Both haptic signals and simple, non-anthropomorphic robots can convey complex emotions and enhance remote communication. In this study, we integrated a zoomorphic socially expressive Blossom robot and a haptic sleeve to create a novel multimodal telepresence platform for remote social interaction. Through a within-subject user study with 16 participants, we explored the individual and combined effects of socially expressive robots and mediated social touch on affective communication and social presence during a semi-collaborative LEGO assembly task. Across all participants, the robot and wearable device significantly impacted how participants perceived expressions of gratitude, calming, attention-grabbing, and sadness, evaluated through self-reported valence and arousal. The robot and wearable device in our setting did not show a significant effect on social presence. The observations from this exploratory study can inform the design of multimodal telepresence systems and interactions using non-anthropomorphic robots and mediated touch.

Individual differences in vibrotactile perception underscore the growing importance of personalization as haptic feedback becomes more prevalent in interactive systems. We propose Vibrotactile Preference Learning (VPL), a system that captures user-specific preference spaces over vibrotactile parameters via Gaussian-process-based uncertainty-aware preference learning. VPL uses an expected information gain-based acquisition strategy to guide query selection over 40 rounds of pairwise comparisons of overall user preference, augmented with user-reported uncertainty, enabling efficient exploration of the parameter space. We evaluate VPL in a user study (N = 13) using the vibrotactile feedback from a Microsoft Xbox controller, showing that it efficiently learns individualized preferences while maintaining comfortable, low-workload user interactions. These results highlight the potential of VPL for scalable personalization of vibrotactile experiences.

Virtual Reality (VR) systems have increasingly leveraged multisensory feedback to enrich user experience and mitigate cybersickness. With a similar goal in focus, this paper presents an in-depth exploration of integrating airflow with visual and kinesthetic cues in a VR surfing simulation. Utilizing a custom-designed airflow system and a physical surfboard mounted on a 6-Degree of Freedom (DoF) motion platform, we present two studies that evaluate the effect of the different feedback modalities. The first study assesses the impact of variable airflow, which dynamically adjusts to the user's speed (wind speed) in VR, compared to constant airflow conditions, under both active and passive user engagement scenarios. Results demonstrate that variable airflow significantly enhances immersion and reduces cybersickness, particularly when users are actively engaged in the simulation. The second study evaluates the individual and combined effects of vision, motion, and airflow on acceleration perception, user immersion, and cybersickness, revealing that the integration of all feedback modalities yields the most immersive and comfortable VR experience. This study underscores the importance of synchronized multisensory feedback in dynamic VR environments and provides valuable insights for the design of more immersive and realistic virtual simulations, particularly in aquatic, interactive, and motion-intensive scenarios.

Perception in robot manipulation has been actively explored with the goal of advancing and integrating vision and touch for global and local feature extraction. However, it is difficult to perceive certain object internal states, and the integration of visual and haptic perception is not compact and is easily biased. We propose to address these limitations by developing an active acoustic sensing method for robot manipulation. Active acoustic sensing relies on the resonant properties of the object, which are related to its material, shape, internal structure, and contact interactions with the gripper and environment. The sensor consists of a vibration actuator paired with a piezo-electric microphone. The actuator generates a waveform, and the microphone tracks the waveform's propagation and distortion as it travels through the object. This paper presents the sensing principles, hardware design, simulation development, and evaluation of physical and simulated sensory data under different conditions as a proof-of-concept. This work aims to provide fundamentals on a useful tool for downstream robot manipulation tasks using active acoustic sensing, such as object recognition, grasping point estimation, object pose estimation, and external contact formation detection.

Group formation is fundamental for 3D displays that use Flying Light Specks, FLSs, to illuminate shapes and provide haptic interactions. An FLS is a drone with light sources that illuminates a shape. Groups of G FLSs may implement reliability techniques to tolerate FLS failures, provide kinesthetic haptic feedback in response to a user’s touch, and facilitate a divide and conquer approach to challenges such as localizing FLSs to render a shape. This paper evaluates four decentralized techniques to form groups. An FLS implements a technique autonomously using asynchronous communication and without a global clock. We evaluate these techniques using synthetic point clouds with known optimal solutions and real point clouds. Obtained results show a technique named Random Subset (RS) is superior when constructing small groups (G ≤ 5) while a different technique named Closest Available Neighbor First (CANF) is superior when constructing large groups (G ≥ 10).

To address difficulties with affect dysregulation in youth diagnosed with autism spectrum disorder (ASD), we designed and developed an end-to-end vibrotactile breathing pacer system and evaluated its usability. In this paper we describe the system architecture and the features we deployed for this system based on expert advice and reviews. Through piloting this system with one child diagnosed with ASD, we learned that our system was used in ways we did and did not anticipate. For example, the paced-breathing personalization procedure did not meet the attention span of the pilot participant but two instead of one pacer devices encouraged caregiver’s involvement. This paper details our learnings and concludes with a list of system design guidelines at the system architecture level. To the best of our knowledge, this is the first fully functional vibrotactile system designed for ASD children that withstood usability testing in vitro for two weeks.

We describe the design and evaluation of PIV, a personalizable and inconspicuous vibrotactile breathing pacer. Given the prevalence and adverse impact of anxiety and anxiety disorders, our goal is to develop a technology that helps people regulate their anxiety through paced breathing. We examined two previously unstudied questions: What is an effective vibrotactile pattern for paced breathing, and where should the tactors be placed on the body to make the pacer most effective? We designed a series of personalized vibrotactile pacing patterns, and evaluated them on three body sites, in terms of self-reported and psychophysiological measures including skin conductance and breath wave parameters. The results show that personalization plays an important role in PIV’s pattern and placement design choices. We concluded that the choice of frequency based, strong-exhale-phased patterns and abdomen placement are appropriate for future studies.

Soft robotics and pneumatic actuation present opportunities for lightweight wearable haptic devices that provide distributed touch feedback to the skin. Ideally, such devices would be easily donned and doffed, since permanent coverage of a large area of the skin is undesirable. Here we present the design and evaluation of a concept device called HapWRAP: a growing haptic device constructed from flexible low density polyethylene. Controlled air flow through tubes and pouches allows HapWRAP to grow out of a compact housing unit and provide a combination of directional and force feedback to a user. When activated, HapWRAP grows up and around the forearm; its loops form a temporary sleeve. After growth, pneumatic actuators inflate and deflate to stimulate mechanoreceptors in the skin at distinguishable locations. This paper describes the design and manufacturing of HapWRAP, reports its performance metrics, and tests its suitability as a haptic feedback device. Participants were able to interpret force and direction cues from HapWRAP with 92.5% accuracy. These findings suggest that HapWRAP can be successfully used for applications where both force and direction cues are necessary.

In this article, we present a bi-directional communication scheme that facilitates interaction between a person and a mobile robot that follows the person. A person-following robot can assist people in many applications including load carrying, elder care, and emotional support. However, commercially available personal robot systems usually have limited sensing and actuation capabilities. They are not expected to function perfectly in complex environments, and human intervention is required when the robot fails. We propose to use a holdable mechatronic device to reduce the user’s effort in communication and enable natural interaction during the intervention. Our design of the holdable device consists of two parts: a haptic interface that displays touch cues to convey the robot’s failure status via asymmetric vibrations, and a command interface for teleoperating the robot follower with hand gestures. We experimentally evaluated the device and the communication strategy in two sets of user studies with a controlled environment and a physical robot follower. Results show that with the proposed method, users are able to perform their tasks better, respond to robot failure events faster, and adjust walking speed according to the robot’s limitations. We also demonstrate that users can successfully teleoperate the robot to avoid obstacles when navigating in challenging environments.

WAVES, a Wearable Asymmetric Vibration Excitation System, is a novel wearable haptic device for presenting three dimensions of translation and rotation guidance cues. In contrast to traditional vibration feedback, which usually requires that users learn to interpret a binary cue, asymmetric vibrations have been shown to induce a pulling sensation in a desired direction. When attached to the fingers, a single voicecoil actuator presents a translation guidance cue and a pair of voicecoil actuators presents a rotation guidance cue. The directionality of mechanoreceptors in the skin led to our choice of the location and orientation of the actuators in order to elicit very strong sensations in certain directions. For example, users distinguished a "left" cue versus a "right" cue 94.5% of the time. When presented with one of six possible direction cues, users on average correctly identified the direction of translation cues 86.1% of the time and rotation cues 69.0% of the time.

Wearable haptic feedback devices for virtual reality, human-robot interaction, and motion guidance require lightweight actuators that display clearly discernible cues to the user. These goals motivate the design of WRAP, a wearable, pneumatically actuated haptic feedback device. WRAP displays a variety of tactile sensations to the user by inflating a thermoplastic pneumatic actuator in direct contact with the skin. This paper describes the design and construction of WRAP, shows its effectiveness in indicating direction cues to users, and demonstrates two other appUcations for WRAP in image-guided medical interventions and human-computer interaction. Users were able to identify translation and rotation cues from WRAP with 99.4% accuracy. Our results suggest that WRAP is suitable for a variety of wearable and portable applications in which direction cues are beneficial.

Ungrounded haptic devices for virtual reality (VR) applications lack the ability to convincingly render the sensations of a grasped virtual object's rigidity and weight. We present Grabity, a wearable haptic device designed to simulate kinesthetic pad opposition grip forces and weight for grasping virtual objects in VR. The device is mounted on the index finger and thumb and enables precision grasps with a wide range of motion. A unidirectional brake creates rigid grasping force feedback. Two voice coil actuators create virtual force tangential to each finger pad through asymmetric skin deformation. These forces can be perceived as gravitational and inertial forces of virtual objects. The rotational orientation of the voice coil actuators is passively aligned with the real direction of gravity through a revolute joint, causing the virtual forces to always point downward. This paper evaluates the performance of Grabity through two user studies, finding promising ability to simulate different levels of weight with convincing object rigidity. The first user study shows that Grabity can convey various magnitudes of weight and force sensations to users by manipulating the amplitude of the asymmetric vibration. The second user study shows that users can differentiate different weights in a virtual environment using Grabity.

Dragging a tool across a textured surface produces vibrations that convey important perceptual information about the interaction and the underlying qualities of the surface. These vibrations depend on the motions of the tool and respond to both normal force and tangential speed. This paper explores various methods of simulating haptic texture interactions by rendering tool vibrations that are based on recorded data. We designed and ran a human-subject study (N=15) to analyze the importance of creating virtual texture vibrations that respond to user force and speed. Our analysis of data from fifteen textures showed that removing speed responsiveness did cause a statistically significant decrease in perceived realism, but removing force responsiveness did not. This result indicates that virtual textures aiming to simulate real surfaces should vary the rendered vibrations with user speed but may not need to vary them with user force.

If you pick up a tool and drag its tip across a table, a rock, or a swatch of fabric, you are able to feel variations in the textures even though you are not directly touching them. These vibrations are characteristic of the material and the motions made when interacting with the surface. This paper presents a new method for creating haptic texture models from data recorded during natural and unconstrained motions using a new haptic recording device. The recorded vibration data is parsed into short segments that represent the feel of the surface at the associated tool force and speed. We create a low-order auto-regressive (AR) model for each data segment and construct a Delaunay triangulation of models in force-speed space for each surface. During texture rendering, we stably interpolate between these models using barycentric coordinates and drive the interpolated model with white noise to output synthetic vibrations. Our methods were validated through application to data recorded by eight human subjects and the experimenter interacting with six textures. We present a new spectral metric for determining perceptual match of the models in order to evaluate the effectiveness and consistency of the segmenting and modeling approach. Multidimensional scaling (MDS) on the pairwise differences in the synthesized vibrations shows that the 54 created texture models cluster by texture in a two-dimensional perceptual space.