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The digitalization is transforming the very nature of factories, from automated systems to intelligent ones. In this process, industrial robots play a key role. Even if repeatability, precision and velocity of the industrial manipulators enable reaching considerable production levels, factories are required to face an increasingly competitive market, which requires being able to dynamically adapt to different situations and conditions. Hence, facilities are moving toward systems that rely on the collaboration between humans and machines. Human workers should understand the behavior of the robots, placing trust in them to properly collaborate. If a fault occurs on a manipulator, its movements are suddenly stopped for security reasons, thus workers may not be able to understand what happened to the robot. Therefore, the operators' stress and anxiety may increase, compromising the human-robot collaborative scenario. This work fits in this context and it proposes an adaptive Augmented Reality system to display industrial robot faults by means of the Microsoft HoloLens device. Starting from the methodology employed to identify which virtual metaphors best evoke robot faults, an adaptive modality is presented to dynamically display the metaphors in positions close to the fault location, always visible from the user and not occluded by the manipulator. A comparison with a non adaptive modality is proposed to assess the effectiveness of the adaptive solution. Results show that the adaptive modality allows users to recognize faults faster and with fewer movements than the non adaptive one, thus overcoming the limitation of the narrow field-of-view of the HoloLens device.

Nowadays the market is becoming increasingly competitive, factories are required not only to enhance the product quality but also to reduce manufacturing and maintenance times. In an industrial context, modern factories are composed by many automated systems, such as industrial robots, which can perform different tasks. Although industrial robots are becoming more powerful and efficient, human workers are still required to accomplish different operations, such as training and maintenance procedures. The proposed research aims to assess a remote interaction system in an industrial training collaborative mixed-reality (CMR) environment. A remote expert user is capable of explaining a training procedure to an unskilled local user. Remote and local users interact using different interaction systems: the remote operator gives assistance using an immersive Virtual Reality (VR) device, whereas the local user interacts using a wearable Augmented Reality (AR) device. A comparison between an interaction based on the presence of a virtual human and one based on the use of abstract icons is proposed. In the first case, a virtual 3D representation of the remote technician is shown to the local user by using AR: the remote technician can pinpoint the components involved in the training procedure and the local user can visualize the instructions through some animations of the virtual avatar. In the second case, the local user cannot see a 3D representation of the remote technician; on the other hand, different 3D models, such as animated icons, are displayed to the local operator through AR depending on the component pinpointed by the remote technician in the virtual environment. Each 3D icon should suggest to the local user which component has to be manipulated at the current step of the procedure. Preliminary results suggest that the interface that requires less resources to be developed and managed should be preferred. Although in no audio condition the virtual avatar may improve the sense of presence of the remote technician, the use of abstract metaphors seems to be of primary importance to successfully complete an industrial task.

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