Robotics and the construction industry today
Construction is in dire need of robotic vision. It is a harsh, geographically large and disparate, unstructured, and perpetually changing environment where high cost critical operations occur. Currently, work within the industry is not transparent and is sparsely monitored. It is not physically possible to have enough sets of ‘always alert’ intelligent eyes monitoring, and understanding, progress to generate metrics that feed into the type of control paradigm commonly found in manufacturing. Robotic vision presents an opportunity for the required real-time, real-world, robust and reliable information needed to underpin the development of improved monitoring in the industry.
Productivity in construction is significantly lagging comparable industries, and construction is very low (second to bottom) in terms of digital maturity [DIG16]. Robotic vision will enable the capture of benchmark of performance, and drive core measures upon which productivity enhancements can be proposed, made, and measured. Due to the scale of many construction projects, even a small improvement to the efficiency of a process can result in a substantial cost saving. However, the main driver for the application of robotic technologies in the sector is to reduce injury and fatality rates. Injuries can often be caused by an inability to see obstacles, and robotics can help with the identification of objects to reduce safety incidents.
There is an ongoing skills shortage in the construction industry. Australia has an inherently shifting and ageing workforce, with younger generations seemingly reluctant to pursue traditional occupations. Robotics and automation can help fill jobs vacated by the ageing workforce that are unwanted by younger people entering the workforce. Australia’s strength in field robotics (the application of robotics in large, unstructured outdoor domains) can also be applied to improving the increasingly poor productivity in the sector, allowing the collection and interpretation of complex real-time data that will allow performance towards outcomes to be measured across difficult environments.