Dimensional Reduction from 3D to 1D for Realistic Vibration Rendering

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Research Overview

Natural Embodied Touch

Finger-Surface Contact Mechanics in Diverse Moisture Conditions

Perceptual Integration of Contact Force Components During Fingertip Sliding

Material Intelligence of Animal Whiskers

Artificial Touch Sensing and Processing

Giving Touch to Soft Robot Fingertips Using Vision, Audio and Machine Learning

Capturing and Recognizing Multimodal Surface Interactions

Multimodal Puncture Detection for Urgent Percutaneous Therapies

Haptic Actuation

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

CAPT Motor: A Two-Phase Ironless Motor Structure

Immersive Teleoperation

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

Human-Robot Interaction

Enhancing HRI through Responsive Multimodal Feedback

Haptic Empathetic Robot Animal (HERA)

How does HuggieBot compare to a human hugging partner?

HuggieBot: Evolution of an Interactive Hugging Robot with Visual and Haptic Perception

Human Movement

Reconstructing Sign-Language Movements from Images and Bioimpedance Measurements

Advancing Gait-Retraining Techniques

Multimodal Sensing Reveals the Dynamics of Time-Constrained Teamwork

Previous HI Projects

Finger-Surface Contact Mechanics in Diverse Moisture Conditions

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

Intraoperative AR Assistance for Robot-Assisted Minimally Invasive Surgery

Haptipedia

Exercise Games with Baxter

Intuitive Social-Physical Robots for Exercise

Insight: a Haptic Sensor Powered by Vision and Machine Learning

Haptic Intelligence Members Publications

Dimensional Reduction from 3D to 1D for Realistic Vibration Rendering

We are studying ways to reduce a real 3D vibration to a perceptually equivalent 1D vibration. (a) The concept and our real-time conversion system. (b) Our analysis of multi-dimensional vibrations using a magnetic levitation haptic interface.

Unconstrained tool-mediated interaction with a surface generates 3D vibrations that contain high-frequency accelerations in all Cartesian directions. These vibrations convey rich task information, so they need to be captured and portrayed for the user to feel in both virtual and remote interactions. To limit system cost and complexity, haptics researchers often reduce 3D vibrations into 1D signals and render them using a single-axis actuator as humans cannot easily perceive the direction of vibrations. Such three-to-one (321) reduction can be performed using many different algorithms that have rarely been compared.

This project investigates the quality of 321 conversion methods by analyzing the properties of their input and output vibrations. We established a real-time conversion system that simultaneously measures 3D accelerations and plays corresponding 1D vibrations []. A user can interact with various objects via a stylus that contains a three-axis accelerometer. The captured signals are then reduced to 1D by different algorithms and rendered by a standard voice-coil actuator. Objective analysis and subjective user ratings confirmed that more sophisticated conversion methods such as DFT321 perform better than the common approach of choosing a single-axis signal [].

We also developed a novel multi-dimensional vibration rendering system that can accurately generate 3D vibrations using a commercial magnetic levitation haptic device. We quantitatively and qualitatively verified its performance at rendering recorded 3D vibrations []. The system was then used to conduct experiments to compare human perception between the original 3D and different 1D versions of the same vibration signal. Ongoing work assesses the characteristics of all common 321 algorithms by establishing perceptual spaces [].

This project provides many practical results for both real-time haptic teleoperation and offline haptic processing. For instance, our findings can contribute to medical teleoperation systems by offering a simple but realistic 321 method that allows surgeons to feel vibrotactile feedback from remote surgical robots.

Download the MATLAB code of DFT321 at [].

Members

Haptic Intelligence

Hojin Lee

Postdoctoral Researcher

Haptic Intelligence

Gunhyuk Park

Haptic Intelligence, Physical Intelligence

Guney Tombak

Intern

Haptic Intelligence

Katherine J. Kuchenbecker

Director

Publications

Haptic Intelligence Miscellaneous Discrete Fourier Transform Three-to-One (DFT321): Code Landin, N., Romano, J. M., McMahan, W., Kuchenbecker, K. J. MATLAB code of discrete fourier transform three-to-one (DFT321), 2024 (Published) Code BibTeX

Haptic Intelligence Article Perceptual Space of Algorithms for Three-to-One Dimensional Reduction of Realistic Vibrations Lee, H., Tombak, G. I., Park, G., Kuchenbecker, K. J. IEEE Transactions on Haptics, 15(3):521-534, July 2022 (Published)

Abstract ›

Haptics researchers often endeavor to deliver realistic vibrotactile feedback through broad-bandwidth actuators; however, these actuators typically generate only single-axis vibrations, not 3D vibrations like those that occur in natural tool-mediated interactions. Several three-to-one (321) dimensional reduction algorithms have thus been developed to combine 3D vibrations into 1D vibrations. Surprisingly, the perceptual quality of 321-converted vibrations has never been comprehensively compared to rendering of the original 3D signals. In this study, we develop a multi-dimensional vibration rendering system using a magnetic levitation haptic interface. We verify the system's ability to generate realistic 3D vibrations recorded in both tapping and dragging interactions with four surfaces. We then conduct a study with 15 participants to measure the perceived dissimilarities between five 321 algorithms (SAZ, SUM, VM, DFT, PCA) and the original recordings. The resulting perceptual space is investigated with multiple regression and Procrustes analysis to unveil the relationship between the physical and perceptual properties of 321-converted vibrations. Surprisingly, we found that participants perceptually discriminated the original 3D vibrations from all tested 1D versions. Overall, our results indicate that spectral, temporal, and directional attributes may all contribute to the perceived similarities of vibration signals.

DOI BibTeX

Haptic Intelligence Miscellaneous Characterization of a Magnetic Levitation Haptic Interface for Realistic Tool-Based Interactions Lee, H., Tombak, G. I., Park, G., Kuchenbecker, K. J. Work-in-progress poster presented at EuroHaptics, Leiden, the Netherlands, September 2020 (Published)

Abstract ›

We introduce our recent study on the characterization of a commercial magnetic levitation haptic interface (MagLev 200, Butterfly Haptics LLC) for realistic high-bandwidth interactions. This device's haptic rendering scheme can provide strong 6-DoF (force and torque) feedback without friction at all poses in its small workspace. The objective of our study is to enable the device to accurately render realistic multidimensional vibrotactile stimuli measured from a stylus-like tool. Our approach is to characterize the dynamics between the commanded wrench and the resulting translational acceleration across the frequency range of interest. To this end, we first custom-designed and attached a pen-shaped manipulandum (11.5 cm, aluminum) to the top of the MagLev 200's end-effector for better usability in grasping. An accelerometer (ADXL354, Analog Devices) was rigidly mounted inside the manipulandum. Then, we collected a data set where the input is a 30-second-long force and/or torque signal commanded as a sweep function from 10 to 500 Hz; the output is the corresponding acceleration measurement, which we collected both with and without a user holding the handle. We succeeded at fitting both non-parametric and parametric versions of the transfer functions for both scenarios, with a fitting accuracy of about 95% for the parametric transfer functions. In the future, we plan to find the best method of applying the inverse parametric transfer function to our system. We will then employ that compensation method in a user study to evaluate the realism of different algorithms for reducing the dimensionality of tool-based vibrotactile cues.

BibTeX

Conference Paper Objective and Subjective Assessment of Algorithms for Reducing Three-Axis Vibrations to One-Axis Vibrations Park, G., Kuchenbecker, K. J. In Proceedings of the IEEE World Haptics Conference (WHC), 467-472, Tokyo, Japan, July 2019 (Published)

Abstract ›

A typical approach to creating realistic vibrotactile feedback is reducing 3D vibrations recorded by an accelerometer to 1D signals that can be played back on a haptic actuator, but some of the information is often lost in this dimensional reduction process. This paper describes seven representative algorithms and proposes four metrics based on the spectral match, the temporal match, and the average value and the variability of them across 3D rotations. These four performance metrics were applied to four texture recordings, and the method utilizing the discrete fourier transform (DFT) was found to be the best regardless of the sensing axis. We also recruited 16 participants to assess the perceptual similarity achieved by each algorithm in real time. We found the four metrics correlated well with the subjectively rated similarities for the six dimensional reduction algorithms, with the exception of taking the 3D vector magnitude, which was perceived to be good despite its low spectral and temporal match metrics.

DOI BibTeX

Haptic Intelligence Miscellaneous Reducing 3D Vibrations to 1D in Real Time Park, G., Kuchenbecker, K. J. Hands-on demonstration presented at EuroHaptics, Pisa, Italy, June 2018 (Published)

Abstract ›

In this demonstration, you will hold two pen-shaped modules: an in-pen and an out-pen. The in-pen is instrumented with a high-bandwidth three-axis accelerometer, and the out-pen contains a one-axis voice coil actuator. Use the in-pen to interact with different surfaces; the measured 3D accelerations are continually converted into 1D vibrations and rendered with the out-pen for you to feel. You can test conversion methods that range from simply selecting a single axis to applying a discrete Fourier transform or principal component analysis for realistic and brisk real-time conversion.

BibTeX

Haptic Intelligence Miscellaneous Reducing 3D Vibrations to 1D in Real Time Park, G., Kuchenbecker, K. J. Haptic Interaction (Proceedings of AsiaHaptics 2018), 535:21-24, Hands-on demonstration (4 pages) presented at AsiaHaptics, Incheon, South Korea, May 2018 (Published)

Abstract ›

For simple and realistic vibrotactile feedback, 3D accelerations from real contact interactions are usually rendered using a single-axis vibration actuator; this dimensional reduction can be performed in many ways. This demonstration implements a real-time conversion system that simultaneously measures 3D accelerations and renders corresponding 1D vibrations using a two-pen interface. In the demonstration, a user freely interacts with various objects using an In-Pen that contains a 3-axis accelerometer. The captured accelerations are converted to a single-axis signal, and an Out-Pen renders the reduced signal for the user to feel. We prepared seven conversion methods from the simple use of a single-axis signal to applying principal component analysis (PCA) so that users can compare the performance of each conversion method in this demonstration.

DOI BibTeX