Recently, digital displays such as liquid crystal displays and projectors have enabled high-resolution and high-speed information transmission. However, their artificial appearance can sometimes detract from natural environments and landscapes. In contrast, ambient displays, which transfer information to the entire physical environment, have gained attention for their ability to blend seamlessly into living spaces. This study aims to develop an ambient display that harmonizes with traditional Japanese tatami rooms by proposing an information presentation method using tatami mats. By leveraging the anisotropic properties of tatami, which change their reflective characteristics according to viewing angles and light source positions, various images and animations can be represented. We quantitatively evaluated the color change of tatami using color difference. Additionally, we created both static and dynamic displays as information presentation methods using tatami.

https://doi.org/10.1145/3689050.3704924

Hu, Yuhan, Peide Huang, Mouli Sivapurapu, and Jian Zhang. "ELEGNT: Expressive and Functional Movement Design for Non-anthropomorphic Robot." arXiv preprint arXiv:2501.12493(2025).

https://arxiv.org/abs/2501.12493

Nonverbal behaviors such as posture, gestures, and gaze are essential for conveying internal states, both consciously and unconsciously, in human interaction. For robots to interact more naturally with humans, robot movement design should likewise integrate expressive qualities—such as intention, attention, and emotions—alongside traditional functional considerations like task fulfillment, spatial constraints, and time efficiency. In this paper, we present the design and prototyping of a lamp-like robot that explores the interplay between functional and expressive objectives in movement design. Using a research-through-design methodology, we document the hardware design process, define expressive movement primitives, and outline a set of interaction scenario storyboards. We propose a framework that incorporates both functional and expressive utilities during movement generation, and implement the robot behavior sequences in different function- and social-oriented tasks. Through a user study comparing expression-driven versus function-driven movements across six task scenarios, our findings indicate that expression-driven movements significantly enhance user engagement and perceived robot qualities. This effect is especially pronounced in social-oriented tasks.

K. Brandstätter, B. J. Congdon and A. Steed, "Do you read me? (E)motion Legibility of Virtual Reality Character Representations," 2024 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Bellevue, WA, USA, 2024, pp. 299-308, doi: 10.1109/ISMAR62088.2024.00044.

We compared the body movements of five virtual reality (VR) avatar representations in a user study (N=53) to ascertain how well these representations could convey body motions associated with different emotions: one head-and-hands representation using only tracking data, one upper-body representation using inverse kinematics (IK), and three full-body representations using IK, motioncapture, and the state-of-the-art deep-learning model AGRoL. Participants’ emotion detection accuracies were similar for the IK and AGRoL representations, highest for the full-body motion-capture representation and lowest for the head-and-hands representation. Our findings suggest that from the perspective of emotion expressivity, connected upper-body parts that provide visual continuity improve clarity, and that current techniques for algorithmically animating the lower-body are ineffective. In particular, the deep-learning technique studied did not produce more expressive results, suggesting the need for training data specifically made for social VR applications.

https://ieeexplore.ieee.org/document/10765392