arXiv subjects

Yuki Onishi

Publications and source records attributed to Yuki Onishi.

3 recordsLinked to original sources

arXiv2026

A Controllability Gramain Shaping with LMI Constraints under Bures--Wasserstein Distance

This paper proposes a controller design method for shaping the controllability Gramian into a desired form to design the effect from exogenous inputs to the system state. Using the Bures--Wasserstein distance, we formulate the shaping problem as the minimization of the distance between the system Gramian and a desired Gramian, and the objective function is shown to be strictly convex on the set of symmetric positive definite matrices. In addition, by deriving a semidefinite programming formulation via a linear matrix inequality (LMI), computational efficiency is improved and additional LMI constraints can be incorporated. When the exogenous input is modeled as Gaussian white noise, the proposed framework is closely related to $H_2$ control, which can be interpreted as a special case of optimal transport. Numerical examples demonstrate anisotropic controllability design for a guidance robot and verify the ability to impose additional directional constraints through LMIs. The numerical examples also confirm that the proposed method approaches $H_2$ control as the desired Gramian tends to zero.

math.OC↗

arXiv2026

A Two-Week In-the-Wild Study of Screen Filters and Camera Sliders for Smartphone Privacy in Public Spaces

Smartphone usage in public spaces can raise privacy concerns, in terms of shoulder surfing and unintended camera capture. In real-world public space settings, we investigated the impact of tangible privacy-enhancing tools (here: screen filter and camera slider) on smartphone users' reported privacy perception, behavioral adaptations, usability and social dynamics. We conducted a mixed-method, in-the-wild study ($N = 22$) using off-the-shelf smartphone privacy tools. We investigated subjective behavioral transition by combining questionnaires with semi-structured interviews. Participants used the screen filter and the camera slider for two weeks; they reported changes in attitude and behavior after using a screen filter including screen visibility and comfort when using phones publicly. They explained decreased privacy-protective behaviors, such as actively covering their screens, suggesting a shift in perceived risk. Qualitative findings about the camera slider suggested underlying psychological mechanisms, including privacy awareness and concerns about social perception, while also offering insights regarding the tools' effectiveness.

cs.HC↗

arXiv2024

How People Prompt to Create Interactive VR Scenes

Generative AI tools can provide people with the ability to create virtual environments and scenes with natural language prompts. Yet, how people will formulate such prompts is unclear -- particularly when they inhabit the environment that they are designing. For instance, it is likely that a person might say, "Put a chair here", while pointing at a location. If such linguistic features are common to people's prompts, we need to tune models to accommodate them. In this work, we present a wizard-of-oz elicitation study with 22 participants, where we studied people's implicit expectations when verbally prompting such programming agents to create interactive VR scenes. Our findings show that people prompt with several implicit expectations: (1) that agents have an embodied knowledge of the environment; (2) that agents understand embodied prompts by users; (3) that the agents can recall previous states of the scene and the conversation, and that (4) agents have a commonsense understanding of objects in the scene. Further, we found that participants prompt differently when they are prompting in situ (i.e. within the VR environment) versus ex situ (i.e. viewing the VR environment from the outside). To explore how our could be applied, we designed and built Oastaad, a conversational programming agent that allows non-programmers to design interactive VR experiences that they inhabit. Based on these explorations, we outline new opportunities and challenges for conversational programming agents that create VR environments.

cs.HC↗