Quantifying the Quality of Haptic Interfaces
Shape-Changing Haptic Interfaces
Generating Clear Vibrotactile Cues with Magnets Embedded in a Soft Finger Sheath
Salient Full-Fingertip Haptic Feedback Enabled by Wearable Electrohydraulic Actuation
Cutaneous Electrohydraulic (CUTE) Wearable Devices for Pleasant Broad-Bandwidth Haptic Cues
Modeling Finger-Touchscreen Contact during Electrovibration
Perception of Ultrasonic Friction Pulses
Vibrotactile Playback for Teaching Sensorimotor Skills in Medical Procedures
CAPT Motor: A Two-Phase Ironless Motor Structure
4D Intraoperative Surgical Perception: Anatomical Shape Reconstruction from Multiple Viewpoints
Visual-Inertial Force Estimation in Robotic Surgery
Enhancing Robotic Surgical Training
AiroTouch: Naturalistic Vibrotactile Feedback for Large-Scale Telerobotic Assembly
Optimization-Based Whole-Arm Teleoperation for Natural Human-Robot Interaction
Finger-Surface Contact Mechanics in Diverse Moisture Conditions
Computational Modeling of Finger-Surface Contact
Perceptual Integration of Contact Force Components During Tactile Stimulation
Dynamic Models and Wearable Tactile Devices for the Fingertips
Novel Designs and Rendering Algorithms for Fingertip Haptic Devices
Dimensional Reduction from 3D to 1D for Realistic Vibration Rendering
Prendo: Analyzing Human Grasping Strategies for Visually Occluded Objects
Learning Upper-Limb Exercises from Demonstrations
Minimally Invasive Surgical Training with Multimodal Feedback and Automatic Skill Evaluation
Efficient Large-Area Tactile Sensing for Robot Skin
Haptic Feedback and Autonomous Reflexes for Upper-limb Prostheses
Gait Retraining
Modeling Hand Deformations During Contact
Intraoperative AR Assistance for Robot-Assisted Minimally Invasive Surgery
Immersive VR for Phantom Limb Pain
Visual and Haptic Perception of Real Surfaces
Haptipedia
Gait Propulsion Trainer
TouchTable: A Musical Interface with Haptic Feedback for DJs
Exercise Games with Baxter
Intuitive Social-Physical Robots for Exercise
How Should Robots Hug?
Hierarchical Structure for Learning from Demonstration
Fabrication of HuggieBot 2.0: A More Huggable Robot
Learning Haptic Adjectives from Tactile Data
Feeling With Your Eyes: Visual-Haptic Surface Interaction
S-BAN
General Tactile Sensor Model
Insight: a Haptic Sensor Powered by Vision and Machine Learning
Novel Designs and Rendering Algorithms for Fingertip Haptic Devices
Wearable haptic devices have seen growing interest in recent years, but providing realistic tactile feedback is a challenge not to be solved soon. Daily interactions with physical objects elicit complex sensations at the fingertips. Furthermore, human fingertips exhibit a broad range of physical dimensions and perceptive abilities, adding increased complexity to the task of simulating haptic interactions in a compelling manner. Through this project (see [
] for summary), we aim to provide hardware- and software-based solutions for rendering more expressive and personalized tactile cues to the fingertip.
We are the first to explore the idea of rendering 6-DOF tactile fingertip feedback via a wearable 6-DOF device, such that any fingertip interaction with a surface can be simulated. We demonstrated the potential of parallel continuum manipulators to meet the requirements of such a device [], and we presented a motorized version named the Fingertip Puppeteer, or Fuppeteer for short []. We then used this novel hardware to simulate different lower-dimensional devices and evaluate the role of tactile dimensionality on virtual object interaction []. The results showed that higher-dimensional tactile feedback may indeed allow completion of a wider range of virtual tasks, but that feedback dimensionality surprisingly does not greatly affect the exploratory techniques employed by the user.
It is also essential to examine how to meet the small size and low weight requirements for wearable haptic interfaces. We used principal component analysis to find the minimum number of an existing device’s actuators that are required to render a given tactile sensation with minimal estimated haptic rendering error [].
Finally, we have also explored the idea of personalizing fingertip tactile feedback for a particular user. We presented two generalizable software-based approaches to modify an existing data-driven haptic rendering algorithm to more accurately display tactile cues to fingertips of different sizes []. Results showed that both personalization approaches significantly reduced force error magnitudes and improved realism ratings.
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