Automated facility inspection using robotics and BIM: A knowledge-driven approach

Abstract

Facility inspection is crucial for ensuring the performance of built assets. A traditional inspection, characterized by humans’ physical presence, is laborious, time-consuming, and becomes difficult to implement because of travel restrictions amid the pandemic. This laborious practice can potentially be automated by emerging smart technologies such as robotics and building information model (BIM). However, little has been known on how such automation can be achieved, concerning the knowledge-intensive nature of facility inspection. To fill the gap, this research aims to develop a knowledge-driven approach that can synergize knowledge of diverse sources (e.g., explicit knowledge from BIM, and tacit experience in human minds) to allow autonomous implementation of facility inspection by robotic agents. At the core the approach is an integrated scene-task-agent (iSTA) model that formalizes engineering priori in facility management and integrates the rich contextual information from BIM. Experiments demonstrated the applicability of the approach, which can endow robots with autonomy and knowledge to navigate the challenging built environments and deliver facility inspection outcomes. The iSTA model is publicized online, in hope of further extension by the research community and practical deployment to enable automated facility inspection using robotics and BIM.