Augmented reality-enabled human-robot collaboration to balance construction waste sorting efficiency and occupational safety and health

Construction waste sorting (CWS) is highly recommended as a key step for construction waste management. However, current CWS involves humans' manual hand-picking, which poses significant threats to their occu-pational safety and health (OSH). Robotic sorting promises to change the situation by adopting modern artificial intelligence and automation technologies. However, in practice, it is usually challenging for robots to do an efficient job (e.g., measured by quickness and accuracy) owing to the difficulties in precisely recognizing compositions of the mixed and heterogeneous waste stream. Leveraging augmented reality (AR) as a commu-nication interface, this research aims to develop a human-robot collaboration (HRC) approach to address the dilemmatic balance between CWS efficiency and OSH. Firstly, a model for human-robot collaborative sorting using AR is established. Then, a prototype for the AR-enable collaborative sorting system is developed and evaluated. The experimental results demonstrate that the proposed AR-enabled HRC method can improve the accuracy rate of CWS by 10% and 15% for sorting isolated waste and obscured waste, respectively, when compared to the method without human involvement. Interview results indicate a significant improvement in OSH, especially the reduction of contamination risks and machinery risks. The research lays out a human-robot collaborative paradigm for productive and safe CWS via an immersive and interactive interface like AR.

Automated summary

Construction waste sorting is crucial for waste management, but manual sorting poses risks while robotic sorting struggles with recognition. This research developed a human-robot collaboration system using augmented reality to improve sorting accuracy and occupational safety. Results showed a significant improvement in efficiency and safety with the AR-enabled HRC method.