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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.

hi

Project Page [BibTex]

2024


Project Page [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.

al hi ei

Project Page [BibTex]

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

hi

DOI [BibTex]

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)

hi

Project Page [BibTex]

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)

hi

[BibTex]

[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.

hi

DOI [BibTex]

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.

hi zwe-rob

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Three-Dimensional 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.

hi

[BibTex]

[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.

hi

link (url) Project Page [BibTex]

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)

hi

Project Page [BibTex]

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)

hi rm

[BibTex]

[BibTex]


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Cutaneous Electrohydraulic Wearable Devices for Expressive and Salient Haptic Feedback

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

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

hi rm

[BibTex]


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Language Models Can Reduce Asymmetry in Information Markets

Rahaman, N., Weiss, M., Wüthrich, M., Bengio, Y., Li, E., Pal, C., Schölkopf, B.

arXiv:2403.14443, March 2024, Published as: Redesigning Information Markets in the Era of Language Models, Conference on Language Modeling (COLM) (techreport)

Abstract
This work addresses the buyer's inspection paradox for information markets. The paradox is that buyers need to access information to determine its value, while sellers need to limit access to prevent theft. To study this, we introduce an open-source simulated digital marketplace where intelligent agents, powered by language models, buy and sell information on behalf of external participants. The central mechanism enabling this marketplace is the agents' dual capabilities: they not only have the capacity to assess the quality of privileged information but also come equipped with the ability to forget. This ability to induce amnesia allows vendors to grant temporary access to proprietary information, significantly reducing the risk of unauthorized retention while enabling agents to accurately gauge the information's relevance to specific queries or tasks. To perform well, agents must make rational decisions, strategically explore the marketplace through generated sub-queries, and synthesize answers from purchased information. Concretely, our experiments (a) uncover biases in language models leading to irrational behavior and evaluate techniques to mitigate these biases, (b) investigate how price affects demand in the context of informational goods, and (c) show that inspection and higher budgets both lead to higher quality outcomes.

ei

link (url) [BibTex]

link (url) [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.

hi

[BibTex]

[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)

hi

DOI Project Page [BibTex]

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.

zwe-csfm hi

[BibTex]

[BibTex]


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Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning reveals the Giant Exoplanet AF Lep b in High-Contrast Imaging Data from 2011

Bonse, M. J., Gebhard, T. D., Dannert, F. A., Absil, O., Cantalloube, F., Christiaens, V., Cugno, G., Garvin, E. O., Hayoz, J., Kasper, M., Matthews, E., Schölkopf, B., Quanz, S. P.

2024 (misc) Submitted

ei

arXiv [BibTex]

arXiv [BibTex]


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Learning a Terrain- and Robot-Aware Dynamics Model for Autonomous Mobile Robot Navigation

Achterhold, J., Guttikonda, S., Kreber, J. U., Li, H., Stueckler, J.

CoRR abs/2409.11452, 2024, Preprint submitted to Robotics and Autonomous Systems Journal. https://arxiv.org/abs/2409.11452 (techreport) Submitted

Abstract
Mobile robots should be capable of planning cost-efficient paths for autonomous navigation. Typically, the terrain and robot properties are subject to variations. For instance, properties of the terrain such as friction may vary across different locations. Also, properties of the robot may change such as payloads or wear and tear, e.g., causing changing actuator gains or joint friction. Autonomous navigation approaches should thus be able to adapt to such variations. In this article, we propose a novel approach for learning a probabilistic, terrain- and robot-aware forward dynamics model (TRADYN) which can adapt to such variations and demonstrate its use for navigation. Our learning approach extends recent advances in meta-learning forward dynamics models based on Neural Processes for mobile robot navigation. We evaluate our method in simulation for 2D navigation of a robot with uni-cycle dynamics with varying properties on terrain with spatially varying friction coefficients. In our experiments, we demonstrate that TRADYN has lower prediction error over long time horizons than model ablations which do not adapt to robot or terrain variations. We also evaluate our model for navigation planning in a model-predictive control framework and under various sources of noise. We demonstrate that our approach yields improved performance in planning control-efficient paths by taking robot and terrain properties into account.

ev

preprint [BibTex]

preprint [BibTex]


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Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Models
2024 (misc)

Abstract
Humans excel at robust bipedal walking in complex natural environments. In each step, they adequately tune the interaction of biomechanical muscle dynamics and neuronal signals to be robust against uncertainties in ground conditions. However, it is still not fully understood how the nervous system resolves the musculoskeletal redundancy to solve the multi-objective control problem considering stability, robustness, and energy efficiency. In computer simulations, energy minimization has been shown to be a successful optimization target, reproducing natural walking with trajectory optimization or reflex-based control methods. However, these methods focus on particular motions at a time and the resulting controllers are limited when compensating for perturbations. In robotics, reinforcement learning~(RL) methods recently achieved highly stable (and efficient) locomotion on quadruped systems, but the generation of human-like walking with bipedal biomechanical models has required extensive use of expert data sets. This strong reliance on demonstrations often results in brittle policies and limits the application to new behaviors, especially considering the potential variety of movements for high-dimensional musculoskeletal models in 3D. Achieving natural locomotion with RL without sacrificing its incredible robustness might pave the way for a novel approach to studying human walking in complex natural environments. Videos: this https://sites.google.com/view/naturalwalkingrl

al

link (url) [BibTex]


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A Pontryagin Perspective on Reinforcement Learning

Eberhard, O., Vernade, C., Muehlebach, M.

Max Planck Institute for Intelligent Systems, 2024 (techreport)

lds

link (url) [BibTex]

link (url) [BibTex]


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Distributed Event-Based Learning via ADMM

Er, D., Trimpe, S., Muehlebach, M.

Max Planck Institute for Intelligent Systems, 2024 (techreport)

lds

link (url) [BibTex]

link (url) [BibTex]


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Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators

Baumeister, F., Mack, L., Stueckler, J.

CoRR abs/2409.13228, CoRR, 2024, Submitted to IEEE International Conference on Robotics and Automation (ICRA) 2025 (techreport) Submitted

Abstract
Few-shot adaptation is an important capability for intelligent robots that perform tasks in open-world settings such as everyday environments or flexible production. In this paper, we propose a novel approach for non-prehensile manipulation which iteratively adapts a physics-based dynamics model for model-predictive control. We adapt the parameters of the model incrementally with a few examples of robot-object interactions. This is achieved by sampling-based optimization of the parameters using a parallelizable rigid-body physics simulation as dynamic world model. In turn, the optimized dynamics model can be used for model-predictive control using efficient sampling-based optimization. We evaluate our few-shot adaptation approach in several object pushing experiments in simulation and with a real robot.

ev

preprint supplemental video link (url) [BibTex]

preprint supplemental video link (url) [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)

hi

Code Project Page [BibTex]

Code Project Page [BibTex]

2023


Fairness in Machine Learning: Limitations and Opportunities
Fairness in Machine Learning: Limitations and Opportunities

Barocas, S., Hardt, M., Narayanan, A.

MIT Press, December 2023 (book)

Abstract
An introduction to the intellectual foundations and practical utility of the recent work on fairness and machine learning. Fairness and Machine Learning introduces advanced undergraduate and graduate students to the intellectual foundations of this recently emergent field, drawing on a diverse range of disciplinary perspectives to identify the opportunities and hazards of automated decision-making. It surveys the risks in many applications of machine learning and provides a review of an emerging set of proposed solutions, showing how even well-intentioned applications may give rise to objectionable results. It covers the statistical and causal measures used to evaluate the fairness of machine learning models as well as the procedural and substantive aspects of decision-making that are core to debates about fairness, including a review of legal and philosophical perspectives on discrimination. This incisive textbook prepares students of machine learning to do quantitative work on fairness while reflecting critically on its foundations and its practical utility.• Introduces the technical and normative foundations of fairness in automated decision-making• Covers the formal and computational methods for characterizing and addressing problems• Provides a critical assessment of their intellectual foundations and practical utility• Features rich pedagogy and extensive instructor resources

sf

link (url) [BibTex]

2023


link (url) [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.

hi

Manuscript Project Page [BibTex]

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)

hi

Project Page [BibTex]

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)

hi

Project Page [BibTex]

Project Page [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.

hi

Project Page [BibTex]

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)

hi

[BibTex]

[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)

hi

DOI Project Page [BibTex]

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)

hi

Project Page [BibTex]

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.

hi

Project Page [BibTex]

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)

hi

Project Page [BibTex]

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)

hi

Project Page [BibTex]

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)

hi

Project Page [BibTex]

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)

hi

link (url) Project Page [BibTex]

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)

hi

Project Page [BibTex]

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)

hi

Project Page [BibTex]

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)

hi

Project Page [BibTex]

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)

hi

Project Page [BibTex]

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.

hi

Project Page [BibTex]

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.

hi

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


{OCRA}: An Optimization-Based Customizable Retargeting Algorithm for Teleoperation
OCRA: An Optimization-Based Customizable Retargeting Algorithm for Teleoperation

Mohan, M., Kuchenbecker, K. J.

Workshop paper (3 pages) presented at the ICRA Workshop Toward Robot Avatars, London, UK, May 2023 (misc)

Abstract
This paper presents a real-time optimization-based algorithm for mapping motion between two kinematically dissimilar serial linkages, such as a human arm and a robot arm. OCRA can be customized based on the target task to weight end-effector orientation versus the configuration of the central line of the arm, which we call the skeleton. A video-watching study (N=70) demonstrated that when this algorithm considers both the hand orientation and the arm skeleton, it creates robot arm motions that users perceive to be highly similar to those of the human operator, indicating OCRA would be suitable for telerobotics and telepresence through avatars.

hi

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Wearable Biofeedback for Knee Joint Health

Rokhmanova, N.

Extended abstract (5 pages) presented at the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI) Doctoral Consortium, Hamburg, Germany, April 2023 (misc)

Abstract
The human body has the tremendous capacity to learn a new way of walking that reduces its risk of musculoskeletal disease progression. Wearable haptic biofeedback has been used to guide gait retraining in patients with knee osteoarthritis, enabling reductions in pain and improvement in function. However, this promising therapy is not yet a part of standard clinical practice. Here, I propose a two-pronged approach to improving the design and deployment of biofeedback for gait retraining. The first section concerns prescription, with the aim of providing clinicians with an interpretable model of gait retraining outcome in order to best guide their treatment decisions. The second section concerns learning, by examining how internal physiological state and external environmental factors influence the process of learning a therapeutic gait. This work aims to address the challenges keeping a highly promising intervention from being widely used to maintain pain-free mobility throughout the lifespan.

hi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


A Lasting Impact: Using Second-Order Dynamics to Customize the Continuous Emotional Expression of a Social Robot
A Lasting Impact: Using Second-Order Dynamics to Customize the Continuous Emotional Expression of a Social Robot

Burns, R. B., Kuchenbecker, K. J.

Workshop paper (5 pages) presented at the HRI Workshop on Lifelong Learning and Personalization in Long-Term Human-Robot Interaction (LEAP-HRI), Stockholm, Sweden, March 2023 (misc)

Abstract
Robots are increasingly being developed as assistants for household, education, therapy, and care settings. Such robots need social skills to interact warmly and effectively with their users, as well as adaptive behavior to maintain user interest. While complex emotion models exist for chat bots and virtual agents, autonomous physical robots often lack a dynamic internal affective state, instead displaying brief, fixed emotion routines to promote or discourage specific user actions. We address this need by creating a mathematical emotion model that can easily be implemented in a social robot to enable it to react intelligently to external stimuli. The robot's affective state is modeled as a second-order dynamic system analogous to a mass connected to ground by a parallel spring and damper. The present position of this imaginary mass shows the robot's valence, which we visualize as the height of its displayed smile (positive) or frown (negative). Associating positive and negative stimuli with appropriately oriented and sized force pulses applied to the mass enables the robot to respond to social touch and other inputs with a valence that evolves over a longer timescale, capturing essential features of approach-avoidance theory. By adjusting the parameters of this emotion model, one can modify three main aspects of the robot's personality, which we term disposition, stoicism, and calmness.

hi

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80
Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80

Berenz, V., Widmaier, F., Guist, S., Schölkopf, B., Büchler, D.

Robot Software Architectures Workshop (RSA) 2023, ICRA, 2023 (techreport)

Abstract
Robotic applications require the integration of various modalities, encompassing perception, control of real robots and possibly the control of simulated environments. While the state-of-the-art robotic software solutions such as ROS 2 provide most of the required features, flexible synchronization between algorithms, data streams and control loops can be tedious. o80 is a versatile C++ framework for robotics which provides a shared memory model and a command framework for real-time critical systems. It enables expert users to set up complex robotic systems and generate Python bindings for scientists. o80's unique feature is its flexible synchronization between processes, including the traditional blocking commands and the novel ``bursting mode'', which allows user code to control the execution of the lower process control loop. This makes it particularly useful for setups that mix real and simulated environments.

ei

arxiv poster link (url) [BibTex]


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Borges und die Künstliche Intelligenz

Bottou, L., Schölkopf, B.

2023, published in Frankfurter Allgemeine Zeitung, 18 December 2023, Nr. 294 (misc)

ei

PDF [BibTex]

PDF [BibTex]