Fraunhofer Institute for Material Flow and Logistics IMLLaser-based guidance system for sustainable logistics
From idea to MVP in just six months - Fraunhofer employees create a laser-based system to guide employees through processes. The system is tested in real operational settings.
Innovative laser-based guidance system for efficient logistics
One system – endless possibilities
LARS is an innovative laser-based guidance system designed to assist employees in intralogistics warehouses with their daily tasks. With the ability to dynamically and flexibly project personalized information such as routes, storage locations, signs, and order numbers, LARS optimizes operational efficiency and enhances workplace appeal.
LARS enables sustainable warehouse operations, allowing knowledge to be easily conveyed through its projections during initial training or when processes change. There is no need for floor markings, eliminating the requirement for costly renewals and contributing to ecological sustainability.
This ergonomic and scalable solution guides employees precisely through work processes, eliminating the need to search for items or decide where to place them – everything is indicated by the laser projection. LARS is safe for the eyes, and employees do not require any additional equipment to operate it.
Moreover, LARS is intuitive and can be tailored to meet the specific needs of employees, maximizing efficiency in operations. The system places a strong emphasis on people and their needs, promoting inclusion and diversity in the workplace, even in complex environments like warehouses. The usage of light to deliver information makes operation language-independent and comprehensible to all employees.
Developed in 2024 as part of the “Competence Center Logistics and IT” initiative, LARS offers a flexible foundation that can be adapted for various applications. A successful two-week test in a real operational setting has convincingly demonstrated LARS's effectiveness. The LARS team will next focus on enhancing the system's learning capabilities to further improve adaptability and efficiency.
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