# An Approach Based on VR to Design Industrial Human-Robot Collaborative Workstations
## 3 Application to Industrial Case Studies
### Case No.2: Interaction Prototyping for Human-Robot Assembly
These cyclic tests allowed to identify interaction aspects not previously considered, as well as problems and strengths of each interface page, therefore better understanding how to improve it. For example, it emerged that the user must be able to see the interface even from several meters and this affects the HMI design, such as reviewing the size of some elements (e.g., text, buttons). Finally, referring to the third step of the VR-based interaction design approach, we conducted HMI testings. As described in Section 2.2.3, testings aimed at verifying the usability of the designed HMI and the overall user experience in the early VR-based prototype developed with the proposed approach. The HMI testing phase was conducted involving seven participants with different ages and familiarity with VR devices (Figure 16). In particular, participants were PhD students and research fellows, not directly involved in the research, of which two women and five men between 25 and 32 years old. Figure 15: Interface design flow with some screens of the low-fidelity and high-fidelity prototypes of the case no.2. During the test, participants were guided by a moderator who explained the activities to be carried out in sequence. Task descriptions were pretty generic in order not to excessively influence the users and to leave them free to act. The sequence of tasks indicated to participants is:  
1. Place the trolley with the monocque near the robot;
2. Communicate the positioning on the HMI and verify that the automatic phase is started;
3. Carry out parallel activities (for example on the desk located on the left);
4. Resolve the reported problem;
5. Communicate the resolution of the problem;
6. Suspend the activity of the robot. During the tests some participants expressed comments regarding the HMI interaction and the general activities performance. Some of the most helpful comments that emerged were:  
* \"I expected to receive an indication of the exact positioning of the monocque\";
* \"The interface was clear, but it has a rather limited appeal. I would like it more colorful\";
* \"I was expecting feedback on the successful completion of the hand guidance phase\";
* \"In the problem resolution screen, it was not clear that I had to do something like moving the robot in hand guidance\". Moreover, after the tasks execution, participants were asked to fill in a questionnaire to better investigate the user perception about the HMI interactions and the overall user experience. The questionnaire was based on the SUS model [39] but it was customized to better suit the needs of the specific survey. For each following statements, participants were asked to express a degree of agreement on a 5-Point Likert Scale (i.e., 1 = Strongly disagree, 5 = Strongly agree):  
1. I think I would like to use the interface;
2. I found the interface very clear;
3. I found the interface easy to use;  
Figure 16: Pictures of three testing sessions for case no.2. * I felt safe in interacting with the interface;
* I think the type of interface is appropriate for the type of work;
* I think the interface provides me with all the information I need to do my tasks;
* I think that the interaction with the interface is not hindered by the surrounding environment;
* I think that the HMI evaluation is not influenced by the VR scene characteristics. As mentioned in Section 2.2.3, at this design phase HMI testing mainly aims at qualitative data collection. In fact, more attention was given to the users' comments and behavior as a source of suggestions for improving the interface. For example, a red border has been added to the problem management page to better differentiate it from other pages; the list of tasks that the user must perform has been included to better guide the user during the resolution of a problem; the title of the displayed page has been made more evident to facilitate orientation within the system. On the other hand, post-test questionnaire responses were analyzed to understand the users' satisfaction level.