On-site autonomous construction robots: Towards unsupervised building

Real-world construction projects typically require three groups of tasks: site preparation (earthmoving, leveling), substructure (anchoring, foundations), and superstructure (load-bearing elements, facade, plumbing, wiring, etc.). Advances in construction automation have revealed a gap between industry and academic research, where industry efforts have been focused on automating conventional earthmoving equipment and embracing pre-fabrication in order to reduce the amount of work that needs to be done on site, while academic efforts have largely concentrated on proposals for on-site additive manufacturing or discrete assembly, which may be of limited applicability to industry. This review presents a broad range of advancements in construction automation research, and finds that achieving fully autonomous construction in unstructured environments will require considerably more development in all three groups of construction tasks, as well as a particular emphasis on coordinating myriad construction tasks between different task-specific robots. Consideration is given to both mature technologies (conventional equipment widely used in industry) and emerging technologies (novel machines designed for autonomy). Key findings from the survey suggest that achieving the goal of fully autonomous construction will require more attention to be paid to site preparation and substructure tasks, material-robot systems (co-designed robots and building materials), embedded sensing, auxiliary construction tasks, and coordinating operations between robot systems. More general lessons from the literature indicate that making incremental improvements to mature technologies may benefit the industry in the short term, but there are considerable limitations to adding autonomy to equipment designed for human operators. Instead, we perceive a demand for novel hardware to be developed for specific tasks, in each case based on fundamental principles and at the appropriate scale, as well as for an increase in interdisciplinary research. We suggest that the reported shortage of skilled labor in the industry can be met with an increased emphasis on training for leveraging advances in automation.