%0 Journal Article %1 yang2025implementation %A Yang, Xiliu %A Amtsberg, Felix %A Kaiser, Benjamin %A Skoury, Lior %A Stark, Tim %A Treml, Simon %A Opgenorth, Nils %A Sousa Calepso, Aimée %A Sedlmair, Michael %A Wortmann, Thomas %A Verl, Alexander %A Menges, Achim %D 2025 %I Elsevier BV %J Advanced Engineering Informatics %K mac peer livmatsbiomimetic %P 103475 %R 10.1016/j.aei.2025.103475 %T An implementation and evaluation of large-scale multi-user human–robot collaboration with head-mounted augmented reality %U http://dx.doi.org/10.1016/j.aei.2025.103475 %V 67 %X Human–robot collaboration (HRC) offers promising potential for more flexible and sustainable production practices in architecture and construction. This requires HRC setups to scale up from light-payload collaborative robots to conform with the scale of building construction while considering the safety and teamwork culture for workers. This research proposes a system for large-scale multi-user HRC using head-mounted augmented reality (AR) devices. To achieve this, we contribute three methods that work in conjunction: (1) an AR system that enables multiple users to share tasks and work together with robots; (2) a dynamic human task allocation engine that reacts to the changing production teams and task types; and (3) a safety zone generation and allocation method to configure human collaboration in shared space with large-scale robots. The system is evaluated using a case study of prefabricated timber cassettes combining discrete event simulations, a user study and a fabrication process demonstrator with an industry partner.

@article{yang2025implementation, abstract = {Human–robot collaboration (HRC) offers promising potential for more flexible and sustainable production practices in architecture and construction. This requires HRC setups to scale up from light-payload collaborative robots to conform with the scale of building construction while considering the safety and teamwork culture for workers. This research proposes a system for large-scale multi-user HRC using head-mounted augmented reality (AR) devices. To achieve this, we contribute three methods that work in conjunction: (1) an AR system that enables multiple users to share tasks and work together with robots; (2) a dynamic human task allocation engine that reacts to the changing production teams and task types; and (3) a safety zone generation and allocation method to configure human collaboration in shared space with large-scale robots. The system is evaluated using a case study of prefabricated timber cassettes combining discrete event simulations, a user study and a fabrication process demonstrator with an industry partner. }, added-at = {2025-07-08T04:26:59.000+0200}, author = {Yang, Xiliu and Amtsberg, Felix and Kaiser, Benjamin and Skoury, Lior and Stark, Tim and Treml, Simon and Opgenorth, Nils and Sousa Calepso, Aimée and Sedlmair, Michael and Wortmann, Thomas and Verl, Alexander and Menges, Achim}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/296335eb49513f579f57622ca7933d0d7/icd}, doi = {10.1016/j.aei.2025.103475}, interhash = {737b4c23d81e74ec1155b41072c3d2c5}, intrahash = {96335eb49513f579f57622ca7933d0d7}, issn = {1474-0346}, journal = {Advanced Engineering Informatics}, keywords = {mac peer livmatsbiomimetic}, month = sep, pages = 103475, publisher = {Elsevier BV}, timestamp = {2025-07-08T04:26:59.000+0200}, title = {An implementation and evaluation of large-scale multi-user human–robot collaboration with head-mounted augmented reality}, url = {http://dx.doi.org/10.1016/j.aei.2025.103475}, volume = 67, year = 2025 }