Adaptive robotic manufacturing using higher order knowledge systems
Despite a well-understood potential to increase productivity of the global construction industry and sustained, international research efforts in recent years, wide-scale adoption of robotic technology currently remains elusive in the industry. As part of a larger industrial research effort to incre...
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| Veröffentlicht in: | Automation in construction 2021-07, Vol.127, p.103702, Article 103702 |
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| container_title | Automation in construction |
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| creator | Neythalath, Narendrakrishnan Søndergaard, Asbjørn Bærentzen, Jakob Andreas |
| description | Despite a well-understood potential to increase productivity of the global construction industry and sustained, international research efforts in recent years, wide-scale adoption of robotic technology currently remains elusive in the industry. As part of a larger industrial research effort to increase the efficiency of automation technologies within construction, this paper proposes a novel multi-layered knowledge encapsulation model to enable low-cost development of highly diverse robotic control applications within a parametric manufacturing paradigm. The effectiveness of proposed theoretical framework has been validated by developing multiple industrial applications and resulted in almost 40% reduction in development time.
•Process innovation and optimization.•Affordable robotic solutions for construction.•Construction 4.0 strategy. |
| doi_str_mv | 10.1016/j.autcon.2021.103702 |
| format | Article |
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| ispartof | Automation in construction, 2021-07, Vol.127, p.103702, Article 103702 |
| issn | 0926-5805 1872-7891 |
| language | eng |
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| source | Access via ScienceDirect (Elsevier) |
| subjects | Automation Construction 4.0 Construction industry Industrial applications Industrial research Industrial robots Multilayers Process optimization Robot control Robotics |
| title | Adaptive robotic manufacturing using higher order knowledge systems |
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