Diminished Reality (DR) modifies or removes elements of the perceived environment. We explored DR for attention support through diary studies, interviews, and speculative co-design with 15 university students with ADHD. Participants described a persistent gap between intention and attention, and the use of externalization strategies that encounter fundamental limits in physical reality. In co-design, rather than reasoning from visual operations, participants articulated which properties of stimuli they needed to perceive versus filter, revealing cases where visual diminishment does not reliably map to attentional diminishment. We contribute rich descriptive data on the attentional challenges and DR preferences of students with ADHD, and propose Attentional Diminishment, a sensitizing concept that reframes DR for attention support from visual outcomes to attentional effects.

Emotion regulation (ER) is a dynamic process that often unfolds in social contexts. However, current digital ER tools predominantly rely on single-agent systems that lack the complexity of social dynamics. Swarm user interfaces present unique affordances for ER through their collective adaptability and expressive group behaviour. However, their potential in supporting ER remains underexplored. To investigate how swarm user interfaces can be designed to support ER, we conducted a series of speculative participatory design workshops with 15 participants through the Magic Machine Workshop method, where participants created and enacted interactive swarm-based artifacts with craft materials. The analysis led to diverse contexts of use, envisioned swarm framing, and interaction modes. Based on these findings, we synthesize eight interaction patterns that translate abstract user metaphors into robotic behaviors. We conclude by articulating design opportunities and challenges, positioning swarm interfaces as a novel medium for ER support.

We present RoboTheater, a multi-robot storytelling platform, designed to explore and demonstrate the expressive capabilities of robots in stage execution. RoboTheater bridges computational narrative generation with embodied robotic execution, enabling robots to perform with varied dialogues and movements to create immersive stage narratives. The system uses large language models (LLMs) to generate structured scripts that are mapped into robots’ movements, speech, and visual projections, with all commands sent over a wireless network. A user study with 13 participants was conducted to evaluate the system’s usability and gather feedback. Our findings indicate that the RoboTheater effectively conveys emotion and character through multimodal cues, sustaining audience engagement and immersion. The work expands multi-robot storytelling and paves the way for creative, narrative applications.

Figure 1: Two user-defined patterns of swarm robot co-speech gestures corresponding to the word "run."Each pattern includes multiple phases, with red squares indicating the robots that have moved relative to the previous phase.

Individuals with ADHD grapple with elevated stress levels, emotional regulation challenges, and difficulty sustaining focus. Fidgeting, a behavior traditionally frowned upon, has been shown to help people with ADHD in concentration, emotional and mental state management, and energy regulation. However, traditional fidgeting devices have limited fixed affordances providing cookie-cutter style fidgeting experience to all despite individual differences. Recognizing the uniqueness of individual fidgeting tendencies, we use small tabletop robots to provide a customizable fidgeting interaction experience and conduct co-design sessions with 16 adults diagnosed with ADHD to explore how they envision their fidgeting interactions being changed with these programmable robots. We examine core elements defining a successful fidgeting interaction with robots, assess the significance of customizability in these interactions and any common trends among participants, and investigate additional advantages that interactions with robots may offer. This research reveals nuanced preferences of adults with ADHD concerning robot-assisted fidgeting.

Exploring how robots impact human cognition and emotions has become increasingly important as robots gradually become ubiquitous in our lives. In this study, we investigate the impact of robotic presence on human cognition and emotion by examining various robot parameters such as anthropomorphism, number of robots, and multi-robot motion patterns. 16 participants completed two cognitive tasks in the presence of anthropomorphic and non-anthropomorphic robots, alone, and with a human nearby. The non-anthropomorphic robot conditions were further varied in the number of robots and their motion patterns. We find that increasing the number of non-anthropomorphic robots generally leads to slower performance, but coordinated patterned motions can lower the completion time compared to random movements. An anthropomorphic robot induces an increased level of feelings of being judged compared to a non-anthropomorphic robot. These findings provide preliminary insights into how designers or users can purposefully integrate robots into our environment by understanding the effects of anthropomorphism, number of robots, and multi-robot motion patterns on human cognition and emotion.

How do people use their faces and bodies to test the interactive abilities of a robot? Making lively, believable agents is often seen as a goal for robots and virtual agents but believability can easily break down. In this Wizard-of-Oz (WoZ) study, we observed 1169 nonverbal interactions between 20 participants and 6 types of agents. We collected the nonverbal behaviors participants used to challenge the characters physically, emotionally, and socially. The participants interacted freely with humanoid and non-humanoid forms: a robot, a human, a penguin, a pufferfish, a banana, and a toilet. We present a human behavior codebook of 188 unique nonverbal behaviors used by humans to test the virtual characters. The insights and design strategies drawn from video observations aim to help build more interaction-aware and believable robots, especially when humans push them to their limits.

The IDC research community has a growing interest in designing AI interfaces for children with special educational needs. Nonetheless, little research has explored the research and design issues, rationale, challenges, and opportunities in this field. Therefore, we propose to host a half-day workshop to bring together researchers and practitioners from the Learning & Education, Accessibility, and Intelligent User Interfaces sub-fields to discuss and identify existing design issues, challenges, and collaboration barriers, to establish consensus on the design of a pragmatic framework, as well as explore future innovation and research opportunities. We aim to foster mutual understanding and in-depth collaboration among researchers in the IDC community.

Food is essential for human health, growth, and development. However, children need more learning materials and motivation to receive food literacy education or know the fundamental food processes from farm to table. In this work, we explored the design of a prototype named WooGu with tangible user interfaces (TUI) and embodied interactions, which aims to improve young children’s food literacy. WooGu presents three design features: a cube displaying user interfaces, step-by-step tasks guiding children to learn food from farm to table, and hands-on props made by cardboard empowering embodied interactions. We evaluated WooGu with two families in a pilot test, and the findings suggested that WooGu provides children with the embodied experience of food production, improving their food literacy, logical thinking, and practical ability. This research contributed to the human-food interaction area and provided a novel way of learning food literacy for children through embodied interactions with WooGu.

We introduce the concept of programmable actuated fidgeting, a type of fidgeting that involves devices integrated with actuators, sensors, and computing to enable a customizable interactive fidgeting experience. In particular, we explore the potential of a swarm of tabletop robots as an instance of programmable actuated fidgeting as robots are becoming increasingly available. Through ideation sessions among researchers and feedback from the participants, we formulate the design space for SwarmFidget, where swarm robots are used to facilitate programmable actuated fidgeting. To gather user impressions, we conducted an exploratory study where we introduced the concept of SwarmFidget to twelve participants and had them experience and provide feedback on six example fidgeting interactions. Our study demonstrates the potential of SwarmFidget for facilitating fidgeting interaction and provides insights and guidelines for designing effective and engaging fidgeting interactions with swarm robots. We believe our work can inspire future research in the area of programmable actuated fidgeting and open up new opportunities for designing novel swarm robot-based fidgeting systems.

In this paper, we study how a co-located robot affects human motivation and emotion. In particular, we examine the role of the co-located robot’s anthropomorphism, as well as the effects of the human’s personality and gender. To study this, we conducted an online experiment, where 182 participants completed a repetitive task, either easy or hard, in one of the four conditions: in the presence of a non-anthropomorphic robot, an anthropomorphic robot, another human, or alone. For each condition, we analyzed the number of repetitions and the total time users spent, which we treated as the proxy of their motivation, as well as their self-reported emotional states. The study results suggest that the presence of a non-anthropomorphic robot has the potential to lead to a higher level of motivation and a more desirable affective state for users than the presence of an anthropomorphic robot or another human, especially for introverts and female users during difficult tasks.

As swarm robots begin to share the same space with people, it is critical to design legible swarm robot motion that clearly and rapidly communicates the intent of the robots to nearby users. To address this, we apply concepts from intent-expressive robotics, swarm intelligence, and vision science. Specifically, we leverage the trajectory, collective behavior, and density of swarm robots to generate motion that implicitly guides people’s attention toward the goal of the robots. Through online evaluations, we compared different types of intent-expressive motions both in terms of legibility as well as glanceability, a measure we introduce to gauge an observer’s ability to predict robots’ intent pre-attentively. The results show that the collective behavior-based motion has the best legibility performance overall, whereas, for glanceability, trajectory-based legible motion is most effective. These results suggest that the optimal solution may involve a combination of these legibility cues based on the scenario and the desired properties of the motion.

Social media platforms facilitate communication through sharing photos and videos. The abundance of visual content creates accessibility issues, particularly for people who are blind or have low vision. While assistive technologies like screen readers can help when alt-text for images is provided, synthesized voices lack the human element that is important for social interaction. Here, we investigate when it makes the most sense to use human narration as opposed to a screen reader to describe photos in a social media context. We explore the effects of voice familiarity (i.e., whether you hear the voice of someone you know) and the perspective of the description (i.e., first vs. third person point-of-view (POV)). Preliminary study suggests that users prefer hearing from a person they know when the content is described in first person POV, whereas synthesized voice is preferred for content described in third person POV.

A swarm of robots can accomplish more than the sum of its parts, and swarm systems will soon see increased use in applications ranging from tangible interfaces to search and rescue teams. However, effective human control of robot swarms has been shown to be demonstrably more difficult than controlling a single robot, and swarm-specific interactions methodologies are relatively underexplored. As we envision even non-expert users will have more daily in-person encounters with different numbers of robots in the future, we present a user-defined set of control interactions for tabletop swarm robots derived from an elicitation study. We investigated the effects of number of robots and proximity on the user's interaction and found significant effects. For instance, participants varied between using 1-2 fingers, one hand, and both hands depending on the group size. We also provide general design guidelines such as preferred interaction modality, common strategies, and a high-agreement interaction set.

This paper seeks to better understand the use of haptic feedback in abstract, ubiquitous robotic interfaces. We introduce and provide preliminary evaluations of SwarmHaptics, a new type of haptic display using a swarm of small, wheeled robots. These robots move on a flat surface and apply haptic patterns to the user's hand, arm, or any other accessible body parts. We explore the design space of SwarmHaptics including individual and collective robot parameters, and demonstrate example scenarios including remote social touch using the Zooids platform. To gain insights into human perception, we applied haptic patterns with varying number of robots, force type, frequency, and amplitude and obtained user's perception in terms of emotion, urgency, and Human-Robot Interaction metrics. In a separate elicitation study, users generated a set of haptic patterns for social touch. The results from the two studies help inform how users perceive and generate haptic patterns with SwarmHaptics.

Passive haptic proxy objects allow for rich tangible interaction, and this is especially true in VR applications. However, this requires users to have many physical objects at hand. Our paper proposes robotic assembly at run-time of low-resolution haptic proxies for tangible interaction and virtual reality. These assembled physical proxy objects are composed of magnetically attached blocks which are assembled by a small multi robot system, specifically Zooids. We explore the design of the basic building blocks and illustrate two approaches to assembling physical proxies: using multirobot systems to (1) self-assemble into structures and (2) assemble 2.5D structure with passive blocks of various heights. The success rate and completion time are evaluated for both approaches. Finally, we demonstrate the potential of assembled proxy objects for tangible interaction and virtual reality through a set of demonstrations.

Current mobile devices do not leverage the rich haptic channel of information that our hands can sense, and instead focus primarily on touch based graphical interfaces. Our goal is to enrich the user experience of these devices through bi-directional haptic and tactile interactions (display and control) around the edge of hand-held devices. We propose a novel type of haptic interface, a Haptic Edge Display, consisting of actuated pins on the side of a display, to form a linear array of tactile pixels (taxels). These taxels are implemented using small piezoelectric actuators, which can be made cheaply and have ideal characteristics for mobile devices. We developed two prototype Haptic Edge Displays, one with 24 actuated pins (3.75mm in pitch) and a second with 40 pins (2.5mm in pitch). This paper describes several novel haptic interactions for the Haptic Edge Display including dynamic physical affordances, shape display, non-dominant hand interactions, and also in-pocket ``pull' style haptic notifications. In a laboratory experiment we investigated the limits of human perception for Haptic Edge Displays, measuring the just-noticeable difference for pin width and height changes for both in-hand and simulated in-pocket conditions.

This paper introduces swarm user interfaces, a new class of human-computer interfaces comprised of many autonomous robots that handle both display and interaction. We describe the design of Zooids, an open-source open-hardware platform for developing tabletop swarm interfaces. The platform consists of a collection of custom-designed wheeled micro robots each 2.6 cm in diameter, a radio base-station, a high-speed DLP structured light projector for optical tracking, and a software framework for application development and control. We illustrate the potential of tabletop swarm user interfaces through a set of application scenarios developed with Zooids, and discuss general design considerations unique to swarm user interfaces.

In a teleoperated system, misalignment between the master and slave manipulators can result from clutching, errors in the kinematic model, and/or sensor errors. This study examines the effects of type and magnitude of misalignment on the performance of the teleoperator. We first characterized the magnitude and direction of orientation misalignment created when clutching and unclutching during use of two surgical robots: the Raven II and the da Vinci Research Kit. We then purposely generated typical misalignments in order to measure the impact of such misalignment on user performance of a peg transfer task with the Raven II. Users were able to compensate for misalignment angles up to approximately 20 degrees in both tool orientation and camera viewpoint misalignment. These results can be used to guide the design and control of teleoperated systems for a variety of applications.