Intralogistics specialist Linde Material Handling (MH) and the Aschaffenburg University of Applied Sciences (UAS) presented the results of the research project “KAnIS – Cooperative Autonomous Intralogistics Systems” with live demonstrations on the test site at the Linde plant in Aschaffenburg on December 5, 2023. In several subprojects, solutions were developed for the demanding applications of autonomous counterbalanced forklifts, which transport loads both indoors and outdoors. One focus was on the cooperative behavior of these vehicles that exchange information in real time via a 5G network and an edge server and can warn each other of obstacles. The project, which ran for almost four years, was funded with approximately 2.8 million euros as part of the Free State of Bavaria’s “Information and Communication Technology” R&D program.
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Starting next year, the autonomous counterweight forklifts are to be further developed and tested in order to take on specific material flow tasks at the Linde Material Handling plant in the future. One of these is the transport of driver's canopies, which are transported on special load carriers from the pre-assembly to the main assembly lines.
“Autonomous vehicles will gradually take over more and more transport tasks,” asserts Stefan Prokosch, initiator of the KAnIS project at Linde MH. As a technology leader in the industry, the intralogistics specialist wants to make the benefits of autonomous vehicles available to customers who use counterbalanced forklifts to transport goods or load and unload heavy trucks. “However, the requirements for forklifts operating in outdoor areas are much higher than those for purely indoor vehicles. These include the ability to operate on inclines and gradients, the presence of a significantly higher volume of people and traffic and different weather influences and temperature conditions that need to be taken into account,” Prokosch explains. “Thanks to the joint research work with Aschaffenburg UAS, we have been able to develop viable solutions for these complex requirements. Once the project is completed, these findings will form an essential basis for further development projects.”
The overall goal of the project was to investigate how the cooperative behavior of networked, autonomous vehicles can improve operational reliability and handling performance. To solve this broad task, several subprojects were formed to address vehicle location, regulation and control as well as forklift cooperation, load carrier recognition, the impact of weather influences, predictive maintenance, route optimization and automatic load management.
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Prof. Dr. Hans-Georg Stark, Project Manager KAnIS, Faculty of Engineering at Aschaffenburg UAS
“For the university, the KAnIS project was a very complex, interdisciplinary research project. Ten professors and numerous research assistants and students were involved,” summarized Prof. Dr. Hans-Georg Stark, Project Manager KAnIS, Faculty of Engineering at Aschaffenburg UAS, during the event.
„Both project partners have benefited greatly from the intensive exchange between Aschaffenburg UAS’s scientific research activities and Linde MH’s many years of expertise in vehicle development.“
Four Linde E20, E25 and E30 electric counterbalanced trucks with a load capacity of 2.0 to 3.0 tons were automated and equipped with electrohydraulic steering (Linde Steer Control), the Linde Safety Pilot assistance system with electronic load diagram and an integrated fork positioner.
„The practical implementation of the research results was an important aspect for both Linde MH and Aschaffenburg UAS.“
Starting next year, the vehicles are to be further developed and tested so that they can perform four specific material handling tasks in the future. These include the transport of wire mesh crates and of pallets containing batteries, and the relocation of vehicle frames and overhead guards, which have to be transported on special load carriers from pre-assembly to the main assembly lines.
A particular focus of the research project was on the automated forklifts’ perception of their surroundings in order to ensure their reliable interaction with other road users. For this purpose, the vehicles are equipped with 3D scanners and HD cameras in addition to the sensors of the personal protection system. The camera data forms the basis for detecting and classifying objects with the help of AI algorithms and then locating them in order to adjust the vehicle’s speed and slow it down to a standstill.
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“The forklift trucks know what is happening around them because we teach them how to see,” explains Prof. Dr. Konrad Doll, Faculty of Engineering, TH AB.
Another key issue focused on critical situations that arise when people are in concealed areas that cannot be detected by the forklift’s sensors and approach the vehicle’s path of travel. This is where cooperation between the forklift trucks comes into play, because if another forklift is in the vicinity, it can provide the relevant information. However, this requires real-time transmission of the perception data. To achieve these low latencies, Linde has set up a private 5G network at the Aschaffenburg plant. The perception data is transmitted from the forklifts to an edge server, which uses the locally detected objects to create a global list of all detected objects and sends it back to the forklifts.
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Prof. Dr. Klaus Zindler, Vice President for Research and Transfer at Aschaffenburg UAS
“Fast wireless networks are the prerequisite for autonomous forklifts to be able to act cooperatively in outdoor areas and react to unforeseen traffic situations in real time,” emphasized Prof. Dr. Klaus Zindler, Vice President for Research and Transfer at Aschaffenburg UAS, at the event.
„Our goal is to develop general standards and algorithms using AI methods, which can then be flexibly applied to different vehicles and applications and continue to learn.“
Another work package looked at how to clean the near-ground optical sensors when they become dirty from water splashes in the rain or wet road surfaces. This is critical because if reliable object detection is no longer possible, the operator protection system will automatically bring the truck safely to a stop. To prevent this, the project team developed a cleaning system that uses compressed air to blow off any dirty water droplets that may have collected on the laser scanners.
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The autonomous charging of the forklift batteries was solved in the research project “KAnIS – Cooperative Autonomous Intralogistics Systems” by means of an AI-based robot that connects the charging plug to the forklift’s charging socket.
Another project team investigated possible solutions for autonomous charging of the forklift batteries. The result was in favor of an AI-based robot that connects the charging plug to the forklift’s charging socket. The rear of the truck was modified accordingly and an automatically operated charging flap was added to protect the charging socket from dirt and splash water.
Picture at the top: One focus of the research project “KAnIS – Cooperative Autonomous Intralogistics Systems” by Linde Material Handling and Technischer Hochschule Aschaffenburg focused on the cooperative behavior of autonomous forklifts: Via a 5G network and an edge server, the vehicles exchange information in real time and are able to alert themselves in critical situations. (Image source of all photos on this page: Linde Material Handling GmbH)
