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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]


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.

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arXiv IEEE Xplore DOI Project Page [BibTex]

arXiv IEEE Xplore DOI 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)

ics

PDF [BibTex]

PDF [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.

am ics

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]


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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Enhanced Non-Steady Gliding Performance of the MultiMo-Bat through Optimal Airfoil Configuration and Control Strategy

Kim, H., Woodward, M. A., Sitti, M.

In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 1382-1388, 2018 (inproceedings)

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[BibTex]

[BibTex]


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Collectives of Spinning Mobile Microrobots for Navigation and Object Manipulation at the Air-Water Interface

Wang, W., Kishore, V., Koens, L., Lauga, E., Sitti, M.

In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 1-9, 2018 (inproceedings)

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[BibTex]

[BibTex]


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Endo-VMFuseNet: A Deep Visual-Magnetic Sensor Fusion Approach for Endoscopic Capsule Robots

Turan, M., Almalioglu, Y., Gilbert, H. B., Sari, A. E., Soylu, U., Sitti, M.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 1-7, 2018 (inproceedings)

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[BibTex]

[BibTex]


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Endosensorfusion: Particle filtering-based multi-sensory data fusion with switching state-space model for endoscopic capsule robots

Turan, M., Almalioglu, Y., Gilbert, H., Araujo, H., Cemgil, T., Sitti, M.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 1-8, 2018 (inproceedings)

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[BibTex]

[BibTex]


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Direct observations of sub-100 nm spin wave propagation in magnonic wave-guides

Träger, N., Gruszecki, P., Lisiecki, F., Förster, J., Weigand, M., Kuswik, P., Dubowik, J., Schütz, G., Krawczyk, M., Gräfe, J.

In 2018 IEEE International Magnetics Conference (INTERMAG 2018), IEEE, Singapore, 2018 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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Interpreting FORC diagrams beyond the Preisach model: an experimental permalloy micro array investigation

Gross, F., Ilse, S., Schütz, G., Gräfe, J., Goering, E.

In 2018 IEEE International Magnetics Conference (INTERMAG 2018), IEEE, Singapore, 2018 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]

2015


Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results
Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results

Marco, A., Hennig, P., Bohg, J., Schaal, S., Trimpe, S.

Machine Learning in Planning and Control of Robot Motion Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (iROS), pages: , , Machine Learning in Planning and Control of Robot Motion Workshop, October 2015 (conference)

Abstract
This paper proposes an automatic controller tuning framework based on linear optimal control combined with Bayesian optimization. With this framework, an initial set of controller gains is automatically improved according to a pre-defined performance objective evaluated from experimental data. The underlying Bayesian optimization algorithm is Entropy Search, which represents the latent objective as a Gaussian process and constructs an explicit belief over the location of the objective minimum. This is used to maximize the information gain from each experimental evaluation. Thus, this framework shall yield improved controllers with fewer evaluations compared to alternative approaches. A seven-degree-of-freedom robot arm balancing an inverted pole is used as the experimental demonstrator. Preliminary results of a low-dimensional tuning problem highlight the method’s potential for automatic controller tuning on robotic platforms.

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PDF DOI Project Page [BibTex]

2015


PDF DOI Project Page [BibTex]


Compliant wing design for a flapping wing micro air vehicle
Compliant wing design for a flapping wing micro air vehicle

Colmenares, D., Kania, R., Zhang, W., Sitti, M.

In Intelligent Robots and Systems (IROS), 2015 IEEE/RSJ International Conference on, pages: 32-39, September 2015 (inproceedings)

Abstract
In this work, we examine several wing designs for a motor-driven, flapping-wing micro air vehicle capable of liftoff. The full system consists of two wings independently driven by geared pager motors that include a spring in parallel with the output shaft. The linear transmission allows for resonant operation, while control is achieved by direct drive of the wing angle. Wings used in previous work were chosen to be fully rigid for simplicity of modeling and fabrication. However, biological wings are highly flexible and other micro air vehicles have successfully utilized flexible wing structures for specialized tasks. The goal of our study is to determine if wing flexibility can be generally used to increase wing performance. Two approaches to lift improvement using flexible wings are explored, resonance of the wing cantilever structure and dynamic wing twisting. We design and test several wings that are compared using different figures of merit. A twisted design improved lift per power by 73.6% and maximum lift production by 53.2% compared to the original rigid design. Wing twist is then modeled in order to propose optimal wing twist profiles that can maximize either wing efficiency or lift production.

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DOI [BibTex]

DOI [BibTex]


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Millimeter-scale magnetic swimmers using elastomeric undulations

Zhang, J., Diller, E.

In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 1706-1711, September 2015 (inproceedings)

Abstract
This paper presents a new soft-bodied millimeterscale swimmer actuated by rotating uniform magnetic fields. The proposed swimmer moves through internal undulatory deformations, resulting from a magnetization profile programmed into its body. To understand the motion of the swimmer, a mathematical model is developed to describe the general relationship between the deflection of a flexible strip and its magnetization profile. As a special case, the situation of the swimmer on the water surface is analyzed and predictions made by the model are experimentally verified. Experimental results show the controllability of the proposed swimmer under a computer vision-based closed-loop controller. The swimmers have nominal dimensions of 1.5×4.9×0.06 mm and a top speed of 50 mm/s (10 body lengths per second). Waypoint following and multiagent control are demonstrated for swimmers constrained at the air-water interface and underwater swimming is also shown, suggesting the promising potential of this type of swimmer in biomedical and microfluidic applications.

pi

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Direct Loss Minimization Inverse Optimal Control
Direct Loss Minimization Inverse Optimal Control

Doerr, A., Ratliff, N., Bohg, J., Toussaint, M., Schaal, S.

In Proceedings of Robotics: Science and Systems, Rome, Italy, Robotics: Science and Systems XI, July 2015 (inproceedings)

Abstract
Inverse Optimal Control (IOC) has strongly impacted the systems engineering process, enabling automated planner tuning through straightforward and intuitive demonstration. The most successful and established applications, though, have been in lower dimensional problems such as navigation planning where exact optimal planning or control is feasible. In higher dimensional systems, such as humanoid robots, research has made substantial progress toward generalizing the ideas to model free or locally optimal settings, but these systems are complicated to the point where demonstration itself can be difficult. Typically, real-world applications are restricted to at best noisy or even partial or incomplete demonstrations that prove cumbersome in existing frameworks. This work derives a very flexible method of IOC based on a form of Structured Prediction known as Direct Loss Minimization. The resulting algorithm is essentially Policy Search on a reward function that rewards similarity to demonstrated behavior (using Covariance Matrix Adaptation (CMA) in our experiments). Our framework blurs the distinction between IOC, other forms of Imitation Learning, and Reinforcement Learning, enabling us to derive simple, versatile, and practical algorithms that blend imitation and reinforcement signals into a unified framework. Our experiments analyze various aspects of its performance and demonstrate its efficacy on conveying preferences for motion shaping and combined reach and grasp quality optimization.

am ics

PDF Video Project Page [BibTex]

PDF Video Project Page [BibTex]


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LMI-Based Synthesis for Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceedings of the American Control Conference, July 2015 (inproceedings)

Abstract
This paper presents an LMI-based synthesis procedure for distributed event-based state estimation. Multiple agents observe and control a dynamic process by sporadically exchanging data over a broadcast network according to an event-based protocol. In previous work [1], the synthesis of event-based state estimators is based on a centralized design. In that case three different types of communication are required: event-based communication of measurements, periodic reset of all estimates to their joint average, and communication of inputs. The proposed synthesis problem eliminates the communication of inputs as well as the periodic resets (under favorable circumstances) by accounting explicitly for the distributed structure of the control system.

am ics

PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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Guaranteed H2 Performance in Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceeding of the First International Conference on Event-based Control, Communication, and Signal Processing, June 2015 (inproceedings)

am ics

PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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On the Choice of the Event Trigger in Event-based Estimation

Trimpe, S., Campi, M.

In Proceeding of the First International Conference on Event-based Control, Communication, and Signal Processing, June 2015 (inproceedings)

am ics

PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


Fiberbot: A miniature crawling robot using a directional fibrillar pad
Fiberbot: A miniature crawling robot using a directional fibrillar pad

Han, Y., Marvi, H., Sitti, M.

In Robotics and Automation (ICRA), 2015 IEEE International Conference on, pages: 3122-3127, May 2015 (inproceedings)

Abstract
Vibration-driven locomotion has been widely used for crawling robot studies. Such robots usually have a vibration motor as the actuator and a fibrillar structure for providing directional friction on the substrate. However, there has not been any studies about the effect of fiber structure on robot crawling performance. In this paper, we develop Fiberbot, a custom made mini vibration robot, for studying the effect of fiber angle on robot velocity, steering, and climbing performance. It is known that the friction force with and against fibers depends on the fiber angle. Thus, we first present a new fabrication method for making millimeter scale fibers at a wide range of angles. We then show that using 30° angle fibers that have the highest friction anisotropy (ratio of backward to forward friction force) among the other fibers we fabricated in this study, Fiberbot speed on glass increases to 13.8±0.4 cm/s (compared to ν = 0.6±0.1 cm/s using vertical fibers). We also demonstrate that the locomotion direction of Fiberbot depends on the tilting direction of fibers and we can steer the robot by rotating the fiber pad. Fiberbot could also climb on glass at inclinations of up to 10° when equipped with fibers of high friction anisotropy. We show that adding a rigid tail to the robot it can climb on glass at 25° inclines. Moreover, the robot is able to crawl on rough surfaces such as wood (ν = 10.0±0.2 cm/s using 30° fiber pad). Fiberbot, a low-cost vibration robot equipped with a custom-designed fiber pad with steering and climbing capabilities could be used for studies on collective behavior on a wide range of topographies as well as search and exploratory missions.

pi

DOI [BibTex]

DOI [BibTex]


Platform design and tethered flight of a motor-driven flapping-wing system
Platform design and tethered flight of a motor-driven flapping-wing system

Hines, L., Colmenares, D., Sitti, M.

In Robotics and Automation (ICRA), 2015 IEEE International Conference on, pages: 5838-5845, May 2015 (inproceedings)

Abstract
In this work, we examine two design modifications to a tethered motor-driven flapping-wing system. Previously, we had demonstrated a simple mechanism utilizing a linear transmission for resonant operation and direct drive of the wing flapping angle for control. The initial two-wing system had a weight of 2.7 grams and a maximum lift-to-weight ratio of 1.4. While capable of vertical takeoff, in open-loop flight it demonstrated instability and pitch oscillations at the wing flapping frequency, leading to flight times of only a few wing strokes. Here the effect of vertical wing offset as well as an alternative multi-wing layout is investigated and experimentally tested with newly constructed prototypes. With only a change in vertical wing offset, stable open-loop flight of the two-wing flapping system is shown to be theoretically possible, but difficult to achieve with our current design and operating parameters. Both of the new two and four-wing systems, however, prove capable of flying to the end of the tether, with the four-wing system prototype eliminating disruptive wing beat oscillations.

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DOI [BibTex]

DOI [BibTex]


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Event-based Estimation and Control for Remote Robot Operation with Reduced Communication

Trimpe, S., Buchli, J.

In Proceedings of the IEEE International Conference on Robotics and Automation, May 2015 (inproceedings)

Abstract
An event-based communication framework for remote operation of a robot via a bandwidth-limited network is proposed. The robot sends state and environment estimation data to the operator, and the operator transmits updated control commands or policies to the robot. Event-based communication protocols are designed to ensure that data is transmitted only when required: the robot sends new estimation data only if this yields a significant information gain at the operator, and the operator transmits an updated control policy only if this comes with a significant improvement in control performance. The developed framework is modular and can be used with any standard estimation and control algorithms. Simulation results of a robotic arm highlight its potential for an efficient use of limited communication resources, for example, in disaster response scenarios such as the DARPA Robotics Challenge.

am ics

PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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A New Perspective and Extension of the Gaussian Filter

Wüthrich, M., Trimpe, S., Kappler, D., Schaal, S.

In Robotics: Science and Systems, 2015 (inproceedings)

Abstract
The Gaussian Filter (GF) is one of the most widely used filtering algorithms; instances are the Extended Kalman Filter, the Unscented Kalman Filter and the Divided Difference Filter. GFs represent the belief of the current state by a Gaussian with the mean being an affine function of the measurement. We show that this representation can be too restrictive to accurately capture the dependencies in systems with nonlinear observation models, and we investigate how the GF can be generalized to alleviate this problem. To this end we view the GF from a variational-inference perspective, and analyze how restrictions on the form of the belief can be relaxed while maintaining simplicity and efficiency. This analysis provides a basis for generalizations of the GF. We propose one such generalization which coincides with a GF using a virtual measurement, obtained by applying a nonlinear function to the actual measurement. Numerical experiments show that the proposed Feature Gaussian Filter (FGF) can have a substantial performance advantage over the standard GF for systems with nonlinear observation models.

am ics

Web PDF Project Page [BibTex]


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Combined FORC and x-ray microscopy study of magnetisation reversal in antidot lattices

Gräfe, J., Haering, F., Stahl, C., Weigand, M., Skripnik, M., Nowak, U., Ziemann, P., Wiedwald, U., Schütz, G., Goering, E.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


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Local control of domain wall dynamics in ferromagnetic rings

Richter, K., Mawass, M., Krone, A., Krüger, B., Weigand, M., Stoll, H., Schütz, G., Kläui, M.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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Ultrafast demagnetization after laser pulse irradiation in Ni: Ab-initio electron-phonon scattering and phase space calculations

Illg, C., Haag, M., Fähnle, M.

In Ultrafast Magnetism I. Proceedings of the International Conference UMC 2013, 159, pages: 131-133, Springer Proceedings in Physics, Springer, Strasbourg, 2015 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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Automotive domain wall propagation in ferromagnetic rings

Richter, K., Mawass, M., Krone, A., Krüger, B., Weigand, M., Schütz, G., Stoll, H., Kläui, M.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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The third dimension: Vortex core reversal by interaction with \textquotesingleflexure modes’

Noske, M., Stoll, H., Fähnle, M., Weigand, M., Dieterle, G., Förster, J., Gangwar, A., Slavin, A., Back, C. H., Schütz, G.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]


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Skyrmions at room temperature in magnetic multilayers

Moreau-Luchaire, C., Reyren, N., Moutafis, C., Sampaio, J., Van Horne, N., Vaz, C. A., Warnicke, P., Garcia, K., Weigand, M., Bouzehouane, K., Deranlot, C., George, J., Raabe, J., Cros, V., Fert, A.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

mms

DOI [BibTex]

DOI [BibTex]

2007


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A strategy for vision-based controlled pushing of microparticles

Lynch, N. A., Onal, C., Schuster, E., Sitti, M.

In Robotics and Automation, 2007 IEEE International Conference on, pages: 1413-1418, 2007 (inproceedings)

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[BibTex]

2007


[BibTex]


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Autonomous 2D microparticle manipulation based on visual feedback

Onal, C. D., Sitti, M.

In Advanced intelligent mechatronics, 2007 IEEE/ASME international conference on, pages: 1-6, 2007 (inproceedings)

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[BibTex]

[BibTex]


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STRIDE: A highly maneuverable and non-tethered water strider robot

Song, Y. S., Sitti, M.

In Robotics and Automation, 2007 IEEE International Conference on, pages: 980-984, 2007 (inproceedings)

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[BibTex]

[BibTex]


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Dry spinning polymeric nano/microfiber arrays using glass micropipettes with controlled porosities and fiber diameters

Nain, A. S., Gupta, A., Amon, C., Sitti, M.

In Nanotechnology, 2007. IEEE-NANO 2007. 7th IEEE Conference on, pages: 728-732, 2007 (inproceedings)

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[BibTex]

[BibTex]


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Microrobotically fabricated biological scaffolds for tissue engineering

Nain, A. S., Chung, F., Rule, M., Jadlowiec, J. A., Campbell, P. G., Amon, C., Sitti, M.

In Robotics and Automation, 2007 IEEE International Conference on, pages: 1918-1923, 2007 (inproceedings)

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[BibTex]

[BibTex]


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Bacterial flagella assisted propulsion of patterned latex particles: Effect of particle size

Behkam, B., Sitti, M.

In Nanotechnology, 2007. IEEE-NANO 2007. 7th IEEE Conference on, pages: 723-727, 2007 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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A scaled bilateral control system for experimental 1-D teleoperated nanomanipulation applications

Onal, C. D., Pawashe, C., Sitti, M.

In Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on, pages: 483-488, 2007 (inproceedings)

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[BibTex]

[BibTex]