A Significant Integrated Autonomous Construction System Based On Intelligent Robotics and Digital Technologies

Abstract

: The construction industry has been evolving much with the application of intelligent automation, robotic systems and digital technologies to promote productivity safety constructability and sustainability of finished projects. Despite the significant progress made in the development of construction machinery and project management systems, traditional construction activities still proceed through the lack of construction manpower, safety-related issues, schedule slippage, inefficient resource allocation, Quality Variability and limited decision support in real-time manner. Existing automation systems mainly apply various autonomous control machines but work independently within a fragmented working process, which limits the automation integration among construction activities. To address the challenges, this research aims to establish a Robust Autonomous Construction Structure Using Intelligent Robotics and Digital Technologies, which combines autonomous building construction robots, construction unmanned aerial vehicles (UAVs), IoT-enabled sensing system, edge-cloud computing, Artificial Intelligence (AI), Machine Learning (ML), Building Information Modelling (BIM), Digital Twin and advanced construction projection forecasting, into an integrated intelligent construction environment to acquire continually the real-time construction information from in-field sensor networks, robotic machines, construction UAVs and digital construction models for real-time construction activity recognition, autonomous construction task execution, construction site equipment health diagnostics, construction progress tracking and adaptive construction project schedule and quality optimization, construction equipment operation management and safety management. The AI and ML application in near-real-time operation process enables to analyze the construction operation and environment data of robotic machines and construction site, identify critical hazards and real-time construction risks while suggest optimal project resource optimal allocation and autonomous project schedule optimization, pre-empt construction equipment failure and guide in-field worker operational actions in any circumstances. The digital Twin simulation synchronization can further verify the execution strategies of construction and construction operation options for project managers and construction practitioners so that to eliminate construction execution risks off-site. Based on representative construction scenarios, experimental result shows that the accuracy of construction activity recognition is greater than 96.2%, project schedule slip goes down by 32.7%, project equipment utilization rate goes up by 26.8%, construction safety can be monitored constantly in a construction site through collecting the new construction information, and overall construction productivity increases by 24.5%. The proposed architecture not only leads to sustainable infrastructure development and construction quality assurance through high-precision operation control, but also offers a scalable autonomous construction environment for next-generation SMART construction (Industry 5.0 and Construction 4.0).