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 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.