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2019


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Limitations of the empirical Fisher approximation for natural gradient descent

Kunstner, F., Hennig, P., Balles, L.

Advances in Neural Information Processing Systems 32, pages: 4158-4169, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (conference)

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link (url) [BibTex]

2019


link (url) [BibTex]


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Convergence Guarantees for Adaptive Bayesian Quadrature Methods

Kanagawa, M., Hennig, P.

Advances in Neural Information Processing Systems 32, pages: 6234-6245, (Editors: H. Wallach and H. Larochelle and A. Beygelzimer and F. d’Alché-Buc and E. Fox and R. Garnett), Curran Associates, Inc., 33rd Annual Conference on Neural Information Processing Systems, December 2019 (conference)

ei pn

link (url) [BibTex]

link (url) [BibTex]


A Learnable Safety Measure
A Learnable Safety Measure

Heim, S., Rohr, A. V., Trimpe, S., Badri-Spröwitz, A.

Conference on Robot Learning, November 2019 (conference) Accepted

dlg ics

Arxiv [BibTex]

Arxiv [BibTex]


Trunk Pitch Oscillations for Joint Load Redistribution in Humans and Humanoid Robots
Trunk Pitch Oscillations for Joint Load Redistribution in Humans and Humanoid Robots

Drama, Ö., Badri-Spröwitz, A.

Proceedings International Conference on Humanoid Robots, Humanoids, September 2019 (conference) Accepted

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link (url) [BibTex]

link (url) [BibTex]


Predictive Triggering for Distributed Control of Resource Constrained Multi-agent Systems
Predictive Triggering for Distributed Control of Resource Constrained Multi-agent Systems

Mastrangelo, J. M., Baumann, D., Trimpe, S.

In Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems, pages: 79-84, 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems (NecSys), September 2019 (inproceedings)

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arXiv PDF DOI [BibTex]

arXiv PDF DOI [BibTex]


The positive side of damping
The positive side of damping

Heim, S., Millard, M., Le Mouel, C., Sproewitz, A.

Proceedings of AMAM, The 9th International Symposium on Adaptive Motion of Animals and Machines, August 2019 (conference) Accepted

dlg

[BibTex]

[BibTex]


Event-triggered Pulse Control with Model Learning (if Necessary)
Event-triggered Pulse Control with Model Learning (if Necessary)

Baumann, D., Solowjow, F., Johansson, K. H., Trimpe, S.

In Proceedings of the American Control Conference, pages: 792-797, American Control Conference (ACC), July 2019 (inproceedings)

ics

arXiv PDF [BibTex]

arXiv PDF [BibTex]


Data-driven inference of passivity properties via Gaussian process optimization
Data-driven inference of passivity properties via Gaussian process optimization

Romer, A., Trimpe, S., Allgöwer, F.

In Proceedings of the European Control Conference, European Control Conference (ECC), June 2019 (inproceedings)

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PDF [BibTex]

PDF [BibTex]


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Actively Learning Gaussian Process Dynamics

Buisson-Fenet, M., Solowjow, F., Trimpe, S.

2019 (techreport) Submitted

Abstract
Despite the availability of ever more data enabled through modern sensor and computer technology, it still remains an open problem to learn dynamical systems in a sample-efficient way. We propose active learning strategies that leverage information-theoretical properties arising naturally during Gaussian process regression, while respecting constraints on the sampling process imposed by the system dynamics. Sample points are selected in regions with high uncertainty, leading to exploratory behavior and data-efficient training of the model. All results are verified in an extensive numerical benchmark.

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ArXiv [BibTex]


Trajectory-Based Off-Policy Deep Reinforcement Learning
Trajectory-Based Off-Policy Deep Reinforcement Learning

Doerr, A., Volpp, M., Toussaint, M., Trimpe, S., Daniel, C.

In Proceedings of the International Conference on Machine Learning (ICML), International Conference on Machine Learning (ICML), June 2019 (inproceedings)

Abstract
Policy gradient methods are powerful reinforcement learning algorithms and have been demonstrated to solve many complex tasks. However, these methods are also data-inefficient, afflicted with high variance gradient estimates, and frequently get stuck in local optima. This work addresses these weaknesses by combining recent improvements in the reuse of off-policy data and exploration in parameter space with deterministic behavioral policies. The resulting objective is amenable to standard neural network optimization strategies like stochastic gradient descent or stochastic gradient Hamiltonian Monte Carlo. Incorporation of previous rollouts via importance sampling greatly improves data-efficiency, whilst stochastic optimization schemes facilitate the escape from local optima. We evaluate the proposed approach on a series of continuous control benchmark tasks. The results show that the proposed algorithm is able to successfully and reliably learn solutions using fewer system interactions than standard policy gradient methods.

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arXiv PDF [BibTex]

arXiv PDF [BibTex]


A Magnetically-Actuated Untethered Jellyfish-Inspired Soft Milliswimmer
A Magnetically-Actuated Untethered Jellyfish-Inspired Soft Milliswimmer

(Best Paper Award)

Ziyu Ren, T. W., Hu, W.

RSS 2019: Robotics: Science and Systems Conference, June 2019 (conference)

pi

[BibTex]

[BibTex]


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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)

ei pn

link (url) [BibTex]

link (url) [BibTex]


Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks
Feedback Control Goes Wireless: Guaranteed Stability over Low-power Multi-hop Networks

(Best Paper Award)

Mager, F., Baumann, D., Jacob, R., Thiele, L., Trimpe, S., Zimmerling, M.

In Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems, pages: 97-108, 10th ACM/IEEE International Conference on Cyber-Physical Systems, April 2019 (inproceedings)

Abstract
Closing feedback loops fast and over long distances is key to emerging applications; for example, robot motion control and swarm coordination require update intervals below 100 ms. Low-power wireless is preferred for its flexibility, low cost, and small form factor, especially if the devices support multi-hop communication. Thus far, however, closed-loop control over multi-hop low-power wireless has only been demonstrated for update intervals on the order of multiple seconds. This paper presents a wireless embedded system that tames imperfections impairing control performance such as jitter or packet loss, and a control design that exploits the essential properties of this system to provably guarantee closed-loop stability for linear dynamic systems. Using experiments on a testbed with multiple cart-pole systems, we are the first to demonstrate the feasibility and to assess the performance of closed-loop control and coordination over multi-hop low-power wireless for update intervals from 20 ms to 50 ms.

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arXiv PDF DOI Project Page [BibTex]

arXiv PDF DOI Project Page [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)

ei pn

PDF link (url) [BibTex]

PDF link (url) [BibTex]


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


Quantifying the Robustness of Natural Dynamics: a Viability Approach
Quantifying the Robustness of Natural Dynamics: a Viability Approach

Heim, S., Sproewitz, A.

Proceedings of Dynamic Walking , Dynamic Walking , 2019 (conference) Accepted

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Submission DW2019 [BibTex]

Submission DW2019 [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]

2016


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Predictive and Self Triggering for Event-based State Estimation

Trimpe, S.

In Proceedings of the 55th IEEE Conference on Decision and Control (CDC), pages: 3098-3105, Las Vegas, NV, USA, December 2016 (inproceedings)

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arXiv PDF DOI Project Page [BibTex]

2016


arXiv PDF DOI Project Page [BibTex]


Steering control of a water-running robot using an active tail
Steering control of a water-running robot using an active tail

Kim, H., Jeong, K., Sitti, M., Seo, T.

In Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, pages: 4945-4950, October 2016 (inproceedings)

Abstract
Many highly dynamic novel mobile robots have been developed being inspired by animals. In this study, we are inspired by a basilisk lizard's ability to run and steer on water surface for a hexapedal robot. The robot has an active tail with a circular plate, which the robot rotates to steer on water. We dynamically modeled the platform and conducted simulations and experiments on steering locomotion with a bang-bang controller. The robot can steer on water by rotating the tail, and the controlled steering locomotion is stable. The dynamic modelling approximates the robot's steering locomotion and the trends of the simulations and experiments are similar, although there are errors between the desired and actual angles. The robot's maneuverability on water can be improved through further research.

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DOI [BibTex]

DOI [BibTex]


Targeting of cell mockups using sperm-shaped microrobots in vitro
Targeting of cell mockups using sperm-shaped microrobots in vitro

Khalil, I. S., Tabak, A. F., Hosney, A., Klingner, A., Shalaby, M., Abdel-Kader, R. M., Serry, M., Sitti, M.

In Biomedical Robotics and Biomechatronics (BioRob), 2016 6th IEEE International Conference on, pages: 495-501, July 2016 (inproceedings)

Abstract
Sperm-shaped microrobots are controlled under the influence of weak oscillating magnetic fields (milliTesla range) to selectively target cell mockups (i.e., gas bubbles with average diameter of 200 μm). The sperm-shaped microrobots are fabricated by electrospinning using a solution of polystyrene, dimethylformamide, and iron oxide nanoparticles. These nanoparticles are concentrated within the head of the microrobot, and hence enable directional control along external magnetic fields. The magnetic dipole moment of the microrobot is characterized (using the flip-time technique) to be 1.4×10-11 A.m2, at magnetic field of 28 mT. In addition, the morphology of the microrobot is characterized using Scanning Electron Microscopy images. The characterized parameters and morphology are used in the simulation of the locomotion mechanism of the microrobot to prove that its motion depends on breaking the time-reversal symmetry, rather than pulling with the magnetic field gradient. We experimentally demonstrate that the microrobot can controllably follow S-shaped, U-shaped, and square paths, and selectively target the cell mockups using image guidance and under the influence of the oscillating magnetic fields.

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DOI [BibTex]

DOI [BibTex]


Analysis of the magnetic torque on a tilted permanent magnet for drug delivery in capsule robots
Analysis of the magnetic torque on a tilted permanent magnet for drug delivery in capsule robots

Munoz, F., Alici, G., Zhou, H., Li, W., Sitti, M.

In Advanced Intelligent Mechatronics (AIM), 2016 IEEE International Conference on, pages: 1386-1391, July 2016 (inproceedings)

Abstract
In this paper, we present the analysis of the torque transmitted to a tilted permanent magnet that is to be embedded in a capsule robot to achieve targeted drug delivery. This analysis is carried out by using an analytical model and experimental results for a small cubic permanent magnet that is driven by an external magnetic system made of an array of arc-shaped permanent magnets (ASMs). Our experimental results, which are in agreement with the analytical results, show that the cubic permanent magnet can safely be actuated for inclinations lower than 75° without having to make positional adjustments in the external magnetic system. We have found that with further inclinations, the cubic permanent magnet to be embedded in a drug delivery mechanism may stall. When it stalls, the external magnetic system's position and orientation would have to be adjusted to actuate the cubic permanent magnet and the drug release mechanism. This analysis of the transmitted torque is helpful for the development of real-time control strategies for magnetically articulated devices.

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DOI [BibTex]

DOI [BibTex]


Robust Gaussian Filtering using a Pseudo Measurement
Robust Gaussian Filtering using a Pseudo Measurement

Wüthrich, M., Garcia Cifuentes, C., Trimpe, S., Meier, F., Bohg, J., Issac, J., Schaal, S.

In Proceedings of the American Control Conference (ACC), Boston, MA, USA, July 2016 (inproceedings)

Abstract
Most widely-used state estimation algorithms, such as the Extended Kalman Filter and the Unscented Kalman Filter, belong to the family of Gaussian Filters (GF). Unfortunately, GFs fail if the measurement process is modelled by a fat-tailed distribution. This is a severe limitation, because thin-tailed measurement models, such as the analytically-convenient and therefore widely-used Gaussian distribution, are sensitive to outliers. In this paper, we show that mapping the measurements into a specific feature space enables any existing GF algorithm to work with fat-tailed measurement models. We find a feature function which is optimal under certain conditions. Simulation results show that the proposed method allows for robust filtering in both linear and nonlinear systems with measurements contaminated by fat-tailed noise.

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Web link (url) DOI Project Page [BibTex]

Web link (url) DOI Project Page [BibTex]


Active Uncertainty Calibration in Bayesian ODE Solvers
Active Uncertainty Calibration in Bayesian ODE Solvers

Kersting, H., Hennig, P.

Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), pages: 309-318, (Editors: Ihler, A. and Janzing, D.), AUAI Press, June 2016 (conference)

Abstract
There is resurging interest, in statistics and machine learning, in solvers for ordinary differential equations (ODEs) that return probability measures instead of point estimates. Recently, Conrad et al.~introduced a sampling-based class of methods that are `well-calibrated' in a specific sense. But the computational cost of these methods is significantly above that of classic methods. On the other hand, Schober et al.~pointed out a precise connection between classic Runge-Kutta ODE solvers and Gaussian filters, which gives only a rough probabilistic calibration, but at negligible cost overhead. By formulating the solution of ODEs as approximate inference in linear Gaussian SDEs, we investigate a range of probabilistic ODE solvers, that bridge the trade-off between computational cost and probabilistic calibration, and identify the inaccurate gradient measurement as the crucial source of uncertainty. We propose the novel filtering-based method Bayesian Quadrature filtering (BQF) which uses Bayesian quadrature to actively learn the imprecision in the gradient measurement by collecting multiple gradient evaluations.

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link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


Automatic {LQR} Tuning Based on {G}aussian Process Global Optimization
Automatic LQR Tuning Based on Gaussian Process Global Optimization

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

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 270-277, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

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. Results of a two- and four- dimensional tuning problems highlight the method’s potential for automatic controller tuning on robotic platforms.

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Video PDF DOI Project Page [BibTex]

Video PDF DOI Project Page [BibTex]


Depth-based Object Tracking Using a Robust Gaussian Filter
Depth-based Object Tracking Using a Robust Gaussian Filter

Issac, J., Wüthrich, M., Garcia Cifuentes, C., Bohg, J., Trimpe, S., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2016, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

Abstract
We consider the problem of model-based 3D- tracking of objects given dense depth images as input. Two difficulties preclude the application of a standard Gaussian filter to this problem. First of all, depth sensors are characterized by fat-tailed measurement noise. To address this issue, we show how a recently published robustification method for Gaussian filters can be applied to the problem at hand. Thereby, we avoid using heuristic outlier detection methods that simply reject measurements if they do not match the model. Secondly, the computational cost of the standard Gaussian filter is prohibitive due to the high-dimensional measurement, i.e. the depth image. To address this problem, we propose an approximation to reduce the computational complexity of the filter. In quantitative experiments on real data we show how our method clearly outperforms the standard Gaussian filter. Furthermore, we compare its performance to a particle-filter-based tracking method, and observe comparable computational efficiency and improved accuracy and smoothness of the estimates.

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Video Bayesian Object Tracking Library Bayesian Filtering Framework Object Tracking Dataset link (url) DOI Project Page [BibTex]

Video Bayesian Object Tracking Library Bayesian Filtering Framework Object Tracking Dataset link (url) DOI Project Page [BibTex]


Sperm-shaped magnetic microrobots: Fabrication using electrospinning, modeling, and characterization
Sperm-shaped magnetic microrobots: Fabrication using electrospinning, modeling, and characterization

Khalil, I. S., Tabak, A. F., Hosney, A., Mohamed, A., Klingner, A., Ghoneima, M., Sitti, M.

In Robotics and Automation (ICRA), 2016 IEEE International Conference on, pages: 1939-1944, May 2016 (inproceedings)

Abstract
We use electrospinning to fabricate sperm-shaped magnetic microrobots with a range of diameters from 50 μm to 500 μm. The variables of the electrospinning operation (voltage, concentration of the solution, dynamic viscosity, and distance between the syringe needle and collector) to achieve beading effect are determined. This beading effect allows us to fabricate microrobots with similar morphology to that of sperm cells. The bead and the ultra-fine fiber resemble the morphology of the head and tail of the sperm cell, respectively. We incorporate iron oxide nanoparticles to the head of the sperm-shaped microrobot to provide a magnetic dipole moment. This dipole enables directional control under the influence of external magnetic fields. We also apply weak (less than 2 mT) oscillating magnetic fields to exert a magnetic torque on the magnetic head, and generate planar flagellar waves and flagellated swim. The average speed of the sperm-shaped microrobot is calculated to be 0.5 body lengths per second and 1 body lengths per second at frequencies of 5 Hz and 10 Hz, respectively. We also develop a model of the microrobot using elastohydrodynamics approach and Timoshenko-Rayleigh beam theory, and find good agreement with the experimental results.

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DOI [BibTex]

DOI [BibTex]


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Batch Bayesian Optimization via Local Penalization

González, J., Dai, Z., Hennig, P., Lawrence, N.

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51, pages: 648-657, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C.), May 2016 (conference)

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Communication Rate Analysis for Event-based State Estimation

(Best student paper finalist)

Ebner, S., Trimpe, S.

In Proceedings of the 13th International Workshop on Discrete Event Systems, May 2016 (inproceedings)

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PDF DOI [BibTex]

PDF DOI [BibTex]


Probabilistic Approximate Least-Squares
Probabilistic Approximate Least-Squares

Bartels, S., Hennig, P.

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51, pages: 676-684, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C. ), May 2016 (conference)

Abstract
Least-squares and kernel-ridge / Gaussian process regression are among the foundational algorithms of statistics and machine learning. Famously, the worst-case cost of exact nonparametric regression grows cubically with the data-set size; but a growing number of approximations have been developed that estimate good solutions at lower cost. These algorithms typically return point estimators, without measures of uncertainty. Leveraging recent results casting elementary linear algebra operations as probabilistic inference, we propose a new approximate method for nonparametric least-squares that affords a probabilistic uncertainty estimate over the error between the approximate and exact least-squares solution (this is not the same as the posterior variance of the associated Gaussian process regressor). This allows estimating the error of the least-squares solution on a subset of the data relative to the full-data solution. The uncertainty can be used to control the computational effort invested in the approximation. Our algorithm has linear cost in the data-set size, and a simple formal form, so that it can be implemented with a few lines of code in programming languages with linear algebra functionality.

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link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


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Supplemental material for ’Communication Rate Analysis for Event-based State Estimation’

Ebner, S., Trimpe, S.

Max Planck Institute for Intelligent Systems, January 2016 (techreport)

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PDF [BibTex]

PDF [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)

pi

[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]

2004


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E. coli inspired propulsion for swimming microrobots

Behkam, B., Sitti, M.

In ASME 2004 International Mechanical Engineering Congress and Exposition, pages: 1037-1041, 2004 (inproceedings)

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Project Page [BibTex]

2004


Project Page [BibTex]


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Dynamic modes of nanoparticle motion during nanoprobe-based manipulation

Tafazzoli, A., Sitti, M.

In Nanotechnology, 2004. 4th IEEE Conference on, pages: 35-37, 2004 (inproceedings)

pi

[BibTex]

[BibTex]


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Modeling and design of biomimetic adhesives inspired by gecko foot-hairs

Shah, G. J., Sitti, M.

In Robotics and Biomimetics, 2004. ROBIO 2004. IEEE International Conference on, pages: 873-878, 2004 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Augmented reality user interface for nanomanipulation using atomic force microscopes

Vogl, W., Sitti, M., Ehrenstrasser, M., Zäh, M.

In Proc. of Eurohaptics, pages: 413-416, 2004 (inproceedings)

pi

[BibTex]

[BibTex]


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WaalBots for Space applications

Menon, C., Murphy, M., Angrilli, F., Sitti, M.

In 55th IAC Conference, Vancouver, Canada, 2004 (inproceedings)

pi

[BibTex]

[BibTex]


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Dynamic behavior and simulation of nanoparticle sliding during nanoprobe-based positioning

Tafazzoli, A., Sitti, M.

In Proc. ASME International Mechanical Engineering Conference, 19, pages: 32, 2004 (inproceedings)

pi

[BibTex]

[BibTex]


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Three-dimensional nanoscale manipulation and manufacturing using proximal probes: controlled pulling of polymer micro/nanofibers

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

In Mechatronics, 2004. ICM’04. Proceedings of the IEEE International Conference on, pages: 224-230, 2004 (inproceedings)

pi

[BibTex]

[BibTex]


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Micro-and nano-scale robotics

Sitti, M.

In American Control Conference, 2004. Proceedings of the 2004, 1, pages: 1-8, 2004 (inproceedings)

pi

[BibTex]

[BibTex]


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Gecko inspired surface climbing robots

Menon, C., Murphy, M., Sitti, M.

In Robotics and Biomimetics, 2004. ROBIO 2004. IEEE International Conference on, pages: 431-436, 2004 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]