo soluzioni complete di apprendimento digitale e fisico nell'ambiente industriale.

© Festo SE & Co. KG
FLAIROP
Nel progetto di ricerca FLAIROP, i robot vengono addestrati con diversi articoli in luoghi separati. I pesi di tutte le stazioni vengono raccolti e ottimizzati utilizzando vari criteri. Quindi la versione migliorata viene riprodotta alle stazioni...