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2019


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DeepOBS: A Deep Learning Optimizer Benchmark Suite

Schneider, F., Balles, L., Hennig, P.

7th International Conference on Learning Representations (ICLR), May 2019 (conference)

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link (url) [BibTex]

2019


link (url) [BibTex]


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Fast and Robust Shortest Paths on Manifolds Learned from Data

Arvanitidis, G., Hauberg, S., Hennig, P., Schober, M.

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89, pages: 1506-1515, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)

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PDF link (url) [BibTex]

PDF link (url) [BibTex]


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Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization

de Roos, F., Hennig, P.

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), 89, pages: 1448-1457, (Editors: Kamalika Chaudhuri and Masashi Sugiyama), PMLR, April 2019 (conference)

Abstract
Pre-conditioning is a well-known concept that can significantly improve the convergence of optimization algorithms. For noise-free problems, where good pre-conditioners are not known a priori, iterative linear algebra methods offer one way to efficiently construct them. For the stochastic optimization problems that dominate contemporary machine learning, however, this approach is not readily available. We propose an iterative algorithm inspired by classic iterative linear solvers that uses a probabilistic model to actively infer a pre-conditioner in situations where Hessian-projections can only be constructed with strong Gaussian noise. The algorithm is empirically demonstrated to efficiently construct effective pre-conditioners for stochastic gradient descent and its variants. Experiments on problems of comparably low dimensionality show improved convergence. In very high-dimensional problems, such as those encountered in deep learning, the pre-conditioner effectively becomes an automatic learning-rate adaptation scheme, which we also empirically show to work well.

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PDF link (url) [BibTex]

PDF link (url) [BibTex]


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Elastic modulus affects adhesive strength of gecko-inspired synthetics in variable temperature and humidity

Mitchell, CT, Drotlef, D, Dayan, CB, Sitti, M, Stark, AY

In INTEGRATIVE AND COMPARATIVE BIOLOGY, pages: E372-E372, OXFORD UNIV PRESS INC JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA, March 2019 (inproceedings)

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[BibTex]

[BibTex]


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X-ray Optics Fabrication Using Unorthodox Approaches

Sanli, U., Baluktsian, M., Ceylan, H., Sitti, M., Weigand, M., Schütz, G., Keskinbora, K.

Bulletin of the American Physical Society, APS, 2019 (article)

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[BibTex]

[BibTex]


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Microrobotics and Microorganisms: Biohybrid Autonomous Cellular Robots

Alapan, Y., Yasa, O., Yigit, B., Yasa, I. C., Erkoc, P., Sitti, M.

Annual Review of Control, Robotics, and Autonomous Systems, 2019 (article)

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[BibTex]

[BibTex]


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Tailored Magnetic Springs for Shape-Memory Alloy Actuated Mechanisms in Miniature Robots

Woodward, M. A., Sitti, M.

IEEE Transactions on Robotics, 35, 2019 (article)

Abstract
Animals can incorporate large numbers of actuators because of the characteristics of muscles; whereas, robots cannot, as typical motors tend to be large, heavy, and inefficient. However, shape-memory alloys (SMA), materials that contract during heating because of change in their crystal structure, provide another option. SMA, though, is unidirectional and therefore requires an additional force to reset (extend) the actuator, which is typically provided by springs or antagonistic actuation. These strategies, however, tend to limit the actuator's work output and functionality as their force-displacement relationships typically produce increasing resistive force with limited variability. In contrast, magnetic springs-composed of permanent magnets, where the interaction force between magnets mimics a spring force-have much more variable force-displacement relationships and scale well with SMA. However, as of yet, no method for designing magnetic springs for SMA-actuators has been demonstrated. Therefore, in this paper, we present a new methodology to tailor magnetic springs to the characteristics of these actuators, with experimental results both for the device and robot-integrated SMA-actuators. We found magnetic building blocks, based on sets of permanent magnets, which are well-suited to SMAs and have the potential to incorporate features such as holding force, state transitioning, friction minimization, auto-alignment, and self-mounting. We show magnetic springs that vary by more than 3 N in 750 $\mu$m and two SMA-actuated devices that allow the MultiMo-Bat to reach heights of up to 4.5 m without, and 3.6 m with, integrated gliding airfoils. Our results demonstrate the potential of this methodology to add previously impossible functionality to smart material actuators. We anticipate this methodology will inspire broader consideration of the use of magnetic springs in miniature robots and further study of the potential of tailored magnetic springs throughout mechanical systems.

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DOI [BibTex]


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Magnetically Actuated Soft Capsule Endoscope for Fine-Needle Biopsy

Son, D., Gilbert, H., Sitti, M.

Soft robotics, Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New …, 2019 (article)

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[BibTex]

[BibTex]


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Thrust and Hydrodynamic Efficiency of the Bundled Flagella

Danis, U., Rasooli, R., Chen, C., Dur, O., Sitti, M., Pekkan, K.

Micromachines, 10, 2019 (article)

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[BibTex]

[BibTex]


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The near and far of a pair of magnetic capillary disks

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

Soft Matter, 2019 (article)

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[BibTex]

[BibTex]


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Multifarious Transit Gates for Programmable Delivery of Bio‐functionalized Matters

Hu, X., Torati, S. R., Kim, H., Yoon, J., Lim, B., Kim, K., Sitti, M., Kim, C.

Small, Wiley Online Library, 2019 (article)

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[BibTex]

[BibTex]


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Multi-functional soft-bodied jellyfish-like swimming

Ren, Z., Hu, W., Dong, X., Sitti, M.

Nature communications, 10, 2019 (article)

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[BibTex]


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Welcome to Progress in Biomedical Engineering

Sitti, M.

Progress in Biomedical Engineering, 1, IOP Publishing, 2019 (article)

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[BibTex]

[BibTex]


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Mechanics of a pressure-controlled adhesive membrane for soft robotic gripping on curved surfaces

Song, S., Drotlef, D., Paik, J., Majidi, C., Sitti, M.

Extreme Mechanics Letters, Elsevier, 2019 (article)

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[BibTex]


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Graphene oxide synergistically enhances antibiotic efficacy in Vancomycin resistance Staphylococcus aureus

Singh, V., Kumar, V., Kashyap, S., Singh, A. V., Kishore, V., Sitti, M., Saxena, P. S., Srivastava, A.

ACS Applied Bio Materials, ACS Publications, 2019 (article)

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[BibTex]

[BibTex]


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Review of emerging concepts in nanotoxicology: opportunities and challenges for safer nanomaterial design

Singh, A. V., Laux, P., Luch, A., Sudrik, C., Wiehr, S., Wild, A., Santamauro, G., Bill, J., Sitti, M.

Toxicology Mechanisms and Methods, 2019 (article)

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[BibTex]

[BibTex]


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Multifunctional and biodegradable self-propelled protein motors

Pena-Francesch, A., Giltinan, J., Sitti, M.

Nature communications, 10, Nature Publishing Group, 2019 (article)

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[BibTex]

[BibTex]


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Cohesive self-organization of mobile microrobotic swarms

Yigit, B., Alapan, Y., Sitti, M.

arXiv preprint arXiv:1907.05856, 2019 (article)

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[BibTex]

[BibTex]


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Mobile microrobots for active therapeutic delivery

Erkoc, P., Yasa, I. C., Ceylan, H., Yasa, O., Alapan, Y., Sitti, M.

Advanced Therapeutics, Wiley Online Library, 2019 (article)

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[BibTex]

[BibTex]


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Shape-encoded dynamic assembly of mobile micromachines

Alapan, Y., Yigit, B., Beker, O., Demirörs, A. F., Sitti, M.

Nature, 18, 2019 (article)

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[BibTex]

[BibTex]


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Microfluidics Integrated Lithography‐Free Nanophotonic Biosensor for the Detection of Small Molecules

Sreekanth, K. V., Sreejith, S., Alapan, Y., Sitti, M., Lim, C. T., Singh, R.

Advanced Optical Materials, 2019 (article)

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[BibTex]

[BibTex]


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Gecko-inspired composite microfibers for reversible adhesion on smooth and rough surfaces

Drotlef, D., Dayan, C., Sitti, M.

In INTEGRATIVE AND COMPARATIVE BIOLOGY, pages: E58-E58, OXFORD UNIV PRESS INC JOURNALS DEPT, 2001 EVANS RD, CARY, NC 27513 USA, 2019 (inproceedings)

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[BibTex]

[BibTex]


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ENGINEERING Bio-inspired robotic collectives

Sitti, M.

Nature, 567, pages: 314-315, Macmillan Publishers Ltd., London, England, 2019 (article)

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[BibTex]

[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, 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 [BibTex]

https://arxiv.org/abs/1907.04616 [BibTex]


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Peptide-Induced Biomineralization of Tin Oxide (SnO2) Nanoparticles for Antibacterial Applications

Singh, A. V., Jahnke, T., Xiao, Y., Wang, S., Yu, Y., David, H., Richter, G., Laux, P., Luch, A., Srivastava, A., Saxena, P. S., Bill, J., Sitti, M.

Journal of nanoscience and nanotechnology, 19, American Scientific Publishers, 2019 (article)

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[BibTex]

[BibTex]


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Electromechanical actuation of dielectric liquid crystal elastomers for soft robotics

Davidson, Z., Shahsavan, H., Guo, Y., Hines, L., Xia, Y., Yang, S., Sitti, M.

Bulletin of the American Physical Society, APS, 2019 (article)

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[BibTex]

[BibTex]


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Probabilistic Linear Solvers: A Unifying View

Bartels, S., Cockayne, J., Ipsen, I. C. F., Hennig, P.

Statistics and Computing, 2019 (article) Accepted

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link (url) [BibTex]

link (url) [BibTex]


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Learning to Navigate Endoscopic Capsule Robots

Turan, M., Almalioglu, Y., Gilbert, H. B., Mahmood, F., Durr, N. J., Araujo, H., Sarı, A. E., Ajay, A., Sitti, M.

IEEE Robotics and Automation Letters, 4, 2019 (article)

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[BibTex]

[BibTex]