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2020


Characterization of a Magnetic Levitation Haptic Interface for Realistic Tool-Based Interactions
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 (misc)

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.

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link (url) [BibTex]

2020


link (url) [BibTex]


Tactile Textiles: An Assortment of Fabric-Based Tactile Sensors for Contact Force and Contact Location
Tactile Textiles: An Assortment of Fabric-Based Tactile Sensors for Contact Force and Contact Location

Burns, R. B., Thomas, N., Lee, H., Faulkner, R., Kuchenbecker, K. J.

Hands-on demonstration presented at EuroHaptics, Leiden, The Netherlands, September 2020, Rachael Bevill Burns, Neha Thomas, and Hyosang Lee contributed equally to this publication (misc)

Abstract
Fabric-based tactile sensors are promising for the construction of robotic skin due to their soft and flexible nature. Conductive fabric layers can be used to form piezoresistive structures that are sensitive to contact force and/or contact location. This demonstration showcases three diverse fabric-based tactile sensors we have created. The first detects dynamic tactile events anywhere within a region on a robot’s body. The second design measures the precise location at which a single low-force contact is applied. The third sensor uses electrical resistance tomography to output both the force and location of multiple simultaneous contacts applied across a surface.

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Project Page Project Page [BibTex]

Project Page Project Page [BibTex]


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Estimating Human Handshape by Feeling the Wrist

Forte, M., Young, E. M., Kuchenbecker, K. J.

Work-in-progress poster presented at EuroHaptics, Leiden, The Netherlands, September 2020 (misc)

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[BibTex]

[BibTex]


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Intermediate Ridges Amplify Mechanoreceptor Strains in Static and Dynamic Touch

Serhat, G., Kuchenbecker, K. J.

Work-in-progress poster presented at the EuroHaptics (EH), Leiden, The Netherlands, September 2020 (misc)

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[BibTex]

[BibTex]


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Seeing through Touch: Contact-Location Sensing and Tactile Feedback for Prosthetic Hands

Thomas, N., Kuchenbecker, K. J.

Works-in-progress abstract and poster presented at Eurohaptics 2020, Leiden, Netherlands, September 2020 (misc)

Abstract
Locating and picking up an object without vision is a simple task for able-bodied people, due in part to their rich tactile perception capabilities. The same cannot be said for users of standard myoelectric prostheses, who must rely largely on visual cues to successfully interact with the environment. To enable prosthesis users to locate and grasp objects without looking at them, we propose two changes: adding specialized contact-location sensing to the dorsal and palmar aspects of the prosthetic hand’s fingers, and providing the user with tactile feedback of where an object touches the fingers. To evaluate the potential utility of these changes, we developed a simple, sensitive, fabric-based tactile sensor which provides continuous contact location information via a change in voltage of a voltage divider circuit. This sensor was wrapped around the fingers of a commercial prosthetic hand (Ottobock SensorHand Speed). Using an ATI Nano17 force sensor, we characterized the tactile sensor’s response to normal force at distributed contact locations and obtained an average detection threshold of 0.63 +/- 0.26 N. We also confirmed that the voltage-to-location mapping is linear (R squared = 0.99). Sensor signals were adapted to the stationary vibrotactile funneling illusion to provide haptic feedback of contact location. These preliminary results indicate a promising system that imitates a key aspect of the sensory capabilities of the intact hand. Future work includes testing the system in a modified reach-grasp-and-lift study, in which participants must accomplish the task blindfolded.

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[BibTex]

[BibTex]


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Vision-based Force Estimation for a da Vinci Instrument Using Deep Neural Networks

Lee, Y., Husin, H. M., Forte, M., Lee, S., Kuchenbecker, K. J.

Extended abstract presented as an Emerging Technology ePoster at the Annual Meeting of the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES), Cleveland, Ohio, USA, August 2020 (misc) Accepted

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[BibTex]

[BibTex]


A Fabric-Based Sensing System for Recognizing Social Touch
A Fabric-Based Sensing System for Recognizing Social Touch

Burns, R. B., Lee, H., Seifi, H., Kuchenbecker, K. J.

Work-in-progress paper (3 pages) presented at the IEEE Haptics Symposium, Washington, DC, USA, March 2020 (misc)

Abstract
We present a fabric-based piezoresistive tactile sensor system designed to detect social touch gestures on a robot. The unique sensor design utilizes three layers of low-conductivity fabric sewn together on alternating edges to form an accordion pattern and secured between two outer high-conductivity layers. This five-layer design demonstrates a greater resistance range and better low-force sensitivity than previous designs that use one layer of low-conductivity fabric with or without a plastic mesh layer. An individual sensor from our system can presently identify six different communication gestures – squeezing, patting, scratching, poking, hand resting without movement, and no touch – with an average accuracy of 90%. A layer of foam can be added beneath the sensor to make a rigid robot more appealing for humans to touch without inhibiting the system’s ability to register social touch gestures.

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Project Page [BibTex]

Project Page [BibTex]


Do Touch Gestures Affect How Electrovibration Feels?
Do Touch Gestures Affect How Electrovibration Feels?

Vardar, Y., Kuchenbecker, K. J.

Hands-on demonstration (1 page) presented at the IEEE Haptics Symposium, Washington, DC, USA, March 2020 (misc)

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[BibTex]

[BibTex]


Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art
Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art

Janai, J., Güney, F., Behl, A., Geiger, A.

Arxiv, Foundations and Trends in Computer Graphics and Vision, 2020 (book)

Abstract
Recent years have witnessed enormous progress in AI-related fields such as computer vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it becomes increasingly difficult to stay up-to-date or enter the field as a beginner. While several survey papers on particular sub-problems have appeared, no comprehensive survey on problems, datasets, and methods in computer vision for autonomous vehicles has been published. This monograph attempts to narrow this gap by providing a survey on the state-of-the-art datasets and techniques. Our survey includes both the historically most relevant literature as well as the current state of the art on several specific topics, including recognition, reconstruction, motion estimation, tracking, scene understanding, and end-to-end learning for autonomous driving. Towards this goal, we analyze the performance of the state of the art on several challenging benchmarking datasets, including KITTI, MOT, and Cityscapes. Besides, we discuss open problems and current research challenges. To ease accessibility and accommodate missing references, we also provide a website that allows navigating topics as well as methods and provides additional information.

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pdf Project Page link Project Page [BibTex]

2015


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Haptic Textures for Online Shopping

Culbertson, H., Kuchenbecker, K. J.

Interactive demonstrations in The Retail Collective exhibit, presented at the Dx3 Conference in Toronto, Canada, March 2015 (misc)

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[BibTex]

2015


[BibTex]

2012


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Simon Game with Data-driven Visuo-audio-haptic Buttons

Castillo, P., Romano, J. M., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Vancouver, Canada, March 2012 (misc)

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[BibTex]

2012


[BibTex]


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Haptic Vibration Feedback for a Teleoperated Ground Vehicle

Healey, S. K., McMahan, W., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Vancouver, Canada, March 2012 (misc)

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[BibTex]

[BibTex]


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A Biofidelic CPR Manikin With Programmable Pneumatic Damping

Stanley, A. A., Healey, S. K., Maltese, M. R., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Vancouver, Canada, March 2012, Finalist for Best Hands-on Demonstration Award (misc)

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[BibTex]

[BibTex]


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StrokeSleeve: Real-Time Vibrotactile Feedback for Motion Guidance

Bark, K., Cha, E., Tan, F., Jax, S. A., Buxbaum, L. J., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Vancouver, Canada, Vancouver, Canada, March 2012 (misc)

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[BibTex]

[BibTex]


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Pen Tablet Drawing Program with Haptic Textures

Castillo, P., Romano, J. M., Culbertson, H., Mintz, M., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Vancouver, Canada, March 2012 (misc)

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[BibTex]

[BibTex]


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Exploring Presentation Timing through Haptic Reminders

Tam, D., Kuchenbecker, K. J., MacLean, K., McGrenere, J.

Hands-on demonstration presented at IEEE Haptics Symposium, Vancouver, Canada, March 2012 (misc)

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[BibTex]

[BibTex]


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HALO: Haptic Alerts for Low-hanging Obstacles in White Cane Navigation

Wang, Y., Koch, E., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Vancouver, Canada, March 2012, Finalist for Best Hands-on Demonstration Award (misc)

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[BibTex]

[BibTex]


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VerroTeach: Visuo-audio-haptic Training for Dental Caries Detection

Maggio, M. P., Parajon, R., Kuchenbecker, K. J.

Hands-on demonstration presented at IEEE Haptics Symposium, Vancouver, Canada, March 2012, {B}est Demonstration Award (three-way tie) (misc)

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[BibTex]

[BibTex]


Consumer Depth Cameras for Computer Vision - Research Topics and Applications
Consumer Depth Cameras for Computer Vision - Research Topics and Applications

Fossati, A., Gall, J., Grabner, H., Ren, X., Konolige, K.

Advances in Computer Vision and Pattern Recognition, Springer, 2012 (book)

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workshop publisher's site [BibTex]

workshop publisher's site [BibTex]