## 4 Results
### Discussion
This is likely due to the holograms projecting onto the AR headset's see-through lens, allowing participants to have a clear view of the real-world environment. In contrast, the Quest 2's Passthrough feature uses infrared sensors to construct a lower-resolution grayscale view of the user's surroundings, which some participants found difficult to adapt to and use. A participant (P2) even raised concerns about the Passthrough view potentially _\"trigger[ing] motion-sickness in people\"_. This point also raises an issue of emulating AR with VR technology as the VR mapping approach may not be accessible for extended use in all users due to the current real-world visualization techniques available on the Quest 2. However, when comparing the virtual object visualization, the AR headset did not improve over the VR headset. This may be due to the virtual holograms being too transparent on the AR headset, making it difficult for users to determine where their virtual objects were co-located onto the real environment. In contrast, the colored object bounding boxes are more visually striking against the grayscale background--which is why we believe the VR headset was rated higher than the AR headset for survey question V2 on seeing virtual objects with ease. Further work should be undertaken to improve upon the drawbacks of each headset in their visualization methods to enhance the use of these AR and VR devices for semantic mapping. Surprisingly, our hypothesis tests showed that participant enjoyability was the only metric that showed no improvement between the two headsets, with no variable affirming H5. This result is interesting as participants all explicitly stating a preference for the VR headset in a post-study survey. A possible explanation for this result is that participants valued the intuitiveness and visual performance of the VR device more than the overall enjoyability of completing the task. Further work should focus on the design of these survey questions to better evaluate this hypothesis; however, this result implies that improved visualization and control methods for the AR and VR headsets would lead to higher user satisfaction. When evaluating the response to question I3 (Perceived Efficiency), we note that participants perceived the VR headset to be significantly more efficient in assisting the mapping task over the AR headset (\(p\) = 0.005 for variable I3). This is consistent with the observed task times and object mapping accuracy (\(p\) \(\leq\) 0.001 for all objective metrics in favor of the alternate hypotheses H1 and H2). We expect these results are mainly caused by how the VR headset utilizes motion controllers to interface with the mapping application, which supports greater tracking accuracy and lower input latency when compared with real-time hand-tracking systems for hand-gesture control [2, 17, 18, 19]. Although these results were expected, it is important to note that the object mapping accuracies were generally poor, with 3D IoU averaging around 40% for maps generated using the VR headset. In particular, we found that users struggled more when mapping smaller objects, as these objects inherently require greater precision and control over the virtual objects to co-locent them correctly. A summary of the average 3D IoU percentages for each of the experimental objects shown in Table 5 also demonstrates this observation, as users struggled the most when mapping the apple and small box objects. It is also important to consider the potential effect of time pressure on participants when considering IoU results from the AR headset, with all participants requiring more than seven minutes out of a total of eight minutes to complete their mapping task when using the AR device. In addition, seven participants failed to complete the task in time, making it plausible that the participants had to rush the placement of some of their virtual objects, therefore negatively affecting their average IoU for the task.