Human-robot collaboration has great potential in enhancing robot deployment at close proximity with people, especially in non-dyadic collaborations with multiple users. However, autonomous systems that are capable of handling such interactions in a physical domain are rare. This work proposes TriHRCBot, a robotic architecture designed to handle a collaborative task that involves two concurrent users. The architecture is sensitive to position, orientation, body lengths and state of the users in the interaction, and uses this information to adjust the pose of a target object to enable both users to act on it at the same time. A robotic system equipped with the TriHRCBot architecture was deployed in a user study in which 30 participants from the BAE Systems Academy for Skills and Knowledge Centre interacted with it during such multi-user collaborative task. The study shows that the participants considered TriHRCBot acceptable for the task at hand. The code repository of the architecture is publicly available11Code repository: https://github.com/francescosemeraro/TriHRCBot,

Human-robot collaboration has the potential of unlocking new manufacturing paradigms thanks to the introduction of a robotic architecture in a production chain that involves human workers. A possible innovative declination of this is the use of collaborative robots to enable two workers to concurrently act on the same manufacturing target without causing mutual disturbances. By doing so, the efficiency of the process would be preserved while reducing the production times. This work designs a physical collaborative task that involves two users and one collaborative robot. The users act in the scenario in a concurrent way on the same target object, while the robot physically intervenes in the scene as a mediator by adjusting the position and orientation of the object to accommodate both users at the same time. Through this experimental setup, 78 apprentices and teachers of the BAE Systems Academy for Skills and Knowledge Centre were recruited to investigate the users’ perception of the task workload and trust towards the robotic system. Specifically, they performed the same task under two experimental conditions, in which the robot responded to changes in the interaction in a reactive or timed way, respectively. The statistical analysis showed that a timed response of the robot was associated with lower perceived workload and higher predictability of the system.