A novel robot co-worker system for paint factories without the need of existing robotic infrastructure |
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| Affiliation: | 1. School of Modern Post (School of Automation), Beijing University of Posts and Telecommunications, Beijing, China;2. School of Mechanical Engineering and Automation, Beihang University, Beijing, China;3. Department of Digital Machining, Sandvik Coromant, Stockholm, Sweden;4. COMAC Beijing Aircraft Technology Research Institute, Beijing, China;5. Department of Production Engineering, KTH Royal Institute of Technology, Stockholm, Sweden;1. Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control, School of Mechanical Engineering, Tianjin University of Technology, Tianjin 300384, China;2. National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology), China;3. Key laboratory of Modern Mechanisms and Equipment Design of The State Ministry of Education, Tianjin University, Tianjin 300072, China;1. School of Mechanical Engineering and Automation, Northeastern University, No. 3-11, Wenhua Road, Heping District, Shenyang, Zip code: 110819, People''s Republic of China;2. Liaoning Provincial Key Laboratory of High-end Equipment Intelligent Design and Manufacturing Technology, Northeastern University, No. 3-11, Wen hua Road, He ping District, Shenyang, Zip code: 110819, People''s Republic of China;1. Department of Mechanical Engineering, Politecnico di Milano, via La Masa 1, 20133 Milano, Italy;2. GKN Aerospace, Kongsberg, Norway;1. University of Zagreb Faculty of Electrical Engineering and Computing, Department of Control and Computer Engineering, Laboratory for Autonomous Systems and Mobile Robotics, Unska 3, HR-10000, Zagreb, Croatia;2. Karlsruhe Institute of Technology, Institute for Anthropomatics and Robotics, Intelligent Process Automation and Robotics Lab, Kaiserstraße 12, DE-76131, Karlsruhe, Germany |
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| Abstract: | This paper presents a human–robot co-working system to be applied to industrial tasks such as the production line of a paint factory. The aim is to optimize the picking task with respect to manual operation in a paint factory. The use of an agile autonomous robot co-worker reduces the time in the picking process of materials, and the reduction of the exposure time to raw materials of the worker improves the human safety. Moreover, the process supervision is also improved thanks to a better traceability of the whole process. The whole system consists of a manufacturing process management system, an autonomous navigation system, and a people detection and tracking system. The localization module does not require the installation of reflectors or visual markers for robot operation, significantly simplifying the system deployment in a factory. The robot is able to respond to changing environmental conditions such as people, moving forklifts or unmapped static obstacles like pallets or boxes. The system is not tied to specific manufacturing orders. It is fully integrated with the manufacturing process management system and it can process all possible orders as long as their components are placed into the warehouse. Real experiments to validate the system have been performed in a paint factory by a real holonomic platform and a worker. The results are promising from the evaluation of performance indicators such as exposure time of the worker to raw materials, automation of the process, robust and safe navigation, and the assessment of the end-user. |
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| Keywords: | Warehouse automation Autonomous robot co-worker People detection and tracking Field robotics |
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