Abstract
This research focuses on a long-standing, yet critical problem in the erection of steel structures. In the current state of practice, steel workers must stand on an unfinished structure to assist with the assembly of structural elements manually. They must pull on the wire hanging under the rigging elements to align the bolting holes of the moving and fixed elements. This work is often performed in high places, which can be very risky. Therefore, we have developed a robotic assembly system (RAS) for steel beam erection and assembly to prevent workers from having to work in a high place. The RAS consists of four methods: rotation, alignment, bolting, and unloading. The rotation method involves a flywheel installed on top of the rigging beam, which aims to rotate the beam to the assembly angle. The alignment method includes both vertical and horizontal alignment. The vertical alignment relies on a camera and a marker on the column to align the beam altitude. The horizontal alignment relies on a specially-designed beam, which allows for it to be smoothly guided into the right position. The bolting method is used to connect the beam to a fixed element. We designed an additional guide hole above each bolt hole. The bolt can be inserted in the guide hole and slid to the bolt hole. The unloading method is used to unload the crane cable and the RAS. We use a pin mechanism for the beam-hook connection so it can easily be unplugged by a motor. The system is built in a scaled experimental construction site to validate its feasibility. The results show that the RAS can operate the assembly process without humans working at risky heights, and can complete faster than the traditional method. In conclusion, we have developed a robotics assembly system that can help reduce the frequency of accidental falls during the steel beam assembly process. The RAS adheres to the process of the current erection method and can be broadly introduced to existing construction sites.
Ci-Jyun Polar Liang
Assistant Professor (Jan 2024)
My research interests include Human-Robot Collaboration, Computer Vision, Reinforcement Learning, BIM, Digital Twins, and Extended Reality.