Haptic Intelligence

184 results (View BibTeX file of all listed publications)

2024

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Demonstration: OCRA - A Kinematic Retargeting Algorithm for Expressive Whole-Arm Teleoperation

Mohan, M., Kuchenbecker, K. J.

Hands-on demonstration presented at the Conference on Robot Learning (CoRL), Munich, Germany, November 2024 (misc) Accepted

Abstract
Traditional teleoperation systems focus on controlling the pose of the end-effector (task space), often neglecting the additional degrees of freedom present in human and many robotic arms. This demonstration presents the Optimization-based Customizable Retargeting Algorithm (OCRA), which was designed to map motions from one serial kinematic chain to another in real time. OCRA is versatile, accommodating any robot joint counts and segment lengths, and it can retarget motions from human arms to kinematically different serial robot arms with revolute joints both expressively and efficiently. One of OCRA's key features is its customizability, allowing the user to adjust the emphasis between hand orientation error and the configuration error of the arm's central line, which we call the arm skeleton. To evaluate the perceptual quality of the motions generated by OCRA, we conducted a video-watching study with 70 participants; the results indicated that the algorithm produces robot motions that closely resemble human movements, with a median rating of 78/100, particularly when the arm skeleton error weight and hand orientation error are balanced. In this demonstration, the presenter will wear an Xsens MVN Link and teleoperate the arms of a NAO child-size humanoid robot to highlight OCRA's ability to create intuitive and human-like whole-arm motions.

[BibTex]

2024

Mohan, M., Kuchenbecker, K. J. Demonstration: OCRA - A Kinematic Retargeting Algorithm for Expressive Whole-Arm Teleoperation Hands-on demonstration presented at the Conference on Robot Learning (CoRL), Munich, Germany, November 2024 (misc) Accepted

[BibTex]

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Demonstration: Minsight - A Soft Vision-Based Tactile Sensor for Robotic Fingertips

Andrussow, I., Sun, H., Martius, G., Kuchenbecker, K. J.

Hands-on demonstration presented at the Conference on Robot Learning (CoRL), Munich, Germany, November 2024 (misc) Accepted

Abstract
Beyond vision and hearing, tactile sensing enhances a robot's ability to dexterously manipulate unfamiliar objects and safely interact with humans. Giving touch sensitivity to robots requires compact, robust, affordable, and efficient hardware designs, especially for high-resolution tactile sensing. We present a soft vision-based tactile sensor engineered to meet these requirements. Comparable in size to a human fingertip, Minsight uses machine learning to output high-resolution directional contact force distributions at 60 Hz. Minsight's tactile force maps enable precise sensing of fingertip contacts, which we use in this hands-on demonstration to allow a 3-DoF robot arm to physically track contact with a user's finger. While observing the colorful image captured by Minsight's internal camera, attendees can experience how its ability to detect delicate touches in all directions facilitates real-time robot interaction.

Project Page [BibTex]

Andrussow, I., Sun, H., Martius, G., Kuchenbecker, K. J. Demonstration: Minsight - A Soft Vision-Based Tactile Sensor for Robotic Fingertips Hands-on demonstration presented at the Conference on Robot Learning (CoRL), Munich, Germany, November 2024 (misc) Accepted

Project Page [BibTex]

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Active Haptic Feedback for a Virtual Wrist-Anchored User Interface

Bartels, J. U., Sanchez-Tamayo, N., Sedlmair, M., Kuchenbecker, K. J.

Hands-on demonstration presented at the ACM Symposium on User Interface Software and Technology (UIST), Pittsburgh, USA, October 2024 (misc) Accepted

DOI [BibTex]

Bartels, J. U., Sanchez-Tamayo, N., Sedlmair, M., Kuchenbecker, K. J. Active Haptic Feedback for a Virtual Wrist-Anchored User Interface Hands-on demonstration presented at the ACM Symposium on User Interface Software and Technology (UIST), Pittsburgh, USA, October 2024 (misc) Accepted

DOI [BibTex]

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Fiber-Optic Shape Sensing Using Neural Networks Operating on Multispecklegrams

Cao, C. G. L., Javot, B., Bhattarai, S., Bierig, K., Oreshnikov, I., Volchkov, V. V.

IEEE Sensors Journal, 24(17):27532-27540, September 2024 (article)

Abstract
Application of machine learning techniques on fiber speckle images to infer fiber deformation allows the use of an unmodified multimode fiber to act as a shape sensor. This approach eliminates the need for complex fiber design or construction (e.g., Bragg gratings and time-of-flight). Prior work in shape determination using neural networks trained on a finite number of possible fiber shapes (formulated as a classification task), or trained on a few continuous degrees of freedom, has been limited to reconstruction of fiber shapes only one bend at a time. Furthermore, generalization to shapes that were not used in training is challenging. Our innovative approach improves generalization capabilities, using computer vision-assisted parameterization of the actual fiber shape to provide a ground truth, and multiple specklegrams per fiber shape obtained by controlling the input field. Results from experimenting with several neural network architectures, shape parameterization, number of inputs, and specklegram resolution show that fiber shapes with multiple bends can be accurately predicted. Our approach is able to generalize to new shapes that were not in the training set. This approach of end-to-end training on parameterized ground truth opens new avenues for fiber-optic sensor applications. We publish the datasets used for training and validation, as well as an out-of-distribution (OOD) test set, and encourage interested readers to access these datasets for their own model development.

DOI [BibTex]

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Cutaneous Electrohydraulic (CUTE) Wearable Devices for Pleasant Broad-Bandwidth Haptic Cues

Sanchez-Tamayo, N., Yoder, Z., Rothemund, P., Ballardini, G., Keplinger, C., Kuchenbecker, K. J.

Advanced Science, (2402461):1-14, September 2024 (article)

Abstract
By focusing on vibrations, current wearable haptic devices underutilize the skin's perceptual capabilities. Devices that provide richer haptic stimuli, including contact feedback and/or variable pressure, are typically heavy and bulky due to the underlying actuator technology and the low sensitivity of hairy skin, which covers most of the body. This paper presents a system architecture for compact wearable devices that deliver salient and pleasant broad-bandwidth haptic cues: Cutaneous Electrohydraulic (CUTE) devices combine a custom materials design for soft haptic electrohydraulic actuators that feature high stroke, high force, and electrical safety with a comfortable mounting strategy that places the actuator in a non-contact resting position. A prototypical wrist-wearable CUTE device produces rich tactile sensations by making and breaking contact with the skin (2.44 mm actuation stroke), applying high controllable forces (exceeding 2.3 N), and delivering vibrations at a wide range of amplitudes and frequencies (0-200 Hz). A perceptual study with fourteen participants achieved 97.9% recognition accuracy across six diverse cues and verified their pleasant and expressive feel. This system architecture for wearable devices gives unprecedented control over the haptic cues delivered to the skin, providing an elegant and discreet way to activate the user's sense of touch.

DOI [BibTex]

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Modeling Shank Tissue Properties and Quantifying Body Composition with a Wearable Actuator-Accelerometer Set

Rokhmanova, N., Martus, J., Faulkner, R., Fiene, J., Kuchenbecker, K. J.

Extended abstract (1 page) presented at the American Society of Biomechanics Annual Meeting (ASB), Madison, USA, August 2024 (misc)

Project Page [BibTex]

Rokhmanova, N., Martus, J., Faulkner, R., Fiene, J., Kuchenbecker, K. J. Modeling Shank Tissue Properties and Quantifying Body Composition with a Wearable Actuator-Accelerometer Set Extended abstract (1 page) presented at the American Society of Biomechanics Annual Meeting (ASB), Madison, USA, August 2024 (misc)

Project Page [BibTex]

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Adapting a High-Fidelity Simulation of Human Skin for Comparative Touch Sensing

Schulz, A., Serhat, G., Kuchenbecker, K. J.

Extended abstract (1 page) presented at the American Society of Biomechanics Annual Meeting (ASB), Madison, USA, August 2024 (misc)

[BibTex]

Schulz, A., Serhat, G., Kuchenbecker, K. J. Adapting a High-Fidelity Simulation of Human Skin for Comparative Touch Sensing Extended abstract (1 page) presented at the American Society of Biomechanics Annual Meeting (ASB), Madison, USA, August 2024 (misc)

[BibTex]

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Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test

Khojasteh, B., Solowjow, F., Trimpe, S., Kuchenbecker, K. J.

IEEE Transactions on Automation Science and Engineering, 21(3):4432-4447, July 2024 (article)

Abstract
Machine learning and deep learning have been used extensively to classify physical surfaces through images and time-series contact data. However, these methods rely on human expertise and entail the time-consuming processes of data and parameter tuning. To overcome these challenges, we propose an easily implemented framework that can directly handle heterogeneous data sources for classification tasks. Our data-versus-data approach automatically quantifies distinctive differences in distributions in a high-dimensional space via kernel two-sample testing between two sets extracted from multimodal data (e.g., images, sounds, haptic signals). We demonstrate the effectiveness of our technique by benchmarking against expertly engineered classifiers for visual-audio-haptic surface recognition due to the industrial relevance, difficulty, and competitive baselines of this application; ablation studies confirm the utility of key components of our pipeline. As shown in our open-source code, we achieve 97.2% accuracy on a standard multi-user dataset with 108 surface classes, outperforming the state-of-the-art machine-learning algorithm by 6% on a more difficult version of the task. The fact that our classifier obtains this performance with minimal data processing in the standard algorithm setting reinforces the powerful nature of kernel methods for learning to recognize complex patterns. Note to Practitioners—We demonstrate how to apply the kernel two-sample test to a surface-recognition task, discuss opportunities for improvement, and explain how to use this framework for other classification problems with similar properties. Automating surface recognition could benefit both surface inspection and robot manipulation. Our algorithm quantifies class similarity and therefore outputs an ordered list of similar surfaces. This technique is well suited for quality assurance and documentation of newly received materials or newly manufactured parts. More generally, our automated classification pipeline can handle heterogeneous data sources including images and high-frequency time-series measurements of vibrations, forces and other physical signals. As our approach circumvents the time-consuming process of feature engineering, both experts and non-experts can use it to achieve high-accuracy classification. It is particularly appealing for new problems without existing models and heuristics. In addition to strong theoretical properties, the algorithm is straightforward to use in practice since it requires only kernel evaluations. Its transparent architecture can provide fast insights into the given use case under different sensing combinations without costly optimization. Practitioners can also use our procedure to obtain the minimum data-acquisition time for independent time-series data from new sensor recordings.

DOI Project Page [BibTex]

Khojasteh, B., Solowjow, F., Trimpe, S., Kuchenbecker, K. J. Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test IEEE Transactions on Automation Science and Engineering, 21(3):4432-4447, July 2024 (article)

DOI Project Page [BibTex]

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Errors in Long-Term Robotic Surgical Training

Lev, H. K., Sharon, Y., Geftler, A., Nisky, I.

Work-in-progress paper (3 pages) presented at the EuroHaptics Conference, Lille, France, June 2024 (misc)

Abstract
Robotic surgeries offer many advantages but require surgeons to master complex motor tasks over years. Most motor-control studies focus on simple tasks and span days at most. To help bridge this gap, we followed surgical residents learning complex tasks on a surgical robot over six months. Here, we focus on the task of moving a ring along a curved wire as quickly and accurately as possible. We wrote an image processing algorithm to locate the errors in the task and computed error metrics and task completion time. We found that participants decreased their completion time and number of errors over the six months, however, the percentage of error time in the task remained constant. This long-term study sheds light on the learning process of the surgeons and opens the possibility of further studying their errors with the aim of minimizing them.

DOI [BibTex]

Lev, H. K., Sharon, Y., Geftler, A., Nisky, I. Errors in Long-Term Robotic Surgical Training Work-in-progress paper (3 pages) presented at the EuroHaptics Conference, Lille, France, June 2024 (misc)

DOI [BibTex]

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GaitGuide: A Wearable Device for Vibrotactile Motion Guidance

Rokhmanova, N., Martus, J., Faulkner, R., Fiene, J., Kuchenbecker, K. J.

Workshop paper (3 pages) presented at the ICRA Workshop on Advancing Wearable Devices and Applications Through Novel Design, Sensing, Actuation, and AI, Yokohama, Japan, May 2024 (misc)

Abstract
Wearable vibrotactile devices can provide salient sensations that attract the user's attention or guide them to change. The future integration of such feedback into medical or consumer devices would benefit from understanding how vibrotactile cues vary in amplitude and perceived strength across the heterogeneity of human skin. Here, we developed an adhesive vibrotactile device (the GaitGuide) that uses two individually mounted linear resonant actuators to deliver directional motion guidance. By measuring the mechanical vibrations of the actuators via small on-board accelerometers, we compared vibration amplitudes and perceived signal strength across 20 subjects at five signal voltages and four sites around the shank. Vibrations were consistently smallest in amplitude—but perceived to be strongest—at the site located over the tibia. We created a fourth-order linear dynamic model to capture differences in tissue properties across subjects and sites via optimized stiffness and damping parameters. The anterior site had significantly higher skin stiffness and damping; these values also correlate with subject-specific body-fat percentages. Surprisingly, our study shows that the perception of vibrotactile stimuli does not solely depend on the vibration magnitude delivered to the skin. These findings also help to explain the clinical practice of evaluating vibrotactile sensitivity over a bony prominence.

link (url) Project Page [BibTex]

Rokhmanova, N., Martus, J., Faulkner, R., Fiene, J., Kuchenbecker, K. J. GaitGuide: A Wearable Device for Vibrotactile Motion Guidance Workshop paper (3 pages) presented at the ICRA Workshop on Advancing Wearable Devices and Applications Through Novel Design, Sensing, Actuation, and AI, Yokohama, Japan, May 2024 (misc)

link (url) Project Page [BibTex]

Fingertip Dynamic Response Simulated Across Excitation Points and Frequencies
Fingertip Dynamic Response Simulated Across Excitation Points and Frequencies

Serhat, G., Kuchenbecker, K. J.

Biomechanics and Modeling in Mechanobiology, 23, pages: 1369-1376, May 2024 (article)

Abstract
Predicting how the fingertip will mechanically respond to different stimuli can help explain human haptic perception and enable improvements to actuation approaches such as ultrasonic mid-air haptics. This study addresses this goal using high-fidelity 3D finite element analyses. We compute the deformation profiles and amplitudes caused by harmonic forces applied in the normal direction at four locations: the center of the finger pad, the side of the finger, the tip of the finger, and the oblique midpoint of these three sites. The excitation frequency is swept from 2.5 to 260 Hz. The simulated frequency response functions (FRFs) obtained for displacement demonstrate that the relative magnitudes of the deformations elicited by stimulating at each of these four locations greatly depends on whether only the excitation point or the entire finger is considered. The point force that induces the smallest local deformation can even cause the largest overall deformation at certain frequency intervals. Above 225 Hz, oblique excitation produces larger mean displacement amplitudes than the other three forces due to excitation of multiple modes involving diagonal deformation. These simulation results give novel insights into the combined influence of excitation location and frequency on the fingertip dynamic response, potentially facilitating the design of future vibration feedback devices.

DOI Project Page [BibTex]

Serhat, G., Kuchenbecker, K. J. Fingertip Dynamic Response Simulated Across Excitation Points and Frequencies Biomechanics and Modeling in Mechanobiology, 23, pages: 1369-1376, May 2024 (article)

DOI Project Page [BibTex]

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Three-Dimentional Surface Reconstruction of a Soft System via Distributed Magnetic Sensing

Sundaram, V. H., Smith, L., Turin, Z., Rentschler, M. E., Welker, C. G.

Workshop paper (3 pages) presented at the ICRA Workshop on Advancing Wearable Devices and Applications Through Novel Design, Sensing, Actuation, and AI, Yokohama, Japan, May 2024 (misc)

Abstract
This study presents a new method for reconstructing continuous 3D surface deformations for a soft pneumatic actuation system using embedded magnetic sensors. A finite element analysis (FEA) model was developed to quantify the surface deformation given the magnetometer readings, with a relative error between the experimental and the simulated sensor data of 7.8%. Using the FEA simulation solutions and a basic model-based mapping, our method achieves sub-millimeter accuracy in measuring deformation from sensor data with an absolute error between the experimental and simulated sensor data of 13.5%. These results show promise for real-time adjustments to deformation, crucial in environments like prosthetic and orthotic interfaces with human limbs.

[BibTex]

Sundaram, V. H., Smith, L., Turin, Z., Rentschler, M. E., Welker, C. G. Three-Dimentional Surface Reconstruction of a Soft System via Distributed Magnetic Sensing Workshop paper (3 pages) presented at the ICRA Workshop on Advancing Wearable Devices and Applications Through Novel Design, Sensing, Actuation, and AI, Yokohama, Japan, May 2024 (misc)

[BibTex]

Closing the Loop in Minimally Supervised Human-Robot Interaction: Formative and Summative Feedback
Closing the Loop in Minimally Supervised Human-Robot Interaction: Formative and Summative Feedback

Mohan, M., Nunez, C. M., Kuchenbecker, K. J.

Scientific Reports, 14(10564):1-18, May 2024 (article)

Abstract
Human instructors fluidly communicate with hand gestures, head and body movements, and facial expressions, but robots rarely leverage these complementary cues. A minimally supervised social robot with such skills could help people exercise and learn new activities. Thus, we investigated how nonverbal feedback from a humanoid robot affects human behavior. Inspired by the education literature, we evaluated formative feedback (real-time corrections) and summative feedback (post-task scores) for three distinct tasks: positioning in the room, mimicking the robot's arm pose, and contacting the robot's hands. Twenty-eight adults completed seventy-five 30-second-long trials with no explicit instructions or experimenter help. Motion-capture data analysis shows that both formative and summative feedback from the robot significantly aided user performance. Additionally, formative feedback improved task understanding. These results show the power of nonverbal cues based on human movement and the utility of viewing feedback through formative and summative lenses.

DOI Project Page [BibTex]

Airo{T}ouch: Enhancing Telerobotic Assembly through Naturalistic Haptic Feedback of Tool Vibrations
AiroTouch: Enhancing Telerobotic Assembly through Naturalistic Haptic Feedback of Tool Vibrations

Gong, Y., Husin, H. M., Erol, E., Ortenzi, V., Kuchenbecker, K. J.

Frontiers in Robotics and AI, 11, pages: 1-15, May 2024 (article)

Abstract
Teleoperation allows workers to safely control powerful construction machines; however, its primary reliance on visual feedback limits the operator's efficiency in situations with stiff contact or poor visibility, hindering its use for assembly of pre-fabricated building components. Reliable, economical, and easy-to-implement haptic feedback could fill this perception gap and facilitate the broader use of robots in construction and other application areas. Thus, we adapted widely available commercial audio equipment to create AiroTouch, a naturalistic haptic feedback system that measures the vibration experienced by each robot tool and enables the operator to feel a scaled version of this vibration in real time. Accurate haptic transmission was achieved by optimizing the positions of the system's off-the-shelf accelerometers and voice-coil actuators. A study was conducted to evaluate how adding this naturalistic type of vibrotactile feedback affects the operator during telerobotic assembly. Thirty participants used a bimanual dexterous teleoperation system (Intuitive da Vinci Si) to build a small rigid structure under three randomly ordered haptic feedback conditions: no vibrations, one-axis vibrations, and summed three-axis vibrations. The results show that users took advantage of both tested versions of the naturalistic haptic feedback after gaining some experience with the task, causing significantly lower vibrations and forces in the second trial. Subjective responses indicate that haptic feedback increased the realism of the interaction and reduced the perceived task duration, task difficulty, and fatigue. As hypothesized, higher haptic feedback gains were chosen by users with larger hands and for the smaller sensed vibrations in the one-axis condition. These results elucidate important details for effective implementation of naturalistic vibrotactile feedback and demonstrate that our accessible audio-based approach could enhance user performance and experience during telerobotic assembly in construction and other application domains.

DOI Project Page [BibTex]

{CAPT} Motor: A Strong Direct-Drive Rotary Haptic Interface
CAPT Motor: A Strong Direct-Drive Rotary Haptic Interface

Javot, B., Nguyen, V. H., Ballardini, G., Kuchenbecker, K. J.

Hands-on demonstration presented at the IEEE Haptics Symposium, Long Beach, USA, April 2024 (misc)

Abstract
We have designed and built a new motor named CAPT Motor that delivers continuous and precise torque. It is a brushless ironless motor using a Halbach-magnet ring and a planar axial Lorentz-coil array. This motor is unique as we use a two-phase design allowing for higher fill factor and geometrical accuracy of the coils, as they can all be made separately. This motor outperforms existing Halbach ring and cylinder motors with a torque constant per magnet volume of 9.94 (Nm/A)/dm3, a record in the field. The angular position of the rotor is measured by a high-resolution incremental optical encoder and tracked by a multimodal data acquisition device. The system's control firmware uses this angle measurement to calculate the two-phase motor currents needed to produce the torque commanded by the virtual environment at the rotor's position. The strength and precision of the CAPT Motor's torque and the lack of any mechanical transmission enable unusually high haptic rendering quality, indicating the promise of this new motor design.

link (url) Project Page [BibTex]

Javot, B., Nguyen, V. H., Ballardini, G., Kuchenbecker, K. J. CAPT Motor: A Strong Direct-Drive Rotary Haptic Interface Hands-on demonstration presented at the IEEE Haptics Symposium, Long Beach, USA, April 2024 (misc)

link (url) Project Page [BibTex]

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Quantifying Haptic Quality: External Measurements Match Expert Assessments of Stiffness Rendering Across Devices

Fazlollahi, F., Seifi, H., Ballardini, G., Taghizadeh, Z., Schulz, A., MacLean, K. E., Kuchenbecker, K. J.

Work-in-progress paper (2 pages) presented at the IEEE Haptics Symposium, Long Beach, USA, April 2024 (misc)

Project Page [BibTex]

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Cutaneous Electrohydraulic (CUTE) Wearable Devices for Multimodal Haptic Feedback

Sanchez-Tamayo, N., Yoder, Z., Ballardini, G., Rothemund, P., Keplinger, C., Kuchenbecker, K. J.

Extended abstract (1 page) presented at the IEEE RoboSoft Workshop on Multimodal Soft Robots for Multifunctional Manipulation, Locomotion, and Human-Machine Interaction, San Diego, USA, April 2024 (misc)

[BibTex]

Sanchez-Tamayo, N., Yoder, Z., Ballardini, G., Rothemund, P., Keplinger, C., Kuchenbecker, K. J. Cutaneous Electrohydraulic (CUTE) Wearable Devices for Multimodal Haptic Feedback Extended abstract (1 page) presented at the IEEE RoboSoft Workshop on Multimodal Soft Robots for Multifunctional Manipulation, Locomotion, and Human-Machine Interaction, San Diego, USA, April 2024 (misc)

[BibTex]

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Modeling Fatigue in Manual and Robot-Assisted Work for Operator 5.0

Allemang–Trivalle, A., Donjat, J., Bechu, G., Coppin, G., Chollet, M., Klaproth, O. W., Mitschke, A., Schirrmann, A., Cao, C. G. L.

IISE Transactions on Occupational Ergonomics and Human Factors, 12(1-2):135-147, March 2024 (article)

DOI [BibTex]

Allemang–Trivalle, A., Donjat, J., Bechu, G., Coppin, G., Chollet, M., Klaproth, O. W., Mitschke, A., Schirrmann, A., Cao, C. G. L. Modeling Fatigue in Manual and Robot-Assisted Work for Operator 5.0 IISE Transactions on Occupational Ergonomics and Human Factors, 12(1-2):135-147, March 2024 (article)

DOI [BibTex]

{IMU}-Based Kinematics Estimation Accuracy Affects Gait Retraining Using Vibrotactile Cues
IMU-Based Kinematics Estimation Accuracy Affects Gait Retraining Using Vibrotactile Cues

Rokhmanova, N., Pearl, O., Kuchenbecker, K. J., Halilaj, E.

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32, pages: 1005-1012, February 2024 (article)

Abstract
Wearable sensing using inertial measurement units (IMUs) is enabling portable and customized gait retraining for knee osteoarthritis. However, the vibrotactile feedback that users receive directly depends on the accuracy of IMU-based kinematics. This study investigated how kinematic errors impact an individual's ability to learn a therapeutic gait using vibrotactile cues. Sensor accuracy was computed by comparing the IMU-based foot progression angle to marker-based motion capture, which was used as ground truth. Thirty subjects were randomized into three groups to learn a toe-in gait: one group received vibrotactile feedback during gait retraining in the laboratory, another received feedback outdoors, and the control group received only verbal instruction and proceeded directly to the evaluation condition. All subjects were evaluated on their ability to maintain the learned gait in a new outdoor environment. We found that subjects with high tracking errors exhibited more incorrect responses to vibrotactile cues and slower learning rates than subjects with low tracking errors. Subjects with low tracking errors outperformed the control group in the evaluation condition, whereas those with higher error did not. Errors were correlated with foot size and angle magnitude, which may indicate a non-random algorithmic bias. The accuracy of IMU-based kinematics has a cascading effect on feedback; ignoring this effect could lead researchers or clinicians to erroneously classify a patient as a non-responder if they did not improve after retraining. To use patient and clinician time effectively, future implementation of portable gait retraining will require assessment across a diverse range of patients.

DOI Project Page [BibTex]

Rokhmanova, N., Pearl, O., Kuchenbecker, K. J., Halilaj, E. IMU-Based Kinematics Estimation Accuracy Affects Gait Retraining Using Vibrotactile Cues IEEE Transactions on Neural Systems and Rehabilitation Engineering, 32, pages: 1005-1012, February 2024 (article)

DOI Project Page [BibTex]

Adapting a High-Fidelity Simulation of Human Skin for Comparative Touch Sensing in the Elephant Trunk
Adapting a High-Fidelity Simulation of Human Skin for Comparative Touch Sensing in the Elephant Trunk

Schulz, A., Serhat, G., Kuchenbecker, K. J.

Abstract presented at the Society for Integrative and Comparative Biology Annual Meeting (SICB), Seattle, USA, January 2024 (misc)

Abstract
Skin is a complex biological composite consisting of layers with distinct mechanical properties, morphologies, and mechanosensory capabilities. This work seeks to expand the comparative biomechanics field to comparative haptics, analyzing elephant trunk touch by redesigning a previously published human finger-pad model with morphological parameters measured from an elephant trunk. The dorsal surface of the elephant trunk has a thick, wrinkled epidermis covered with whiskers at the distal tip and deep folds at the proximal base. We hypothesize that this thick dorsal skin protects the trunk from mechanical damage but significantly dulls its tactile sensing ability. To facilitate safe and dexterous motion, the distributed dorsal whiskers might serve as pre-touch antennae, transmitting an amplified version of impending contact to the mechanoreceptors beneath the elephant's armor. We tested these hypotheses by simulating soft tissue deformation through high-fidelity finite element analyses involving representative skin layers and whiskers, modeled based on frozen African elephant trunk (Loxodonta africana) morphology. For a typical contact force, quintupling the stratum corneum thickness to match dorsal trunk skin reduces the von Mises stress communicated to the dermis by 18%. However, adding a whisker offsets this dulled sensing, as hypothesized, amplifying the stress by more than 15 at the same location. We hope this work will motivate further investigations of mammalian touch using approaches and models from the ample literature on human touch.

[BibTex]

Schulz, A., Serhat, G., Kuchenbecker, K. J. Adapting a High-Fidelity Simulation of Human Skin for Comparative Touch Sensing in the Elephant Trunk Abstract presented at the Society for Integrative and Comparative Biology Annual Meeting (SICB), Seattle, USA, January 2024 (misc)

[BibTex]

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MPI-10: Haptic-Auditory Measurements from Tool-Surface Interactions

Khojasteh, B., Shao, Y., Kuchenbecker, K. J.

Dataset published as a companion to the journal article "Robust Surface Recognition with the Maximum Mean Discrepancy: Degrading Haptic-Auditory Signals through Bandwidth and Noise" in IEEE Transactions on Haptics, January 2024 (misc)

DOI Project Page [BibTex]

Khojasteh, B., Shao, Y., Kuchenbecker, K. J. MPI-10: Haptic-Auditory Measurements from Tool-Surface Interactions Dataset published as a companion to the journal article "Robust Surface Recognition with the Maximum Mean Discrepancy: Degrading Haptic-Auditory Signals through Bandwidth and Noise" in IEEE Transactions on Haptics, January 2024 (misc)

DOI Project Page [BibTex]

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How Should Robots Exercise with People? Robot-Mediated Exergames Win with Music, Social Analogues, and Gameplay Clarity

Fitter, N. T., Mohan, M., Preston, R. C., Johnson, M. J., Kuchenbecker, K. J.

Frontiers in Robotics and AI, 10(1155837):1-18, January 2024 (article)

Abstract
The modern worldwide trend toward sedentary behavior comes with significant health risks. An accompanying wave of health technologies has tried to encourage physical activity, but these approaches often yield limited use and retention. Due to their unique ability to serve as both a health-promoting technology and a social peer, we propose robots as a game-changing solution for encouraging physical activity. This article analyzes the eight exergames we previously created for the Rethink Baxter Research Robot in terms of four key components that are grounded in the video-game literature: repetition, pattern matching, music, and social design. We use these four game facets to assess gameplay data from 40 adult users who each experienced the games in balanced random order. In agreement with prior research, our results show that relevant musical cultural references, recognizable social analogues, and gameplay clarity are good strategies for taking an otherwise highly repetitive physical activity and making it engaging and popular among users. Others who study socially assistive robots and rehabilitation robotics can benefit from this work by considering the presented design attributes to generate future hypotheses and by using our eight open-source games to pursue follow-up work on social-physical exercise with robots.

DOI Project Page [BibTex]

Fitter, N. T., Mohan, M., Preston, R. C., Johnson, M. J., Kuchenbecker, K. J. How Should Robots Exercise with People? Robot-Mediated Exergames Win with Music, Social Analogues, and Gameplay Clarity Frontiers in Robotics and AI, 10(1155837):1-18, January 2024 (article)

DOI Project Page [BibTex]

Whiskers That Don’t Whisk: Unique Structure From the Absence of Actuation in Elephant Whiskers
Whiskers That Don’t Whisk: Unique Structure From the Absence of Actuation in Elephant Whiskers

Schulz, A., Kaufmann, L., Brecht, M., Richter, G., Kuchenbecker, K. J.

Abstract presented at the Society for Integrative and Comparative Biology Annual Meeting (SICB), Seattle, USA, January 2024 (misc)

Abstract
Whiskers are so named because these hairs often actuate circularly, whisking, via collagen wrapping at the root of the hair follicle to increase their sensing volumes. Elephant trunks are a unique case study for whiskers, as the dorsal and lateral sections of the elephant proboscis have scattered sensory hairs that lack individual actuation. We hypothesize that the actuation limitations of these non-whisking whiskers led to anisotropic morphology and non-homogeneous composition to meet the animal's sensory needs. To test these hypotheses, we examined trunk whiskers from a 35-year-old female African savannah elephant (Loxodonta africana). Whisker morphology was evaluated through micro-CT and polarized light microscopy. The whiskers from the distal tip of the trunk were found to be axially asymmetric, with an ovular cross-section at the root, shifting to a near-square cross-section at the point. Nanoindentation and additional microscopy revealed that elephant whiskers have a composition unlike any other mammalian hair ever studied: we recorded an elastic modulus of 3 GPa at the root and 0.05 GPa at the point of a single 4-cm-long whisker. This work challenges the assumption that hairs have circular cross-sections and isotropic mechanical properties. With such striking differences compared to other mammals, including the mouse (Mus musculus), rat (Rattus norvegicus), and cat (Felis catus), we conclude that whisker morphology and composition play distinct and complementary roles in elephant trunk mechanosensing.

[BibTex]

Schulz, A., Kaufmann, L., Brecht, M., Richter, G., Kuchenbecker, K. J. Whiskers That Don’t Whisk: Unique Structure From the Absence of Actuation in Elephant Whiskers Abstract presented at the Society for Integrative and Comparative Biology Annual Meeting (SICB), Seattle, USA, January 2024 (misc)

[BibTex]

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Robust Surface Recognition with the Maximum Mean Discrepancy: Degrading Haptic-Auditory Signals through Bandwidth and Noise

(Best ToH Short Paper Award at the IEEE Haptics Symposium Conference 2024)

Khojasteh, B., Shao, Y., Kuchenbecker, K. J.

IEEE Transactions on Haptics, 17(1):58-65, January 2024, Presented at the IEEE Haptics Symposium (article)

Abstract
Sliding a tool across a surface generates rich sensations that can be analyzed to recognize what is being touched. However, the optimal configuration for capturing these signals is yet unclear. To bridge this gap, we consider haptic-auditory data as a human explores surfaces with different steel tools, including accelerations of the tool and finger, force and torque applied to the surface, and contact sounds. Our classification pipeline uses the maximum mean discrepancy (MMD) to quantify differences in data distributions in a high-dimensional space for inference. With recordings from three hemispherical tool diameters and ten diverse surfaces, we conducted two degradation studies by decreasing sensing bandwidth and increasing added noise. We evaluate the haptic-auditory recognition performance achieved with the MMD to compare newly gathered data to each surface in our known library. The results indicate that acceleration signals alone have great potential for high-accuracy surface recognition and are robust against noise contamination. The optimal accelerometer bandwidth exceeds 1000 Hz, suggesting that useful vibrotactile information extends beyond human perception range. Finally, smaller tool tips generate contact vibrations with better noise robustness. The provided sensing guidelines may enable superhuman performance in portable surface recognition, which could benefit quality control, material documentation, and robotics.

DOI Project Page [BibTex]

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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 (misc)

Code Project Page [BibTex]

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

Code Project Page [BibTex]

2023

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Towards Semi-Automated Pleural Cavity Access for Pneumothorax in Austere Environments

L’Orsa, R., Lama, S., Westwick, D., Sutherland, G., Kuchenbecker, K. J.

Acta Astronautica, 212, pages: 48-53, November 2023 (article)

Abstract
Astronauts are at risk for pneumothorax, a condition where injury or disease introduces air between the chest wall and the lungs (i.e., the pleural cavity). In a worst-case scenario, it can rapidly lead to a fatality if left unmanaged and will require prompt treatment in situ if developed during spaceflight. Chest tube insertion is the definitive treatment for pneumothorax, but it requires a high level of skill and frequent practice for safe use. Physician astronauts may struggle to maintain this skill on medium- and long-duration exploration-class missions, and it is inappropriate for pure just-in-time learning or skill refreshment paradigms. This paper proposes semi-automating tool insertion to reduce the risk of complications in austere environments and describes preliminary experiments providing initial validation of an intelligent prototype system. Specifically, we showcase and analyse motion and force recordings from a sensorized percutaneous access needle inserted repeatedly into an ex vivo tissue phantom, along with relevant physiological data simultaneously recorded from the operator. When coupled with minimal just-in-time training and/or augmented reality guidance, the proposed system may enable non-expert operators to safely perform emergency chest tube insertion without the use of ground resources.

DOI Project Page [BibTex]

2023

L’Orsa, R., Lama, S., Westwick, D., Sutherland, G., Kuchenbecker, K. J. Towards Semi-Automated Pleural Cavity Access for Pneumothorax in Austere Environments Acta Astronautica, 212, pages: 48-53, November 2023 (article)

DOI Project Page [BibTex]

Seeking Causal, Invariant, Structures with Kernel Mean Embeddings in Haptic-Auditory Data from Tool-Surface Interaction
Seeking Causal, Invariant, Structures with Kernel Mean Embeddings in Haptic-Auditory Data from Tool-Surface Interaction

Khojasteh, B., Shao, Y., Kuchenbecker, K. J.

Workshop paper (4 pages) presented at the IROS Workshop on Causality for Robotics: Answering the Question of Why, Detroit, USA, October 2023 (misc)

Abstract
Causal inference could give future learning robots strong generalization and scalability capabilities, which are crucial for safety, fault diagnosis and error prevention. One application area of interest consists of the haptic recognition of surfaces. We seek to understand cause and effect during physical surface interaction by examining surface and tool identity, their interplay, and other contact-irrelevant factors. To work toward elucidating the mechanism of surface encoding, we attempt to recognize surfaces from haptic-auditory data captured by previously unseen hemispherical steel tools that differ from the recording tool in diameter and mass. In this context, we leverage ideas from kernel methods to quantify surface similarity through descriptive differences in signal distributions. We find that the effect of the tool is significantly present in higher-order statistical moments of contact data: aligning the means of the distributions being compared somewhat improves recognition but does not fully separate tool identity from surface identity. Our findings shed light on salient aspects of haptic-auditory data from tool-surface interaction and highlight the challenges involved in generalizing artificial surface discrimination capabilities.

Manuscript Project Page [BibTex]

Khojasteh, B., Shao, Y., Kuchenbecker, K. J. Seeking Causal, Invariant, Structures with Kernel Mean Embeddings in Haptic-Auditory Data from Tool-Surface Interaction Workshop paper (4 pages) presented at the IROS Workshop on Causality for Robotics: Answering the Question of Why, Detroit, USA, October 2023 (misc)

Manuscript Project Page [BibTex]

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NearContact: Accurate Human Detection using Tomographic Proximity and Contact Sensing with Cross-Modal Attention

Garrofé, G., Schoeffmann, C., Zangl, H., Kuchenbecker, K. J., Lee, H.

Extended abstract (4 pages) presented at the International Workshop on Human-Friendly Robotics (HFR), Munich, Germany, September 2023 (misc)

Project Page [BibTex]

Garrofé, G., Schoeffmann, C., Zangl, H., Kuchenbecker, K. J., Lee, H. NearContact: Accurate Human Detection using Tomographic Proximity and Contact Sensing with Cross-Modal Attention Extended abstract (4 pages) presented at the International Workshop on Human-Friendly Robotics (HFR), Munich, Germany, September 2023 (misc)

Project Page [BibTex]

The Role of Kinematics Estimation Accuracy in Learning with Wearable Haptics
The Role of Kinematics Estimation Accuracy in Learning with Wearable Haptics

Rokhmanova, N., Pearl, O., Kuchenbecker, K. J., Halilaj, E.

Abstract (1 page) presented at the American Society of Biomechanics Annual Meeting (ASB), Knoxville, USA, August 2023 (misc)

Project Page [BibTex]

Rokhmanova, N., Pearl, O., Kuchenbecker, K. J., Halilaj, E. The Role of Kinematics Estimation Accuracy in Learning with Wearable Haptics Abstract (1 page) presented at the American Society of Biomechanics Annual Meeting (ASB), Knoxville, USA, August 2023 (misc)

Project Page [BibTex]

Minsight: A Fingertip-Sized Vision-Based Tactile Sensor for Robotic Manipulation
Minsight: A Fingertip-Sized Vision-Based Tactile Sensor for Robotic Manipulation

Andrussow, I., Sun, H., Kuchenbecker, K. J., Martius, G.

Advanced Intelligent Systems, 5(8):2300042, August 2023, Inside back cover (article)

Abstract
Intelligent interaction with the physical world requires perceptual abilities beyond vision and hearing; vibrant tactile sensing is essential for autonomous robots to dexterously manipulate unfamiliar objects or safely contact humans. Therefore, robotic manipulators need high-resolution touch sensors that are compact, robust, inexpensive, and efficient. The soft vision-based haptic sensor presented herein is a miniaturized and optimized version of the previously published sensor Insight. Minsight has the size and shape of a human fingertip and uses machine learning methods to output high-resolution maps of 3D contact force vectors at 60 Hz. Experiments confirm its excellent sensing performance, with a mean absolute force error of 0.07 N and contact location error of 0.6 mm across its surface area. Minsight's utility is shown in two robotic tasks on a 3-DoF manipulator. First, closed-loop force control enables the robot to track the movements of a human finger based only on tactile data. Second, the informative value of the sensor output is shown by detecting whether a hard lump is embedded within a soft elastomer with an accuracy of 98%. These findings indicate that Minsight can give robots the detailed fingertip touch sensing needed for dexterous manipulation and physical human–robot interaction.

DOI Project Page [BibTex]

Learning to Estimate Palpation Forces in Robotic Surgery From Visual-Inertial Data
Learning to Estimate Palpation Forces in Robotic Surgery From Visual-Inertial Data

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

IEEE Transactions on Medical Robotics and Bionics, 5(3):496-506, August 2023 (article)

Abstract
Surgeons cannot directly touch the patient's tissue in robot-assisted minimally invasive procedures. Instead, they must palpate using instruments inserted into the body through trocars. This way of operating largely prevents surgeons from using haptic cues to localize visually undetectable structures such as tumors and blood vessels, motivating research on direct and indirect force sensing. We propose an indirect force-sensing method that combines monocular images of the operating field with measurements from IMUs attached externally to the instrument shafts. Our method is thus suitable for various robotic surgery systems as well as laparoscopic surgery. We collected a new dataset using a da Vinci Si robot, a force sensor, and four different phantom tissue samples. The dataset includes 230 one-minute-long recordings of repeated bimanual palpation tasks performed by four lay operators. We evaluated several network architectures and investigated the role of the network inputs. Using the DenseNet vision model and including inertial data best-predicted palpation forces (lowest average root-mean-square error and highest average coefficient of determination). Ablation studies revealed that video frames carry significantly more information than inertial signals. Finally, we demonstrated the model's ability to generalize to unseen tissue and predict shear contact forces.

DOI [BibTex]

Lee, Y., Husin, H. M., Forte, M., Lee, S., Kuchenbecker, K. J. Learning to Estimate Palpation Forces in Robotic Surgery From Visual-Inertial Data IEEE Transactions on Medical Robotics and Bionics, 5(3):496-506, August 2023 (article)

DOI [BibTex]

Strap Tightness and Tissue Composition Both Affect the Vibration Created by a Wearable Device
Strap Tightness and Tissue Composition Both Affect the Vibration Created by a Wearable Device

Rokhmanova, N., Faulkner, R., Martus, J., Fiene, J., Kuchenbecker, K. J.

Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Abstract
Wearable haptic devices can provide salient real-time feedback (typically vibration) for rehabilitation, sports training, and skill acquisition. Although the body provides many sites for such cues, the influence of the mounting location on vibrotactile mechanics is commonly ignored. This study builds on previous research by quantifying how changes in strap tightness and local tissue composition affect the physical acceleration generated by a typical vibrotactile device.

Project Page [BibTex]

Rokhmanova, N., Faulkner, R., Martus, J., Fiene, J., Kuchenbecker, K. J. Strap Tightness and Tissue Composition Both Affect the Vibration Created by a Wearable Device Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Toward a Device for Reliable Evaluation of Vibrotactile Perception
Toward a Device for Reliable Evaluation of Vibrotactile Perception

Ballardini, G., Kuchenbecker, K. J.

Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

[BibTex]

Ballardini, G., Kuchenbecker, K. J. Toward a Device for Reliable Evaluation of Vibrotactile Perception Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

[BibTex]

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Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test: Code

Khojasteh, B., Solowjow, F., Trimpe, S., Kuchenbecker, K. J.

Code published as a companion to the journal article "Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test" in IEEE Transactions on Automation Science and Engineering, July 2023 (misc)

DOI Project Page [BibTex]

Khojasteh, B., Solowjow, F., Trimpe, S., Kuchenbecker, K. J. Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test: Code Code published as a companion to the journal article "Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test" in IEEE Transactions on Automation Science and Engineering, July 2023 (misc)

DOI Project Page [BibTex]

Improving Haptic Rendering Quality by Measuring and Compensating for Undesired Forces
Improving Haptic Rendering Quality by Measuring and Compensating for Undesired Forces

Fazlollahi, F., Taghizadeh, Z., Kuchenbecker, K. J.

Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Fazlollahi, F., Taghizadeh, Z., Kuchenbecker, K. J. Improving Haptic Rendering Quality by Measuring and Compensating for Undesired Forces Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Capturing Rich Auditory-Haptic Contact Data for Surface Recognition
Capturing Rich Auditory-Haptic Contact Data for Surface Recognition

Khojasteh, B., Shao, Y., Kuchenbecker, K. J.

Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Abstract
The sophistication of biological sensing and transduction processes during finger-surface and tool-surface interaction is remarkable, enabling humans to perform ubiquitous tasks such as discriminating and manipulating surfaces. Capturing and processing these rich contact-elicited signals during surface exploration with similar success is an important challenge for artificial systems. Prior research introduced sophisticated mobile surface-sensing systems, but it remains less clear what quality, resolution and acuity of sensor data are necessary to perform human tasks with the same efficiency and accuracy. In order to address this gap in our understanding about artificial surface perception, we have designed a novel auditory-haptic test bed. This study aims to inspire new designs for artificial sensing tools in human-machine and robotic applications.

Project Page [BibTex]

Khojasteh, B., Shao, Y., Kuchenbecker, K. J. Capturing Rich Auditory-Haptic Contact Data for Surface Recognition Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Airo{T}ouch: Naturalistic Vibrotactile Feedback for Telerobotic Construction
AiroTouch: Naturalistic Vibrotactile Feedback for Telerobotic Construction

Gong, Y., Javot, B., Lauer, A. P. R., Sawodny, O., Kuchenbecker, K. J.

Hands-on demonstration presented at the IEEE World Haptics Conference, Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Gong, Y., Javot, B., Lauer, A. P. R., Sawodny, O., Kuchenbecker, K. J. AiroTouch: Naturalistic Vibrotactile Feedback for Telerobotic Construction Hands-on demonstration presented at the IEEE World Haptics Conference, Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

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CAPT Motor: A Strong Direct-Drive Haptic Interface

Javot, B., Nguyen, V. H., Ballardini, G., Kuchenbecker, K. J.

Hands-on demonstration presented at the IEEE World Haptics Conference, Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Javot, B., Nguyen, V. H., Ballardini, G., Kuchenbecker, K. J. CAPT Motor: A Strong Direct-Drive Haptic Interface Hands-on demonstration presented at the IEEE World Haptics Conference, Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Can Recording Expert Demonstrations with Tool Vibrations Facilitate Teaching of Manual Skills?
Can Recording Expert Demonstrations with Tool Vibrations Facilitate Teaching of Manual Skills?

Gourishetti, R., Javot, B., Kuchenbecker, K. J.

Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Gourishetti, R., Javot, B., Kuchenbecker, K. J. Can Recording Expert Demonstrations with Tool Vibrations Facilitate Teaching of Manual Skills? Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Creating a Haptic Empathetic Robot Animal for Children with Autism
Creating a Haptic Empathetic Robot Animal for Children with Autism

Burns, R. B.

Workshop paper (4 pages) presented at the RSS Pioneers Workshop, Daegu, South Korea, July 2023 (misc)

link (url) Project Page [BibTex]

Burns, R. B. Creating a Haptic Empathetic Robot Animal for Children with Autism Workshop paper (4 pages) presented at the RSS Pioneers Workshop, Daegu, South Korea, July 2023 (misc)

link (url) Project Page [BibTex]

The Influence of Amplitude and Sharpness on the Perceived Intensity of Isoenergetic Ultrasonic Signals
The Influence of Amplitude and Sharpness on the Perceived Intensity of Isoenergetic Ultrasonic Signals

Gueorguiev, D., Rohou–Claquin, B., Kuchenbecker, K. J.

Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Gueorguiev, D., Rohou–Claquin, B., Kuchenbecker, K. J. The Influence of Amplitude and Sharpness on the Perceived Intensity of Isoenergetic Ultrasonic Signals Work-in-progress paper (1 page) presented at the IEEE World Haptics Conference (WHC), Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Vibrotactile Playback for Teaching Manual Skills from Expert Recordings
Vibrotactile Playback for Teaching Manual Skills from Expert Recordings

Gourishetti, R., Hughes, A. G., Javot, B., Kuchenbecker, K. J.

Hands-on demonstration presented at the IEEE World Haptics Conference, Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Gourishetti, R., Hughes, A. G., Javot, B., Kuchenbecker, K. J. Vibrotactile Playback for Teaching Manual Skills from Expert Recordings Hands-on demonstration presented at the IEEE World Haptics Conference, Delft, The Netherlands, July 2023 (misc)

Project Page [BibTex]

Naturalistic Vibrotactile Feedback Could Facilitate Telerobotic Assembly on Construction Sites
Naturalistic Vibrotactile Feedback Could Facilitate Telerobotic Assembly on Construction Sites

Gong, Y., Javot, B., Lauer, A. P. R., Sawodny, O., Kuchenbecker, K. J.

Poster presented at the ICRA Workshop on Future of Construction: Robot Perception, Mapping, Navigation, Control in Unstructured and Cluttered Environments, London, UK, June 2023 (misc)

Project Page [BibTex]

Gong, Y., Javot, B., Lauer, A. P. R., Sawodny, O., Kuchenbecker, K. J. Naturalistic Vibrotactile Feedback Could Facilitate Telerobotic Assembly on Construction Sites Poster presented at the ICRA Workshop on Future of Construction: Robot Perception, Mapping, Navigation, Control in Unstructured and Cluttered Environments, London, UK, June 2023 (misc)

Project Page [BibTex]

In the Arms of a Robot: Designing Autonomous Hugging Robots with Intra-Hug Gestures
In the Arms of a Robot: Designing Autonomous Hugging Robots with Intra-Hug Gestures

Block, A. E., Seifi, H., Hilliges, O., Gassert, R., Kuchenbecker, K. J.

ACM Transactions on Human-Robot Interaction, 12(2):1-49, June 2023, Special Issue on Designing the Robot Body: Critical Perspectives on Affective Embodied Interaction (article)

Abstract
Hugs are complex affective interactions that often include gestures like squeezes. We present six new guidelines for designing interactive hugging robots, which we validate through two studies with our custom robot. To achieve autonomy, we investigated robot responses to four human intra-hug gestures: holding, rubbing, patting, and squeezing. Thirty-two users each exchanged and rated sixteen hugs with an experimenter-controlled HuggieBot 2.0. The robot's inflated torso's microphone and pressure sensor collected data of the subjects' demonstrations that were used to develop a perceptual algorithm that classifies user actions with 88% accuracy. Users enjoyed robot squeezes, regardless of their performed action, they valued variety in the robot response, and they appreciated robot-initiated intra-hug gestures. From average user ratings, we created a probabilistic behavior algorithm that chooses robot responses in real time. We implemented improvements to the robot platform to create HuggieBot 3.0 and then validated its gesture perception system and behavior algorithm with sixteen users. The robot's responses and proactive gestures were greatly enjoyed. Users found the robot more natural, enjoyable, and intelligent in the last phase of the experiment than in the first. After the study, they felt more understood by the robot and thought robots were nicer to hug.

DOI Project Page [BibTex]

Block, A. E., Seifi, H., Hilliges, O., Gassert, R., Kuchenbecker, K. J. In the Arms of a Robot: Designing Autonomous Hugging Robots with Intra-Hug Gestures ACM Transactions on Human-Robot Interaction, 12(2):1-49, June 2023, Special Issue on Designing the Robot Body: Critical Perspectives on Affective Embodied Interaction (article)

DOI Project Page [BibTex]

Generating Clear Vibrotactile Cues with a Magnet Embedded in a Soft Finger Sheath
Generating Clear Vibrotactile Cues with a Magnet Embedded in a Soft Finger Sheath

Gertler, I., Serhat, G., Kuchenbecker, K. J.

Soft Robotics, 10(3):624-635, June 2023 (article)

Abstract
Haptic displays act on the user's body to stimulate the sense of touch and enrich applications from gaming and computer-aided design to rehabilitation and remote surgery. However, when crafted from typical rigid robotic components, they tend to be heavy, bulky, and expensive, while sleeker designs often struggle to create clear haptic cues. This article introduces a lightweight wearable silicone finger sheath that can deliver salient and rich vibrotactile cues using electromagnetic actuation. We fabricate the sheath on a ferromagnetic mandrel with a process based on dip molding, a robust fabrication method that is rarely used in soft robotics but is suitable for commercial production. A miniature rare-earth magnet embedded within the silicone layers at the center of the finger pad is driven to vibrate by the application of alternating current to a nearby air-coil. Experiments are conducted to determine the amplitude of the magnetic force and the frequency response function for the displacement amplitude of the magnet perpendicular to the skin. In addition, high-fidelity finite element analyses of the finger wearing the device are performed to investigate the trends observed in the measurements. The experimental and simulated results show consistent dynamic behavior from 10 to 1000 Hz, with the displacement decreasing after about 300 Hz. These results match the detection threshold profile obtained in a psychophysical study performed by 17 users, where more current was needed only at the highest frequency. A cue identification experiment and a demonstration in virtual reality validate the feasibility of this approach to fingertip haptics.

DOI Project Page [BibTex]

Airo{T}ouch: Naturalistic Vibrotactile Feedback for Telerobotic Construction-Related Tasks
AiroTouch: Naturalistic Vibrotactile Feedback for Telerobotic Construction-Related Tasks

Gong, Y., Tashiro, N., Javot, B., Lauer, A. P. R., Sawodny, O., Kuchenbecker, K. J.

Extended abstract (1 page) presented at the ICRA Workshop on Communicating Robot Learning across Human-Robot Interaction, London, UK, May 2023 (misc)

Project Page [BibTex]

Gong, Y., Tashiro, N., Javot, B., Lauer, A. P. R., Sawodny, O., Kuchenbecker, K. J. AiroTouch: Naturalistic Vibrotactile Feedback for Telerobotic Construction-Related Tasks Extended abstract (1 page) presented at the ICRA Workshop on Communicating Robot Learning across Human-Robot Interaction, London, UK, May 2023 (misc)

Project Page [BibTex]

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3D Reconstruction for Minimally Invasive Surgery: Lidar Versus Learning-Based Stereo Matching

Caccianiga, G., Nubert, J., Hutter, M., Kuchenbecker., K. J.

Workshop paper (2 pages) presented at the ICRA Workshop on Robot-Assisted Medical Imaging, London, UK, May 2023 (misc)

Abstract
This work investigates real-time 3D surface reconstruction for minimally invasive surgery. Specifically, we analyze depth sensing through laser-based time-of-flight sensing (lidar) and stereo endoscopy on ex-vivo porcine tissue samples. When compared to modern learning-based stereo matching from endoscopic images, lidar achieves lower processing delay, higher frame rate, and superior robustness against sensor distance and poor illumination. Furthermore, we report on the negative effect of near-infrared light penetration on the accuracy of time-of-flight measurements across different tissue types.

Project Page [BibTex]

Caccianiga, G., Nubert, J., Hutter, M., Kuchenbecker., K. J. 3D Reconstruction for Minimally Invasive Surgery: Lidar Versus Learning-Based Stereo Matching Workshop paper (2 pages) presented at the ICRA Workshop on Robot-Assisted Medical Imaging, London, UK, May 2023 (misc)

Project Page [BibTex]

Surface Perception through Haptic-Auditory Contact Data
Surface Perception through Haptic-Auditory Contact Data

Khojasteh, B., Shao, Y., Kuchenbecker, K. J.

Workshop paper (4 pages) presented at the ICRA Workshop on Embracing Contacts, London, UK, May 2023 (misc)

Abstract
Sliding a finger or tool along a surface generates rich haptic and auditory contact signals that encode properties crucial for manipulation, such as friction and hardness. To engage in contact-rich manipulation, future robots would benefit from having surface-characterization capabilities similar to humans, but the optimal sensing configuration is not yet known. Thus, we developed a test bed for capturing high-quality measurements as a human touches surfaces with different tools: it includes optical motion capture, a force/torque sensor under the surface sample, high-bandwidth accelerometers on the tool and the fingertip, and a high-fidelity microphone. After recording data from three tool diameters and nine surfaces, we describe a surface-classification pipeline that uses the maximum mean discrepancy (MMD) to compare newly gathered data to each surface in our known library. The results achieved under several pipeline variations are compared, and future investigations are outlined.

link (url) Project Page [BibTex]

Khojasteh, B., Shao, Y., Kuchenbecker, K. J. Surface Perception through Haptic-Auditory Contact Data Workshop paper (4 pages) presented at the ICRA Workshop on Embracing Contacts, London, UK, May 2023 (misc)

link (url) Project Page [BibTex]