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2019


Learning to Explore in Motion and Interaction Tasks
Learning to Explore in Motion and Interaction Tasks

Bogdanovic, M., Righetti, L.

Proceedings 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages: 2686-2692, IEEE, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019, ISSN: 2153-0866 (conference)

Abstract
Model free reinforcement learning suffers from the high sampling complexity inherent to robotic manipulation or locomotion tasks. Most successful approaches typically use random sampling strategies which leads to slow policy convergence. In this paper we present a novel approach for efficient exploration that leverages previously learned tasks. We exploit the fact that the same system is used across many tasks and build a generative model for exploration based on data from previously solved tasks to improve learning new tasks. The approach also enables continuous learning of improved exploration strategies as novel tasks are learned. Extensive simulations on a robot manipulator performing a variety of motion and contact interaction tasks demonstrate the capabilities of the approach. In particular, our experiments suggest that the exploration strategy can more than double learning speed, especially when rewards are sparse. Moreover, the algorithm is robust to task variations and parameter tuning, making it beneficial for complex robotic problems.

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DOI [BibTex]

2019


DOI [BibTex]


EM-Fusion: Dynamic Object-Level SLAM With Probabilistic Data Association
EM-Fusion: Dynamic Object-Level SLAM With Probabilistic Data Association

Strecke, M., Stückler, J.

Proceedings International Conference on Computer Vision 2019 (ICCV), pages: 5864-5873, IEEE, 2019 IEEE/CVF International Conference on Computer Vision (ICCV), October 2019 (conference)

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preprint Project page Poster DOI [BibTex]

preprint Project page Poster DOI [BibTex]


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Robust Humanoid Locomotion Using Trajectory Optimization and Sample-Efficient Learning

Yeganegi, M. H., Khadiv, M., Moosavian, S. A. A., Zhu, J., Prete, A. D., Righetti, L.

Proceedings International Conference on Humanoid Robots, IEEE, 2019 IEEE-RAS International Conference on Humanoid Robots, October 2019 (conference)

Abstract
Trajectory optimization (TO) is one of the most powerful tools for generating feasible motions for humanoid robots. However, including uncertainties and stochasticity in the TO problem to generate robust motions can easily lead to intractable problems. Furthermore, since the models used in TO have always some level of abstraction, it can be hard to find a realistic set of uncertainties in the model space. In this paper we leverage a sample-efficient learning technique (Bayesian optimization) to robustify TO for humanoid locomotion. The main idea is to use data from full-body simulations to make the TO stage robust by tuning the cost weights. To this end, we split the TO problem into two phases. The first phase solves a convex optimization problem for generating center of mass (CoM) trajectories based on simplified linear dynamics. The second stage employs iterative Linear-Quadratic Gaussian (iLQG) as a whole-body controller to generate full body control inputs. Then we use Bayesian optimization to find the cost weights to use in the first stage that yields robust performance in the simulation/experiment, in the presence of different disturbance/uncertainties. The results show that the proposed approach is able to generate robust motions for different sets of disturbances and uncertainties.

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https://arxiv.org/abs/1907.04616 link (url) [BibTex]

https://arxiv.org/abs/1907.04616 link (url) [BibTex]


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Learning to Disentangle Latent Physical Factors for Video Prediction

Zhu, D., Munderloh, M., Rosenhahn, B., Stückler, J.

In Pattern Recognition - Proceedings German Conference on Pattern Recognition (GCPR), Springer International, German Conference on Pattern Recognition (GCPR), September 2019 (inproceedings)

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dataset & evaluation code video preprint DOI [BibTex]

dataset & evaluation code video preprint DOI [BibTex]


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3D Birds-Eye-View Instance Segmentation

Elich, C., Engelmann, F., Kontogianni, T., Leibe, B.

In Pattern Recognition - Proceedings 41st DAGM German Conference, DAGM GCPR 2019, pages: 48-61, Lecture Notes in Computer Science (LNCS) 11824, (Editors: Fink G.A., Frintrop S., Jiang X.), Springer, 2019 German Conference on Pattern Recognition (GCPR), September 2019, ISSN: 03029743 (inproceedings)

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[BibTex]

[BibTex]


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Efficient Humanoid Contact Planning using Learned Centroidal Dynamics Prediction

Lin, Y., Ponton, B., Righetti, L., Berenson, D.

International Conference on Robotics and Automation (ICRA), pages: 5280-5286, IEEE, May 2019 (conference)

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DOI [BibTex]

DOI [BibTex]


Leveraging Contact Forces for Learning to Grasp
Leveraging Contact Forces for Learning to Grasp

Merzic, H., Bogdanovic, M., Kappler, D., Righetti, L., Bohg, J.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2019, IEEE, International Conference on Robotics and Automation, May 2019 (inproceedings)

Abstract
Grasping objects under uncertainty remains an open problem in robotics research. This uncertainty is often due to noisy or partial observations of the object pose or shape. To enable a robot to react appropriately to unforeseen effects, it is crucial that it continuously takes sensor feedback into account. While visual feedback is important for inferring a grasp pose and reaching for an object, contact feedback offers valuable information during manipulation and grasp acquisition. In this paper, we use model-free deep reinforcement learning to synthesize control policies that exploit contact sensing to generate robust grasping under uncertainty. We demonstrate our approach on a multi-fingered hand that exhibits more complex finger coordination than the commonly used two- fingered grippers. We conduct extensive experiments in order to assess the performance of the learned policies, with and without contact sensing. While it is possible to learn grasping policies without contact sensing, our results suggest that contact feedback allows for a significant improvement of grasping robustness under object pose uncertainty and for objects with a complex shape.

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video arXiv [BibTex]

video arXiv [BibTex]


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Response of active Brownian particles to shear flow

Asheichyk, K., Solon, A., Rohwer, C. M., Krüger, M.

The Journal of Chemical Physics, 150(14), American Institute of Physics, Woodbury, N.Y., 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Vortex Mass in the Three-Dimensional O(2) Scalar Theory

Delfino, G., Selke, W., Squarcini, A.

Physical Review Letters, 122(5), American Physical Society, Woodbury, N.Y., 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Ferromagnetic colloids in liquid crystal solvents

Zarubin, G.

Universität Stuttgart, Stuttgart, 2019 (phdthesis)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Fluctuating interface with a pinning potential

Pranjić, Daniel

Universität Stuttgart, Stuttgart, 2019 (mastersthesis)

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[BibTex]

[BibTex]


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Dynamics near planar walls for various model self-phoretic particles

Bayati, P., Popescu, M. N., Uspal, W. E., Dietrich, S., Najafi, A.

Soft Matter, 15(28):5644-5672, Royal Society of Chemistry, Cambridge, UK, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Glucose Oxidase Micropumps: Multi-Faceted Effects of Chemical Activity on Tracer Particles Near the Solid-Liquid Interface

Munteanu, R. E., Popescu, M. N., Gáspár, S.

Condensed Matter, 4(3), MDPI, Basel, 2019 (article)

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DOI [BibTex]


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Criticality senses topology

Vasilyev, O. A., Maciolek, A., Dietrich, S.

EPL, 128(2), EDP Science, Les-Ulis, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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A Robustness Analysis of Inverse Optimal Control of Bipedal Walking

Rebula, J. R., Schaal, S., Finley, J., Righetti, L.

IEEE Robotics and Automation Letters, 4(4):4531-4538, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Drag Force for Asymmetrically Grafted Colloids in Polymer Solutions

Werner, M., Malgaretti, P., Maciolek, A.

Frontiers in Physics, 7, Frontiers Media, Lausanne, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Feeling Your Neighbors across the Walls: How Interpore Ionic Interactions Affect Capacitive Energy Storage

Kondrat, S., Vasilyev, O., Kornyshev, A. A.

The Journal of Physical Chemistry Letters, 10(16):4523-4527, American Chemical Society, Washington, DC, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Active Janus colloids at chemically structured surfaces

Uspal, W. E., Popescu, M. N., Dietrich, S., Tasinkevych, M.

The Journal of Chemical Physics, 150(20), American Institute of Physics, Woodbury, N.Y., 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Illumination-induced motion of a Janus nanoparticle in binary solvents

Araki, T., Maciolek, A.

Soft Matter, 15(26):5243-5254, Royal Society of Chemistry, Cambridge, UK, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Transient response of an electrolyte to a thermal quench

Janssen, M., Bier, M.

Physical Review E, 99(4), American Physical Society, Melville, NY, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Rigid vs compliant contact: an experimental study on biped walking

Khadiv, M., Moosavian, S. A. A., Yousefi-Koma, A., Sadedel, M., Ehsani-Seresht, A., Mansouri, S.

Multibody System Dynamics, 45(4):379-401, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Aging phenomena during phase separation in fluids: decay of autocorrelation for vapor\textendashliquid transitions

Roy, Sutapa, Bera, Arabinda, Majumder, Suman, Das, Subir K.

Soft Matter, 15(23):4743-4750, Royal Society of Chemistry, Cambridge, UK, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Controlling pattern formation in the confined Schnakenberg model

Beyer, David Bernhard

Universität Stuttgart, Stuttgart, 2019 (mastersthesis)

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[BibTex]

[BibTex]


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Flux and storage of energy in nonequilibrium stationary states

Holyst, R., Maciolek, A., Zhang, Y., Litniewski, M., Knycha\la, P., Kasprzak, M., Banaszak, M.

Physical Review E, 99(4), American Physical Society, Melville, NY, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Correlations and forces in sheared fluids with or without quenching

Rohwer, C. M., Maciolek, A., Dietrich, S., Krüger, M.

New Journal of Physics, 21, IOP Publishing, Bristol, 2019 (article)

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DOI [BibTex]


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Ensemble dependence of critical Casimir forces in films with Dirichlet boundary conditions

Rohwer, C. M., Squarcini, A., Vasilyev, O., Dietrich, S., Gross, M.

Physical Review E, 99(6), American Physical Society, Melville, NY, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Controlling the dynamics of colloidal particles by critical Casimir forces

Magazzù, A., Callegari, A., Staforelli, J. P., Gambassi, A., Dietrich, S., Volpe, G.

Soft Matter, 15(10):2152-2162, Royal Society of Chemistry, Cambridge, UK, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Charge regulation radically modifies electrostatics in membrane stacks

Majee, A., Bier, M., Blossey, R., Podgornik, R.

Physical Review E, 100(5), American Physical Society, Melville, NY, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Comment on "Which interactions dominate in active colloids?" [J. Chem. Phys. 150, 061102 (2019)]

Popescu, M. N., Dominguez, A., Uspal, W. E., Tasinkevych, M., Dietrich, S.

The Journal of Chemical Physics, 151(6), American Institute of Physics, Woodbury, N.Y., 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Current-mediated synchronization of a pair of beating non-identical flagella

Dotsenko, V., Maciolek, A., Oshanin, G., Vasilyev, O., Dietrich, S.

New Journal of Physics, 21, IOP Publishing, Bristol, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Driving an electrolyte through a corrugated nanopore

Malgaretti, P., Janssen, M., Pagonabarraga, I., Rubi, J. M.

The Journal of Chemical Physics, 151(8), American Institute of Physics, Woodbury, N.Y., 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Interfaces in fluids of ionic liquid crystals

Bartsch, H.

Universität Stuttgart, Stuttgart, 2019 (phdthesis)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Spectral Content of a Single Non-Brownian Trajectory

Krapf, D., Lukat, N., Marinari, E., Metzler, R., Oshanin, G., Selhuber-Unkel, C., Squarcini, A., Stadler, L., Weiss, M., Xu, X.

Physical Review X, 9(1), American Physical Society, New York, NY, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Special issue on transport in narrow channels
Journal of Physics: Condensed Matter, 31, IOP Publishing, Bristol, 2019 (misc)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Curvature affects electrolyte relaxation: Studies of spherical and cylindrical electrodes

Janssen, M.

Physical Review E, 100(4), American Physical Society, Melville, NY, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Birch tar production does not prove Neanderthal behavioral complexity

Schmidt, P., Blessing, M., Rageot, M., Iovita, R., Pfleging, J., Nickel, K. G., Righetti, L., Tennie, C.

Proceedings of the National Academy of Sciences (PNAS), 116(36):17707-17711, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Dynamics of the critical Casimir force for a conserved order parameter after a critical quench

Gross, M., Rohwer, C. M., Dietrich, S.

Physical Review E, 100(1), American Physical Society, Melville, NY, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Interface structures in ionic liquid crystals

Bartsch, H., Bier, M., Dietrich, S.

Soft Matter, 15(20):4109-4126, Royal Society of Chemistry, Cambridge, UK, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Interfacial premelting of ice in nano composite materials

Li, H., Bier, M., Mars, J., Weiss, H., Dippel, A., Gutowski, O., Honkimäki, V., Mezger, M.

Physical Chemistry Chemical Physics, 21(7):3734-3741, Royal Society of Chemistry, Cambridge, England, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Connections Matter: On the Importance of Pore Percolation for Nanoporous Supercapacitors

Vasilyev, O., Kornyshev, A. A., Kondrat, S.

ACS Applied Energy Materials, 2(8):5386-5390, American Chemical Society, Washington, DC, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Theory of light-activated catalytic Janus particles

Uspal, W. E.

The Journal of Chemical Physics, 150(11), American Institute of Physics, Woodbury, N.Y., 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Recovering superhydrophobicity in nanoscale and macroscale surface textures

Giacomello, A., Schimmele, L., Dietrich, S., Tasinkevych, M.

Soft Matter, 15(37):7462-7471, Royal Society of Chemistry, Cambridge, UK, 2019 (article)

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DOI [BibTex]

DOI [BibTex]


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Brownian dynamics assessment of enhanced diffusion exhibited by "fluctuating-dumbbell enzymes".

Kondrat, S., Popescu, M. N.

Physical Chemistry Chemical Physics, 21(35):18811-18815, Royal Society of Chemistry, Cambridge, England, 2019 (article)

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DOI [BibTex]

DOI [BibTex]

2018


Robust Physics-based Motion Retargeting with Realistic Body Shapes
Robust Physics-based Motion Retargeting with Realistic Body Shapes

Borno, M. A., Righetti, L., Black, M. J., Delp, S. L., Fiume, E., Romero, J.

Computer Graphics Forum, 37, pages: 6:1-12, July 2018 (article)

Abstract
Motion capture is often retargeted to new, and sometimes drastically different, characters. When the characters take on realistic human shapes, however, we become more sensitive to the motion looking right. This means adapting it to be consistent with the physical constraints imposed by different body shapes. We show how to take realistic 3D human shapes, approximate them using a simplified representation, and animate them so that they move realistically using physically-based retargeting. We develop a novel spacetime optimization approach that learns and robustly adapts physical controllers to new bodies and constraints. The approach automatically adapts the motion of the mocap subject to the body shape of a target subject. This motion respects the physical properties of the new body and every body shape results in a different and appropriate movement. This makes it easy to create a varied set of motions from a single mocap sequence by simply varying the characters. In an interactive environment, successful retargeting requires adapting the motion to unexpected external forces. We achieve robustness to such forces using a novel LQR-tree formulation. We show that the simulated motions look appropriate to each character’s anatomy and their actions are robust to perturbations.

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pdf video Project Page Project Page [BibTex]

2018


pdf video Project Page Project Page [BibTex]


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Detailed Dense Inference with Convolutional Neural Networks via Discrete Wavelet Transform

Ma, L., Stueckler, J., Wu, T., Cremers, D.

arxiv, 2018, arXiv:1808.01834 (techreport)

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[BibTex]

[BibTex]


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On Time Optimization of Centroidal Momentum Dynamics

Ponton, B., Herzog, A., Del Prete, A., Schaal, S., Righetti, L.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 5776-5782, IEEE, Brisbane, Australia, 2018 (inproceedings)

Abstract
Recently, the centroidal momentum dynamics has received substantial attention to plan dynamically consistent motions for robots with arms and legs in multi-contact scenarios. However, it is also non convex which renders any optimization approach difficult and timing is usually kept fixed in most trajectory optimization techniques to not introduce additional non convexities to the problem. But this can limit the versatility of the algorithms. In our previous work, we proposed a convex relaxation of the problem that allowed to efficiently compute momentum trajectories and contact forces. However, our approach could not minimize a desired angular momentum objective which seriously limited its applicability. Noticing that the non-convexity introduced by the time variables is of similar nature as the centroidal dynamics one, we propose two convex relaxations to the problem based on trust regions and soft constraints. The resulting approaches can compute time-optimized dynamically consistent trajectories sufficiently fast to make the approach realtime capable. The performance of the algorithm is demonstrated in several multi-contact scenarios for a humanoid robot. In particular, we show that the proposed convex relaxation of the original problem finds solutions that are consistent with the original non-convex problem and illustrate how timing optimization allows to find motion plans that would be difficult to plan with fixed timing † †Implementation details and demos can be found in the source code available at https://git-amd.tuebingen.mpg.de/bponton/timeoptimization.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Numerical Quadrature for Probabilistic Policy Search

Vinogradska, J., Bischoff, B., Achterhold, J., Koller, T., Peters, J.

IEEE Transactions on Pattern Analysis and Machine Intelligence, pages: 1-1, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Active microrheology in corrugated channels

Puertas, A. M., Malgaretti, P., Pagonabarraga, I.

The Journal of Chemical Physics, 149(17), American Institute of Physics, Woodbury, N.Y., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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First-passage dynamics of linear stochastic interface models: weak-noise theory and influence of boundary conditions

Gross, M.

Journal of Statistical Mechanics: Theory and Experiment, 2018, Institute of Physics Publishing, Bristol, England, 2018 (article)

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DOI [BibTex]

DOI [BibTex]