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2018


Deep Reinforcement Learning for Event-Triggered Control
Deep Reinforcement Learning for Event-Triggered Control

Baumann, D., Zhu, J., Martius, G., Trimpe, S.

In Proceedings of the 57th IEEE International Conference on Decision and Control (CDC), pages: 943-950, 57th IEEE International Conference on Decision and Control (CDC), December 2018 (inproceedings)

al ics

arXiv PDF DOI Project Page Project Page [BibTex]

2018


arXiv PDF DOI Project Page Project Page [BibTex]


Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds
Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds

Reeb, D., Doerr, A., Gerwinn, S., Rakitsch, B.

In Proceedings Neural Information Processing Systems, Neural Information Processing Systems (NIPS) , December 2018 (inproceedings)

Abstract
Gaussian Processes (GPs) are a generic modelling tool for supervised learning. While they have been successfully applied on large datasets, their use in safety critical applications is hindered by the lack of good performance guarantees. To this end, we propose a method to learn GPs and their sparse approximations by directly optimizing a PAC-Bayesian bound on their generalization performance, instead of maximizing the marginal likelihood. Besides its theoretical appeal, we find in our evaluation that our learning method is robust and yields significantly better generalization guarantees than other common GP approaches on several regression benchmark datasets.

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[BibTex]

[BibTex]


Efficient Encoding of Dynamical Systems through Local Approximations
Efficient Encoding of Dynamical Systems through Local Approximations

Solowjow, F., Mehrjou, A., Schölkopf, B., Trimpe, S.

In Proceedings of the 57th IEEE International Conference on Decision and Control (CDC), pages: 6073 - 6079 , Miami, Fl, USA, December 2018 (inproceedings)

ei ics

arXiv PDF DOI Project Page [BibTex]

arXiv PDF DOI Project Page [BibTex]


Depth Control of Underwater Robots using Sliding Modes and Gaussian Process Regression
Depth Control of Underwater Robots using Sliding Modes and Gaussian Process Regression

Lima, G. S., Bessa, W. M., Trimpe, S.

In Proceeding of the 15th Latin American Robotics Symposium, João Pessoa, Brazil, 15th Latin American Robotics Symposium, November 2018 (inproceedings)

Abstract
The development of accurate control systems for underwater robotic vehicles relies on the adequate compensation for hydrodynamic effects. In this work, a new robust control scheme is presented for remotely operated underwater vehicles. In order to meet both robustness and tracking requirements, sliding mode control is combined with Gaussian process regression. The convergence properties of the closed-loop signals are analytically proven. Numerical results confirm the stronger improved performance of the proposed control scheme.

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[BibTex]

[BibTex]


Gait learning for soft microrobots controlled by light fields
Gait learning for soft microrobots controlled by light fields

Rohr, A. V., Trimpe, S., Marco, A., Fischer, P., Palagi, S.

In International Conference on Intelligent Robots and Systems (IROS) 2018, pages: 6199-6206, International Conference on Intelligent Robots and Systems 2018, October 2018 (inproceedings)

Abstract
Soft microrobots based on photoresponsive materials and controlled by light fields can generate a variety of different gaits. This inherent flexibility can be exploited to maximize their locomotion performance in a given environment and used to adapt them to changing environments. However, because of the lack of accurate locomotion models, and given the intrinsic variability among microrobots, analytical control design is not possible. Common data-driven approaches, on the other hand, require running prohibitive numbers of experiments and lead to very sample-specific results. Here we propose a probabilistic learning approach for light-controlled soft microrobots based on Bayesian Optimization (BO) and Gaussian Processes (GPs). The proposed approach results in a learning scheme that is highly data-efficient, enabling gait optimization with a limited experimental budget, and robust against differences among microrobot samples. These features are obtained by designing the learning scheme through the comparison of different GP priors and BO settings on a semisynthetic data set. The developed learning scheme is validated in microrobot experiments, resulting in a 115% improvement in a microrobot’s locomotion performance with an experimental budget of only 20 tests. These encouraging results lead the way toward self-adaptive microrobotic systems based on lightcontrolled soft microrobots and probabilistic learning control.

ics pf

arXiv IEEE Xplore DOI Project Page [BibTex]

arXiv IEEE Xplore DOI Project Page [BibTex]


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Multi-objective Optimization of Nonconventional Laminated Composite Panels

Serhat, G.

Koc University, October 2018 (phdthesis)

Abstract
Laminated composite panels are extensively used in various industries due to their high stiffness-to-weight ratio and directional properties that allow optimization of stiffness characteristics for specific applications. With the recent improvements in the manufacturing techniques, the technology trend has been shifting towards the development of nonconventional composites. This work aims to develop new methods for the design and optimization of nonconventional laminated composites. Lamination parameters method is used to characterize laminate stiffness matrices in a compact form. An optimization framework based on finite element analysis was developed to calculate the solutions for different panel geometries, boundary conditions and load cases. The first part of the work addresses the multi-objective optimization of composite laminates to maximize dynamic and load-carrying performances simultaneously. Conforming and conflicting behaviors of multiple objective functions are investigated by determining Pareto-optimal solutions, which provide a valuable insight for multi-objective optimization problems. In the second part, design of curved laminated panels for optimal dynamic response is studied in detail. Firstly, the designs yielding maximum fundamental frequency values are computed. Next, optimal designs minimizing equivalent radiated power are obtained for the panels under harmonic pressure excitation, and their effective frequency bands are shown. The relationship between these two design sets is investigated to study the effectiveness of the frequency maximization technique. In the last part, a new method based on lamination parameters is proposed for the design of variable-stiffness composite panels. The results demonstrate that the proposed method provides manufacturable designs with smooth fiber paths that outperform the constant-stiffness laminates, while utilizing the advantages of lamination parameters formulation.

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Multi-objective Optimization of Nonconventional Laminated Composite Panels DOI [BibTex]


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Instrumentation, Data, and Algorithms for Visually Understanding Haptic Surface Properties

Burka, A. L.

University of Pennsylvania, Philadelphia, USA, August 2018, Department of Electrical and Systems Engineering (phdthesis)

Abstract
Autonomous robots need to efficiently walk over varied surfaces and grasp diverse objects. We hypothesize that the association between how such surfaces look and how they physically feel during contact can be learned from a database of matched haptic and visual data recorded from various end-effectors' interactions with hundreds of real-world surfaces. Testing this hypothesis required the creation of a new multimodal sensing apparatus, the collection of a large multimodal dataset, and development of a machine-learning pipeline. This thesis begins by describing the design and construction of the Portable Robotic Optical/Tactile ObservatioN PACKage (PROTONPACK, or Proton for short), an untethered handheld sensing device that emulates the capabilities of the human senses of vision and touch. Its sensory modalities include RGBD vision, egomotion, contact force, and contact vibration. Three interchangeable end-effectors (a steel tooling ball, an OptoForce three-axis force sensor, and a SynTouch BioTac artificial fingertip) allow for different material properties at the contact point and provide additional tactile data. We then detail the calibration process for the motion and force sensing systems, as well as several proof-of-concept surface discrimination experiments that demonstrate the reliability of the device and the utility of the data it collects. This thesis then presents a large-scale dataset of multimodal surface interaction recordings, including 357 unique surfaces such as furniture, fabrics, outdoor fixtures, and items from several private and public material sample collections. Each surface was touched with one, two, or three end-effectors, comprising approximately one minute per end-effector of tapping and dragging at various forces and speeds. We hope that the larger community of robotics researchers will find broad applications for the published dataset. Lastly, we demonstrate an algorithm that learns to estimate haptic surface properties given visual input. Surfaces were rated on hardness, roughness, stickiness, and temperature by the human experimenter and by a pool of purely visual observers. Then we trained an algorithm to perform the same task as well as infer quantitative properties calculated from the haptic data. Overall, the task of predicting haptic properties from vision alone proved difficult for both humans and computers, but a hybrid algorithm using a deep neural network and a support vector machine achieved a correlation between expected and actual regression output between approximately ρ = 0.3 and ρ = 0.5 on previously unseen surfaces.

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Project Page [BibTex]

Project Page [BibTex]


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Learning-Based Robust Model Predictive Control with State-Dependent Uncertainty

Soloperto, R., Müller, M. A., Trimpe, S., Allgöwer, F.

In Proceedings of the IFAC Conference on Nonlinear Model Predictive Control (NMPC), Madison, Wisconsin, USA, 6th IFAC Conference on Nonlinear Model Predictive Control, August 2018 (inproceedings)

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PDF [BibTex]

PDF [BibTex]


Robust Visual Augmented Reality in Robot-Assisted Surgery
Robust Visual Augmented Reality in Robot-Assisted Surgery

Forte, M. P.

Politecnico di Milano, Milan, Italy, July 2018, Department of Electronic, Information, and Biomedical Engineering (mastersthesis)

Abstract
The broader research objective of this line of research is to test the hypothesis that real-time stereo video analysis and augmented reality can increase safety and task efficiency in robot-assisted surgery. This master’s thesis aims to solve the first step needed to achieve this goal: the creation of a robust system that delivers the envisioned feedback to a surgeon while he or she controls a surgical robot that is identical to those used on human patients. Several approaches for applying augmented reality to da Vinci Surgical Systems have been proposed, but none of them entirely rely on a clinical robot; specifically, they require additional sensors, depend on access to the da Vinci API, are designed for a very specific task, or were tested on systems that are starkly different from those in clinical use. There has also been prior work that presents the real-world camera view and the computer graphics on separate screens, or not in real time. In other scenarios, the digital information is overlaid manually by the surgeons themselves or by computer scientists, rather than being generated automatically in response to the surgeon’s actions. We attempted to overcome the aforementioned constraints by acquiring input signals from the da Vinci stereo endoscope and providing augmented reality to the console in real time (less than 150 ms delay, including the 62 ms of inherent latency of the da Vinci). The potential benefits of the resulting system are broad because it was built to be general, rather than customized for any specific task. The entire platform is compatible with any generation of the da Vinci System and does not require a dVRK (da Vinci Research Kit) or access to the API. Thus, it can be applied to existing da Vinci Systems in operating rooms around the world.

hi

Project Page [BibTex]

Project Page [BibTex]


Probabilistic Recurrent State-Space Models
Probabilistic Recurrent State-Space Models

Doerr, A., Daniel, C., Schiegg, M., Nguyen-Tuong, D., Schaal, S., Toussaint, M., Trimpe, S.

In Proceedings of the International Conference on Machine Learning (ICML), International Conference on Machine Learning (ICML), July 2018 (inproceedings)

Abstract
State-space models (SSMs) are a highly expressive model class for learning patterns in time series data and for system identification. Deterministic versions of SSMs (e.g., LSTMs) proved extremely successful in modeling complex time-series data. Fully probabilistic SSMs, however, unfortunately often prove hard to train, even for smaller problems. To overcome this limitation, we propose a scalable initialization and training algorithm based on doubly stochastic variational inference and Gaussian processes. In the variational approximation we propose in contrast to related approaches to fully capture the latent state temporal correlations to allow for robust training.

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arXiv pdf Project Page [BibTex]

arXiv pdf Project Page [BibTex]


Event-triggered Learning for Resource-efficient Networked Control
Event-triggered Learning for Resource-efficient Networked Control

Solowjow, F., Baumann, D., Garcke, J., Trimpe, S.

In Proceedings of the American Control Conference (ACC), pages: 6506 - 6512, American Control Conference, June 2018 (inproceedings)

ics

arXiv PDF DOI Project Page [BibTex]

arXiv PDF DOI Project Page [BibTex]


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Poster Abstract: Toward Fast Closed-loop Control over Multi-hop Low-power Wireless Networks

Mager, F., Baumann, D., Trimpe, S., Zimmerling, M.

Proceedings of the 17th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN), pages: 158-159, Porto, Portugal, April 2018 (poster)

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


Evaluating Low-Power Wireless Cyber-Physical Systems
Evaluating Low-Power Wireless Cyber-Physical Systems

Baumann, D., Mager, F., Singh, H., Zimmerling, M., Trimpe, S.

In Proceedings of the IEEE Workshop on Benchmarking Cyber-Physical Networks and Systems (CPSBench), pages: 13-18, IEEE Workshop on Benchmarking Cyber-Physical Networks and Systems (CPSBench), April 2018 (inproceedings)

ics

arXiv PDF DOI Project Page [BibTex]

arXiv PDF DOI Project Page [BibTex]


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Travelling Ultrasonic Wave Enhances Keyclick Sensation

Gueorguiev, D., Kaci, A., Amberg, M., Giraud, F., Lemaire-Semail, B.

In Haptics: Science, Technology, and Applications, pages: 302-312, Springer International Publishing, Cham, 2018 (inproceedings)

Abstract
A realistic keyclick sensation is a serious challenge for haptic feedback since vibrotactile rendering faces the limitation of the absence of contact force as experienced on physical buttons. It has been shown that creating a keyclick sensation is possible with stepwise ultrasonic friction modulation. However, the intensity of the sensation is limited by the impedance of the fingertip and by the absence of a lateral force component external to the finger. In our study, we compare this technique to rendering with an ultrasonic travelling wave, which exerts a lateral force on the fingertip. For both techniques, participants were asked to report the detection (or not) of a keyclick during a forced choice one interval procedure. In experiment 1, participants could press the surface as many time as they wanted for a given trial. In experiment 2, they were constrained to press only once. The results show a lower perceptual threshold for travelling waves. Moreover, participants pressed less times per trial and exerted smaller normal force on the surface. The subjective quality of the sensation was found similar for both techniques. In general, haptic feedback based on travelling ultrasonic waves is promising for applications without lateral motion of the finger.

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[BibTex]

[BibTex]


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Exploring Fingers’ Limitation of Texture Density Perception on Ultrasonic Haptic Displays

Kalantari, F., Gueorguiev, D., Lank, E., Bremard, N., Grisoni, L.

In Haptics: Science, Technology, and Applications, pages: 354-365, Springer International Publishing, Cham, 2018 (inproceedings)

Abstract
Recent research in haptic feedback is motivated by the crucial role that tactile perception plays in everyday touch interactions. In this paper, we describe psychophysical experiments to investigate the perceptual threshold of individual fingers on both the right and left hand of right-handed participants using active dynamic touch for spatial period discrimination of both sinusoidal and square-wave gratings on ultrasonic haptic touchscreens. Both one-finger and multi-finger touch were studied and compared. Our results indicate that users' finger identity (index finger, middle finger, etc.) significantly affect the perception of both gratings in the case of one-finger exploration. We show that index finger and thumb are the most sensitive in all conditions whereas little finger followed by ring are the least sensitive for haptic perception. For multi-finger exploration, the right hand was found to be more sensitive than the left hand for both gratings. Our findings also demonstrate similar perception sensitivity between multi-finger exploration and the index finger of users' right hands (i.e. dominant hand in our study), while significant difference was found between single and multi-finger perception sensitivity for the left hand.

hi

[BibTex]

[BibTex]


Tactile perception by electrovibration
Tactile perception by electrovibration

Vardar, Y.

Koc University, 2018 (phdthesis)

Abstract
One approach to generating realistic haptic feedback on touch screens is electrovibration. In this technique, the friction force is altered via electrostatic forces, which are generated by applying an alternating voltage signal to the conductive layer of a capacitive touchscreen. Although the technology for rendering haptic effects on touch surfaces using electrovibration is already in place, our knowledge of the perception mechanisms behind these effects is limited. This thesis aims to explore the mechanisms underlying haptic perception of electrovibration in two parts. In the first part, the effect of input signal properties on electrovibration perception is investigated. Our findings indicate that the perception of electrovibration stimuli depends on frequency-dependent electrical properties of human skin and human tactile sensitivity. When a voltage signal is applied to a touchscreen, it is filtered electrically by human finger and it generates electrostatic forces in the skin and mechanoreceptors. Depending on the spectral energy content of this electrostatic force signal, different psychophysical channels may be activated. The channel which mediates the detection is determined by the frequency component which has a higher energy than the sensory threshold at that frequency. In the second part, effect of masking on the electrovibration perception is investigated. We show that the detection thresholds are elevated as linear functions of masking levels for simultaneous and pedestal masking. The masking effectiveness is larger for pedestal masking compared to simultaneous masking. Moreover, our results suggest that sharpness perception depends on the local contrast between background and foreground stimuli, which varies as a function of masking amplitude and activation levels of frequency-dependent psychophysical channels.

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Tactile perception by electrovibration [BibTex]

2013


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Determination of an Analysis Procedure for FEM-Based Fatigue Calculations

Serhat, G.

Technical University of Munich, December 2013 (mastersthesis)

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[BibTex]

2013


[BibTex]


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Virtual Robotization of the Human Body via Data-Driven Vibrotactile Feedback

Kurihara, Y., Hachisu, T., Kuchenbecker, K. J., Kajimoto, H.

In Proc. International Conference on Advances in Computer Entertainment Technology (ACE), 8253, pages: 109-122, Lecture Notes in Computer Science, Springer, Enschede, Netherlands, 2013, Oral presentation given by Kurihara. Best Paper Silver Award (inproceedings)

hi

[BibTex]

[BibTex]


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Virtual Robotization of the Human Body Using Vibration Recording, Modeling and Rendering

Kurihara, Y., Hachisu, T., Kuchenbecker, K. J., Kajimoto, H.

In Proc. Virtual Reality Society of Japan Annual Conference, Osaka, Japan, sep 2013, Paper written in Japanese. Presentation given by Kurihara (inproceedings)

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[BibTex]

[BibTex]


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Virtual Alteration of Body Material by Reality-Based Periodic Vibrotactile Feedback

Kurihara, Y., Hachisu, T., Sato, M., Fukushima, S., Kuchenbecker, K. J., Kajimoto, H.

In Proc. JSME Robotics and Mechatronics Conference (ROBOMEC), Tsukuba, Japan, May 2013, Paper written in Japanese. Poster presentation given by {Kurihara} (inproceedings)

hi

[BibTex]

[BibTex]


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The Design and Field Observation of a Haptic Notification System for Oral Presentations

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

In Proc. SIGCHI Conference on Human Factors in Computing Systems, pages: 1689-1698, Paris, France, May 2013, Oral presentation given by Tam (inproceedings)

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[BibTex]

[BibTex]


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Using Robotic Exploratory Procedures to Learn the Meaning of Haptic Adjectives

Chu, V., McMahon, I., Riano, L., McDonald, C. G., He, Q., Perez-Tejada, J. M., Arrigo, M., Fitter, N., Nappo, J., Darrell, T., Kuchenbecker, K. J.

In Proc. IEEE International Conference on Robotics and Automation, pages: 3048-3055, Karlsruhe, Germany, May 2013, Oral presentation given by Chu. Best Cognitive Robotics Paper Award (inproceedings)

hi

[BibTex]

[BibTex]


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Instrument contact vibrations are a construct-valid measure of technical skill in Fundamentals of Laparoscopic Surgery Training Tasks

Gomez, E. D., Aggarwal, R., McMahan, W., Koch, E., Hashimoto, D. A., Darzi, A., Murayama, K. M., Dumon, K. R., Williams, N. N., Kuchenbecker, K. J.

In Proc. Annual Meeting of the Association for Surgical Education, Orlando, Florida, USA, 2013, Oral presentation given by Gomez (inproceedings)

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[BibTex]

[BibTex]


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Dynamic Simulation of Tool-Mediated Texture Interaction

McDonald, C. G., Kuchenbecker, K. J.

In Proc. IEEE World Haptics Conference, pages: 307-312, Daejeon, South Korea, April 2013, Oral presentation given by McDonald (inproceedings)

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[BibTex]

[BibTex]


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Generating Haptic Texture Models From Unconstrained Tool-Surface Interactions

Culbertson, H., Unwin, J., Goodman, B. E., Kuchenbecker, K. J.

In Proc. IEEE World Haptics Conference, pages: 295-300, Daejeon, South Korea, April 2013, Oral presentation given by Culbertson. Finalist for Best Paper Award (inproceedings)

hi

[BibTex]

[BibTex]


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A practical System for Recording Instrument Contacts and Collisions During Transoral Robotic Surgery

Gomez, E. D., Weinstein, G. S., O’Malley, J. B. W., McMahan, W., Chen, L., Kuchenbecker, K. J.

In Proc. Annual Meeting of the Triological Society, Orlando, Florida, USA, April 2013, Poster presentation given by Gomez (inproceedings)

hi

[BibTex]

[BibTex]


Self-tuning in Sliding Mode Control of High-Precision Motion Systems
Self-tuning in Sliding Mode Control of High-Precision Motion Systems

Heertjes, M. F., Vardar, Y.

In IFAC Proceedings Volumes, 46(5):13 - 19, 2013, 6th IFAC Symposium on Mechatronic Systems (inproceedings)

Abstract
In high-precision motion systems, set-point tracking often comes with the problem of overshoot, hence poor settling behavior. To avoid overshoot, PD control (thus without using an integrator) is preferred over PID control. However, PD control gives rise to steady-state error in view of the constant disturbances acting on the system. To deal with both overshoot and steady-state error, a sliding mode controller with saturated integrator is studied. For large servo signals the controller is switched to PD mode as to constrain the integrator buffer and therefore the overshoot. For small servo signals the controller switches to PID mode as to avoid steady-state error. The tuning of the switching parameters will be done automatically with the aim to optimize the settling behavior. The sliding mode controller will be tested on a high-precision motion system.

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heertjes_ifac2013 link (url) DOI [BibTex]

heertjes_ifac2013 link (url) DOI [BibTex]


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A Practical System For Recording Instrument Interactions During Live Robotic Surgery

McMahan, W., Gomez, E. D., Chen, L., Bark, K., Nappo, J. C., Koch, E. I., Lee, D. I., Dumon, K., Williams, N., Kuchenbecker, K. J.

In Proc. Medicine Meets Virtual Reality, 2013, Poster presentation given by McMahan (inproceedings)

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[BibTex]

[BibTex]

2005


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Perception of Curvature and Object Motion Via Contact Location Feedback

Provancher, W. R., Kuchenbecker, K. J., Niemeyer, G., Cutkosky, M. R.

In Proceedings of the International Symposium on Robotics Research (ISRR), 15, pages: 456-465, Springer Tracts in Advanced Robotics, Springer, Siena, Italy, 2005, Oral presentation given by Provancher in October of 2003 (inproceedings)

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[BibTex]

2005


[BibTex]


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Modeling Induced Master Motion in Force-Reflecting Teleoperation

Kuchenbecker, K. J., Niemeyer, G.

In Proc. IEEE International Conference on Robotics and Automation, pages: 348-353, Barcelona, Spain, April 2005, Oral presentation given by Kuchenbecker (inproceedings)

hi

[BibTex]

[BibTex]


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Event-Based Haptics and Acceleration Matching: Portraying and Assessing the Realism of Contact

Kuchenbecker, K. J., Fiene, J. P., Niemeyer, G.

In Proc. IEEE World Haptics Conference, pages: 381-387, Pisa, Italy, March 2005, Oral presentation given by Kuchenbecker (inproceedings)

hi

[BibTex]

[BibTex]