Method for Motion planning with time and location-optimised provision for autonomous mobile robots in an order-picking system

• Applicant: Professorin Dr.-Ing. Alice Kirchheim
• Subject Area: Production Systems, Operations Management, Quality Management and Factory Planning ; Traffic and Transport Systems, Intelligent and Automated Traffic
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 557637468

During item grasping in order picking processes, a supply unit, a collection unit and a picker meet at a specific location. In the state of the art, one of these material flow elements remains stationary. The applicant developed a concept for a novel picking principle in which all three material flow elements are mobile and automated. This introduces new challenges for motion planning. In the proposed research project, the supply unit and the picking unit are placed on different autonomous mobile robots (AMR), one of which is also equipped with a suitable gripping system. The picking position is dynamically calculated during runtime. There already exist a large number of motion planning algorithms that calculate collision-free trajectories for a fleet of AMR. None of these algorithms are suitable for the problem at hand. There are procedures in which meeting points and meeting times are taken into account. However, these points are defined statically in advance. In the field of vehicle routing exist many algorithms that take time windows or meeting points into account. None of these procedures takes collision-free motion into account or changes the order sequence. The complexity of this task leads to the central research question. How can the essential requirements for motion planning of automated, moving material flow elements be implemented in an algorithm that also takes operational logistics requirements into account, such as limited computing time? The aim of the research project is the development and validation of a suitable method and the comparison to already existing algorithms.

• DFG Programme: Research Grants