Human-robot interaction (HRI) is progressively addressing multiparty scenarios, where a robot interacts with more than one human user at the same time. Conversely, research in this area is still at an early stage for human-robot collaboration (HRC). The intervention of a robot in human collaboration could be helpful to handle mutual disturbances of workers operating at the same time on the same target object. Therefore, this work outlines design methodologies of non-dyadic human-robot collaborations to address concurrent human-human tasks in manufacturing applications. After this, preliminary results regarding a robotic agent’s high-level understanding of such scenarios realised through a variational autoencoder trained by means of transfer learning are shown.
- Non-Dyadic Human-Robot Collaboration
- Multi-Party Human-Robot Collaboration
- Concurrent Tasks
- Multi-User Activity Recognition
- Deep Learning
- Variational Autoencoder
- Transfer Learning