Application Research of Human–Robot Collaboration Technology Based on EEG Signals in the Field of Engineering Construction

Against the background of accelerated advancement of urbanization, the market scale of China's construction industry has been expanding. However, there are still problems such as labor force shortage, low production efficiency and frequent safety accidents, which hinder the development of the construction industry. The construction industry, as one of the important industries of national economy, has also started digital and intelligent technology innovation. Therefore, it is important to reduce the reliance on manual labor, reduce the occurrence of safety accidents and further improve productivity. In this study, EEG data were collected through motor imagery experiments. Based on CNN algorithm to extract, identify and classify EEG signals, the user's operational intention is transformed into a digital signal that can be recognized by the computer. The virtual experiment platform is built based on Unity, and the computer signals that can express the user's intention are transmitted to the virtual experiment platform by means of network communication, and then the movement of the manipulator is controlled to complete the scaffolding dismantling task under the virtual scene in a human–robot collaborative way. The method proposed in this paper can be applied in other scenarios in the engineering field as well, with a certain degree of scalability. In addition, the platform can also be used as a training system and practice platform. Workers can immerse themselves in virtual operation scenarios in order to more skillfully use the human–robot interaction system to complete construction tasks and achieve the purpose of technical handouts.