Journal
IFAC PAPERSONLINE
Volume 51, Issue 11, Pages 716-721Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ifacol.2018.08.403
Keywords
Mobile robot; 3D printing; Accuracy improvement; Automated Guided Vehicle; Foam Additive Manufacturing; Building Information Modeling
Categories
Funding
- BA Systems
- Bouygues Batiment
- LafargeHolcim
- CSTB
- CNRS
- Nantes University
- SATT Ouest Valorisation
- Caisse des depots
- Nantes Metropole
- Nantes metropole Habitat
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Currently, building construction is beginning to consider the use of 3D printing which can be considered as an evolution or modernization of its proven traditional techniques. A new process based on FAM approach (Foam Additive Manufacturing) has been patented by Nantes University. The wall manufacturing is based on the laying of two polyurethane foam beads which plays the role of framework for the concrete and inside and outside thermal insulation. To perform the laying, the development of a robotic architecture integrates an automated guided vehicle and an industrial robot located on it. The printing environment is complex: printed walls, pipes inside the concrete slab, robot hoses, house form complexity, vertical steel reinforcement. Also, the concrete slab inspection shows a flatness defect close to 25mm (regular defect) which impacts the robot accuracy. The objective is then to find the best location for an AGV (Automated Guided Vehicle) in order to perform the printing in the best conditions. After a comparison on current mobile robot architecture for house manufacturing, we present the location of the mobile robot in its environment where, during the first day, the navigation is analysed and then improved to perform the house printing. Via the homogeneous transformation, we outline the Direct Geometrical Model and our implementation to improve the accuracy of the robotic system. Finally, we present the manufacturing principle and the final result: a habitable house by 3D printing. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
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