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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)

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arXiv PDF DOI Project Page Project Page [BibTex]

2018


arXiv PDF DOI Project Page Project Page [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]


Colloidal Chemical Nanomotors
Colloidal Chemical Nanomotors

Alarcon-Correa, M.

Colloidal Chemical Nanomotors, pages: 150, Cuvillier Verlag, MPI-IS , June 2018 (phdthesis)

Abstract
Synthetic sophisticated nanostructures represent a fundamental building block for the development of nanotechnology. The fabrication of nanoparticles complex in structure and material composition is key to build nanomachines that can operate as man-made nanoscale motors, which autonomously convert external energy into motion. To achieve this, asymmetric nanoparticles were fabricated combining a physical vapor deposition technique known as NanoGLAD and wet chemical synthesis. This thesis primarily concerns three complex colloidal systems that have been developed: i)Hollow nanocup inclusion complexes that have a single Au nanoparticle in their pocket. The Au particle can be released with an external trigger. ii)The smallest self-propelling nanocolloids that have been made to date, which give rise to a local concentration gradient that causes enhanced diffusion of the particles. iii)Enzyme-powered pumps that have been assembled using bacteriophages as biological nanoscaffolds. This construct also can be used for enzyme recovery after heterogeneous catalysis.

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[BibTex]

[BibTex]


Soft Miniaturized Linear Actuators Wirelessly Powered by Rotating Permanent Magnets
Soft Miniaturized Linear Actuators Wirelessly Powered by Rotating Permanent Magnets

Qiu, T., Palagi, S., Sachs, J., Fischer, P.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 3595-3600, May 2018 (inproceedings)

Abstract
Wireless actuation by magnetic fields allows for the operation of untethered miniaturized devices, e.g. in biomedical applications. Nevertheless, generating large controlled forces over relatively large distances is challenging. Magnetic torques are easier to generate and control, but they are not always suitable for the tasks at hand. Moreover, strong magnetic fields are required to generate a sufficient torque, which are difficult to achieve with electromagnets. Here, we demonstrate a soft miniaturized actuator that transforms an externally applied magnetic torque into a controlled linear force. We report the design, fabrication and characterization of both the actuator and the magnetic field generator. We show that the magnet assembly, which is based on a set of rotating permanent magnets, can generate strong controlled oscillating fields over a relatively large workspace. The actuator, which is 3D-printed, can lift a load of more than 40 times its weight. Finally, we show that the actuator can be further miniaturized, paving the way towards strong, wirelessly powered microactuators.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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L4: Practical loss-based stepsize adaptation for deep learning

Rolinek, M., Martius, G.

In Advances in Neural Information Processing Systems 31 (NeurIPS 2018), pages: 6434-6444, (Editors: S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett), Curran Associates, Inc., 2018 (inproceedings)

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Github link (url) Project Page [BibTex]

Github link (url) Project Page [BibTex]


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Pattern forming systems under confinement

Maihöfer, Michael

Universität Stuttgart, Stuttgart, 2018 (mastersthesis)

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[BibTex]

[BibTex]


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Effective interactions between colloidal particles in critical solvents

Labbe-Laurent, M.

Universität Stuttgart, Stuttgart, 2018 (phdthesis)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Systematic self-exploration of behaviors for robots in a dynamical systems framework
Systematic self-exploration of behaviors for robots in a dynamical systems framework

Pinneri, C., Martius, G.

In Proc. Artificial Life XI, pages: 319-326, MIT Press, Cambridge, MA, 2018 (inproceedings)

Abstract
One of the challenges of this century is to understand the neural mechanisms behind cognitive control and learning. Recent investigations propose biologically plausible synaptic mechanisms for self-organizing controllers, in the spirit of Hebbian learning. In particular, differential extrinsic plasticity (DEP) [Der and Martius, PNAS 2015], has proven to enable embodied agents to self-organize their individual sensorimotor development, and generate highly coordinated behaviors during their interaction with the environment. These behaviors are attractors of a dynamical system. In this paper, we use the DEP rule to generate attractors and we combine it with a “repelling potential” which allows the system to actively explore all its attractor behaviors in a systematic way. With a view to a self-determined exploration of goal-free behaviors, our framework enables switching between different motion patterns in an autonomous and sequential fashion. Our algorithm is able to recover all the attractor behaviors in a toy system and it is also effective in two simulated environments. A spherical robot discovers all its major rolling modes and a hexapod robot learns to locomote in 50 different ways in 30min.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Non-equilibrium dynamics of a binary solvent around heated colloidal particles

Wilke, Moritz

Universität Stuttgart, Stuttgart, 2018 (mastersthesis)

icm

[BibTex]

[BibTex]


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Monte Carlo study of colloidal structure formation at fluid interfaces

Meiler, Tim

Universität Stuttgart, Stuttgart, 2018 (mastersthesis)

icm

[BibTex]

[BibTex]


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Electrolyte solutions and simple fluids at curved walls

Reindl, A.

Universität Stuttgart, Stuttgart, 2018 (phdthesis)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Learning equations for extrapolation and control
Learning equations for extrapolation and control

Sahoo, S. S., Lampert, C. H., Martius, G.

In Proc. 35th International Conference on Machine Learning, ICML 2018, Stockholm, Sweden, 2018, 80, pages: 4442-4450, http://proceedings.mlr.press/v80/sahoo18a/sahoo18a.pdf, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, 2018 (inproceedings)

Abstract
We present an approach to identify concise equations from data using a shallow neural network approach. In contrast to ordinary black-box regression, this approach allows understanding functional relations and generalizing them from observed data to unseen parts of the parameter space. We show how to extend the class of learnable equations for a recently proposed equation learning network to include divisions, and we improve the learning and model selection strategy to be useful for challenging real-world data. For systems governed by analytical expressions, our method can in many cases identify the true underlying equation and extrapolate to unseen domains. We demonstrate its effectiveness by experiments on a cart-pendulum system, where only 2 random rollouts are required to learn the forward dynamics and successfully achieve the swing-up task.

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Code Arxiv Poster Slides link (url) Project Page [BibTex]

Code Arxiv Poster Slides link (url) Project Page [BibTex]


Robust Affordable 3D Haptic Sensation via Learning Deformation Patterns
Robust Affordable 3D Haptic Sensation via Learning Deformation Patterns

Sun, H., Martius, G.

Proceedings International Conference on Humanoid Robots, pages: 846-853, IEEE, New York, NY, USA, 2018 IEEE-RAS International Conference on Humanoid Robots, 2018, Oral Presentation (conference)

Abstract
Haptic sensation is an important modality for interacting with the real world. This paper proposes a general framework of inferring haptic forces on the surface of a 3D structure from internal deformations using a small number of physical sensors instead of employing dense sensor arrays. Using machine learning techniques, we optimize the sensor number and their placement and are able to obtain high-precision force inference for a robotic limb using as few as 9 sensors. For the optimal and sparse placement of the measurement units (strain gauges), we employ data-driven methods based on data obtained by finite element simulation. We compare data-driven approaches with model-based methods relying on geometric distance and information criteria such as Entropy and Mutual Information. We validate our approach on a modified limb of the “Poppy” robot [1] and obtain 8 mm localization precision.

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Surface structure of liquid crystals

Sattler, Alexander

Universität Stuttgart, Stuttgart, 2018 (mastersthesis)

icm

[BibTex]

[BibTex]


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Dynamics of an active particle in confined viscous flows

Pöhnl, Ruben

Universität Stuttgart, Stuttgart, 2018 (mastersthesis)

icm

[BibTex]

[BibTex]


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Electrostatic interaction between colloids with constant surface potentials at fluid interfaces

Bebon, Rick

Universität Stuttgart, Stuttgart, 2018 (mastersthesis)

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[BibTex]

[BibTex]

2013


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Brownian motion of optically trapped ellipsoids

Dibak, Manuel

Universität Stuttgart, Stuttgart, 2013 (mastersthesis)

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[BibTex]

2013


[BibTex]


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Phase behavior of colloidal suspensions with critical solvents

Mohry, T. F.

Universität Stuttgart, Stuttgart, 2013 (phdthesis)

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link (url) [BibTex]

link (url) [BibTex]


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Zweidimensionale Monte-Carlo-Gittersimulationen im muVT- und NpT-Ensemble

Kirn, Kai Ludwig

Universität Stuttgart, Stuttgart, 2013 (mastersthesis)

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[BibTex]

[BibTex]


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Permittivity of an inhomogeneous dipolar lattice fluid

Schütz, Christian

Universität Stuttgart, Stuttgart, 2013 (mastersthesis)

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[BibTex]

[BibTex]

2009


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From colloids to biophysics: applications of classical density functional theory

Roth, R.

Universität Stuttgart, Stuttgart, 2009 (phdthesis)

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[BibTex]

2009


[BibTex]


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Stäbchensuspensionen in Kontakt mit geometrisch strukturierten Substraten

Günther, F.

Universität Stuttgart, Stuttgart, 2009 (mastersthesis)

icm

[BibTex]

[BibTex]


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Critical and multicritical behavior of the +/-J Ising model in two and three dimensions

Hasenbusch, M., Parisen Toldin, F., Pelissetto, A., Vicari, E.

In Journal of Physics: Conference Series, 145, Braunschweig, 2009 (inproceedings)

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DOI [BibTex]

DOI [BibTex]

2001


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Diffusion of implanted 195Au radiotracer atoms in amorphous silicon under irradiation with 1 MeV-N+ ions

Voss, T., Scharwaechter, P., Frank, W.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, 194/199, pages: 659-665, Defect and Diffusion Forum, Scitec Publications Ltd., Paris, France, 2001 (inproceedings)

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[BibTex]

2001


[BibTex]


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Diffusion of gold in the amorphous ceramic Si28C36N36

Matics, S., Frank, W.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, 194/199, pages: 947-952, Diffusion and Defect Forum, Scitec Publications Ltd., Paris, France, 2001 (inproceedings)

icm

[BibTex]

[BibTex]


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Diffusion of gold in germanium

Strohm, A., Matics, S., Frank, W.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, 194/199, pages: 629-634, Defect and Diffusion Forum, Scitech Publ. Ltd., Paris, France, 2001 (inproceedings)

icm

[BibTex]

[BibTex]


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Einflußvon Teilchenbestrahlung auf die Selbst- und Interdiffusion in amorphen Fe-Zr-Legierungen

Schuler, T.

Universität Stuttgart, Stuttgart, 2001 (phdthesis)

icm

[BibTex]

[BibTex]


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Diffusion im unterkühlten flüssigen und amorphen Zustand von Zr65Cu175,Ni10Al17,5

Schaaff, P.

Universität Stuttgart, Stuttgart, 2001 (phdthesis)

icm

[BibTex]

[BibTex]