Network for knowledge and innovation

In a globalized, networked world, it is important to be open to the ideas of others and to promote the active sharing of knowledge. That is why we are involved in a variety of collaborations with universities, research institutes, and industrial partners. We bring our strength and our expertise to this innovation ecosystem, and in return we benefit from the perspectives and the know-how of our partners. This ensures a continuous inflow of knowledge in areas that go beyond the boundaries of our own company. By working together, we can examine challenges and possible solutions in a wider context – and set new standards within the sector. Below are some examples of the technological fields in which we work, and the partners we work with.

Fifteen project partners are working on a technology tool kit for reliable industrial communications infrastructure that they hope to have ready by mid-2020. Key technologies from areas such as 5G, cloud computing, and industrial monitoring will feature in this endeavor. KION's project partners come from industry and research and include household names such as Bosch, Nokia, Telekom, and Siemens, as well as several universities. This is a beacon project that is supported by the German Federal Ministry for Economic Affairs and Energy.

The project name is an acronym of the project partners: Q stands for Audi Quattro, B for automation specialist Bär, the two Is are for two institutes – the Institute of Material Handling and Logistics (IFL) and the Institute of Intelligent Process Automation and Robotics (IPR) – and the K stands for the KION Group. Their shared objective is to combine the technology of autonomous systems with human capabilities in a way that maximizes the benefits of both. The QBIIK is a system that can position itself within the warehouse, navigate to its destination, and reach for the required goods – all completely autonomously.
The reaching operation of the autonomous robot is aided by various sensors. As well as a 3D camera, there are tactile proximity sensors that explore the area surrounding the manipulator and ensure that items can be grasped and stored without any collision.

If something in the warehouse environment changes and the system is unable to recognize or grasp the goods, it will request human assistance. Using a human-machine interface connected via the cloud, the spatial distance can be bridged, allowing an operator to briefly take control and carry out the process of recognition and grasping remotely. QBIIK learns from its human counterparts and carries out the work steps independently from then on.

The project is supported by the German Federal Ministry for Economic Affairs and Energy.

Digital maps of production halls and warehouses require an industry-wide standard. The KION Group, in the shape of the STILL EMEA Operating Unit, has joined forces in a research project with the sensor manufacturers Pepperl+Fuchs and Sick, several research institutions and universities, and Jungheinrich with the aim of making maps easy to produce and adaptable so that they can be used as the basis for further automation projects.

In 2018, the KION Group took part in a benchmarking project led by the Fraunhofer Institute for Production Technology (IPT) and RWTH Aachen University. The project examined the evolution of radical innovations in the early development phases – from the initial idea to the delivery of a small-scale production run for real customers. The results revealed that the KION Group, Daimler Trucks, Claas KGaA mbH, Deutz AG, and Voith Paper are the top five companies when it comes to best practice in the area of 'agile invention'.

In the not-so-distant future, self-driving vehicles are going to be expected to find their way around the warehouse autonomously. In a research project with the University of Freiburg, the KION Group is already preparing for this moment by working on sharpening the optic nerves in a vehicle’s camera with artificial intelligence models which require as few parameters as possible to accomplish the recognition of objects. Deep learning – or hierarchical learning – is part of a broader family of machine learning methods based on artificial neural networks which can mathematically solve tasks that humans "intuitively" solve.

"Deep PTL" is the name of the join research effort, a combination of deep learning and the acronym for production, transport and logistics. The cooperation got underway in September 2018 and is anticipated to last through early 2022.

Is it a human or a shelf? Helping AGV's to 'see' better

Read our article about this research project

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Executive and Supervisory Board of KION GROUP AG.

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