(E)Mulate Aec: A Gestural Pedagogy And Cloud-Based Collaborative Management Paradigm For On-Site Robotics In Construction

Vishal Vaidhyanathan
Twisha Raja

With about trillion in annual revenue – contributing to almost 6% of the global GDP [1], construction is one of the largest industries. However, with “Industry 4.0” causing paradigm shifts in other industries, construction has failed to be as efficient and technologically fluent. There have been issues of deteriorating labor productivity. Seventy percent of construction firms report they are having a hard time filling hourly craft positions that represent the bulk of the construction workforce [2]. This calls for on-site technological task automation to increase efficiency and abate workforce requirements. Robots in construction can be a great way to expedite and automate this process, as robotic construction is much more efficient in terms of operation and cost [3]. They can complement and augment conventional construction methods and craft-based fabrication with a high level of efficiency [4]. Robots in construction are being increasingly and ubiquitously used in large scale construction sites for performing several, different tasks in tandem, with humans. Programming these robots to perform specific tasks, however, is a highly skill demanding process, necessitating expertise in robotic coding and path planning. It is also impossible to robotically replicate specialized tasks with the same craftsmanship through conventional robot programming methods, as it is a mode of tacit knowledge transfer. Using several robots on-site for different tasks also calls for an efficient network and management system. This article discusses a new paradigm of teaching industrial robots with natural gestures, and a cloud-based management system to synchronize all robots on-site. A prototype was built to teach simple toolpaths to robots of different scales using gestures. All taught toolpaths were synchronized to all robots through the cloud-based interface. Scalability of toolpaths between two different robots (ABB IRB6640 and ABB IRB120) after cloud synchronization was demonstrated. It was concluded that gestural robot programming with cloud-sync, enabled expedited teaching times, and no skill-gap. REFERENCES 1. P. Gerbert, S. Castagnino, C. Rothballer, A. Renz, and R. Filitz, “Digital in Engineering and Construction: The Transformative Power of Building Information Modeling.”Anderson, R.E. Social impacts of computing: Codes of professional ethics. Social Science Computing Review 10, 2 (1992), 453-469. 2. “Seventy-Percent of Contractors Have a Hard Time Finding Qualified Craft Workers to Hire Amid Growing Construction Demand, National Survey Finds | Associated General Contractors of America.” [Online]. Available: [Accessed: 04-Feb-2020].Mather, B.D. Making up titles for conference papers. Ext. Abstracts CHI 2000, ACM Press (2000), 1-2. 3. B. García de Soto et al., “Productivity of digital fabrication in construction: Cost and time analysis of a robotically built wall,” Automation in Construction, vol. 92, pp. 297–311, Aug. 2018, doi: 10.1016/j.autcon. 2018.04.004. 4. M. Bechthold, “The Return of the Future: A Second Go at Robotic Construction,” Architectural Design, vol. 80, no. 4, pp. 116–121, Jul. 2010, doi: 10.1002/ad.1115.

Keywords: Architectural Robotics; Gesture-Based Programming; Cloud Computing; Sdg9

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