KION Group starts research project ARIBIC focused on digital twins of warehouses

The KION Group and its cooperating partners LeddarTech, Karlsruhe Institute of Technology (KIT) and the STARS Lab at the University of Toronto have started research project “ARIBIC.” The acronym stands for “Artificial Intelligence-Based Indoor Cartography,” an effort focused on continuous data evaluation and creating a real-time digital twin of a warehouse or a production environment. This is a further step to enhance already existing digital twin solutions as well as simulation and emulation platforms of KION Group, the company stated in an announcement today.

German and Canadian government agencies are convinced of the project’s potential and provided research budgets. The research project is one of several cooperations KION Group has already started with different partners.

Automated guided vehicles are already being used on a large scale in warehouses and production facilities today. With modern sensor technology such as laser scanners and cameras, they find their way safely through racks, production lines, and warehouses. In the process, they continuously generate a considerable amount of data about the environment in which they move. However, this data is usually not yet systematically processed and lies fallow. What if the full potential of these bits and bytes could be exploited? Systematic data processing is precisely where the ARIBIC digitization project implemented by the STILL, a KION Group subsidiary supplying industrial trucks and related services, comes in.

“The data collected by the sensors on the vehicles are used to create high-quality, high-resolution 3D maps of warehouses or production facilities. The objective is to create a digital twin of the environment, thus enabling relevant information to be displayed and shared in real time,” says Dr. Henry Puhl, Chief Technology Officer of the KION Group.

“Today, many industrial companies apply so-called post-digitization of their production environments and warehouses. However, this only captures a snapshot. The research results of the ARIBIC project go further by enabling continuous data evaluation,” adds Dr. Joachim Tödter, Senior Director Technology & Innovation at the KION Group.

The data generated by the sensor system is sent to the vehicle, processed there, and sent to the ARIBIC cloud platform. The sensor data is then processed further in the cloud. The advantages of this solution are obvious: firstly, the user receives live information about object locations via tracking & tracing. This information makes it possible, for example, to simulate the routes of vehicles and thus optimize processes in the warehouse and production. At the same time, intelligent digital services offer the advantage that anomalies such as a blocked route are detected and reported. The consistent evaluation of the data shall ultimately lead to a warehouse’s entire structure being optimized and adapted, KION stated.

“KION is already in a position to implement such techniques: ARIBIC provides an important progress in adding computational perception capabilities. Those leverage edge intelligence and open the door to many applications ranging from more efficient design of flexible automation and mobile robotic operations for the warehouse of tomorrow to inspection and detection of warehouse material placement and distribution that is critical to workflow optimization for many logistics operations,” says Hamid Montazeri, Senior Vice President, Software & Digital Solutions Development at Dematic, a KION Group subsidiary offering supply chain solutions and related services.

The idea for the research project originated in the summer of 2019 in the Technology & Innovation department of KION Group. In preparing the funding application, cross-border partners from industry and research were recruited: LeddarTech, a leading company in environmental sensing solutions for autonomous vehicles and advanced driver assistance systems headquartered in the Canadian province of Québec is significantly involved in the project. The contribution of LeddarTech to the project will be centered around the sensor system, which leverages their technological expertise in sensing, perception, and sensor fusion for mobility applications.

“When KION approached us and explained their vision for ARIBIC, it was clear from the beginning that we had to be part of this project,” said LeddarTech’s Chief Technology Officer, Pierre Olivier. “Not only does it allow us to collaborate with an industry leader as well as with two renowned labs, it also represents a perfect opportunity to leverage LeddarTech’s strong expertise in sensing, in integrating sensing platforms on vehicles, and in maximizing the potential from the available sensor data,” added Mr. Olivier.

Research partners are the Karlsruhe Institute of Technology (KIT) and the STARS Lab at the University of Toronto, both leading institutes in artificial intelligence and robotics. As part of the ARIBIC project, the STARS Lab will develop methods to extract detailed semantic information (object labels) from large 3D maps of warehouse environments. “ARIBIC is a perfect project for us to collaborate on current research topics with international partners and to establish new industry relationships”, says Prof. Jonathan Kelly, head of the STARS Lab.

The Department of Robotics and Interactive Systems of the Institute of Materials Handling and Logistics Systems (IFL) at the KIT researches future-oriented robotics solutions with practical benefits for its users. The field of research includes topics such as mapping and localization of mobile robots, computer vision, automated grasping and placing of various articles, and the development of intuitive human-machine interaction. Within the ARIBIC Project the IFL focusses on the detection of intralogistics elements in 3D sensor data, as well as the merging of maps in multi-robot scenarios. “We are very much looking forward to the opportunity for international cooperation,” states Prof. Kai Furmans, head of IFL.

At the beginning of 2021, the project was approved by the National Research Council of Canada Industrial Research Assistance Program (NRC IRAP) and the German Federal Ministry for Economic Affairs and Energy (BMWi), and funding was secured. The project is scheduled for completion in the fourth quarter of 2023.