Measuring the Impact of Objects' Physicalization, Avatar Appearance, and their Consistency on Pick-and-Place Performance in Augmented Reality
Year: 2025
Type: article
Abstract: Augmented Reality (AR) is a growing technology that enables interaction with both virtual and real objects. However, in order to support the future development of efficient and usable AR interactions, there is still a lack of systematic knowledge establishing basic interaction performance across different conditions. Therefore, in this paper, we report a user study measuring the impact of objects' physicalization (object's set composed of (i) virtual, (ii) real, or (iii) a composite mix of real and virtual objects) and hand appearance (hand's appearance displayed as (i) the real hand, (ii) an avatar, or (iii) dynamically adapting to the surrounding objects' physicalization) on the speed performance of a pick-and-place task. Overall, our results reveal that objects' physicalization plays a significant role in interaction performance, with the more real objects in a set the better the performance. Moreover, our results also suggest that pick-and-place interaction performances are mostly unaffected by the hand appearance. Interestingly, we also observed that interactions with real objects were less efficient as the object condition required the user to alternate between interactions with virtual and real objects (object condition (iii)), which provides novel insights into an important - mostly AR-specific - factor to consider for designing future AR interactions. Taken together, our results provide a rich characterization of different factors influencing different phases of a pick-and-place interaction, which could be employed to improve the design of future AR applications.
Institutions: Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Institut de Recherche en Informatique et Systèmes Aléatoires, Université de Rennes, École Centrale de Nantes, Laboratoire des Sciences du Numérique de Nantes, Nantes Université
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: Agence Nationale de la Recherche
OpenAlex ID: W4408222501
