Knowledge Evolution in Construction Automation Research

Abstract

Construction automation and robotics have been widely adopted in the construction industry as a promising solutionto such issues like a shortage of skilled labor and the difficulties workers face in harsh working environments. Theanalysis of the knowledge structure and its evolution from the existing articles helps identify essential knowledgeelements and possible future research directions. This study attempts to (1) construct keyword networks from thepapers published in the International Symposium on Automation and Robotics in Construction (ISARC), (2) investigatehow keywords and keyword communities are associated with each other, and (3) examine the changes in the crucialkeywords over time. Through cluster analysis, 79 keywords were categorized into four groups (BIM, Buildingconstruction, Sensing, and GPS as representative keywords) with similar structural positions. Research trends showthat research themes related to Infrastructure, Construction equipment, and 3D have consistently received a largeamount of attention, regardless of geographical region. Research on as-built status model utilization through BIM andLaser scanning and improving Energy performance is taking place more frequently. In contrast, research studies relatedto problem-solving based on Neural networks are not as common as previously. This study provides useful insightsinto the construction automation field, at both the macro and micro levels.