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2013


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3-D Object Reconstruction of Symmetric Objects by Fusing Visual and Tactile Sensing

Illonen, J., Bohg, J., Kyrki, V.

The International Journal of Robotics Research, 33(2):321-341, Sage, October 2013 (article)

Abstract
In this work, we propose to reconstruct a complete 3-D model of an unknown object by fusion of visual and tactile information while the object is grasped. Assuming the object is symmetric, a first hypothesis of its complete 3-D shape is generated. A grasp is executed on the object with a robotic manipulator equipped with tactile sensors. Given the detected contacts between the fingers and the object, the initial full object model including the symmetry parameters can be refined. This refined model will then allow the planning of more complex manipulation tasks. The main contribution of this work is an optimal estimation approach for the fusion of visual and tactile data applying the constraint of object symmetry. The fusion is formulated as a state estimation problem and solved with an iterative extended Kalman filter. The approach is validated experimentally using both artificial and real data from two different robotic platforms.

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Web DOI Project Page [BibTex]

2013


Web DOI Project Page [BibTex]


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Quasi-Newton Methods: A New Direction

Hennig, P., Kiefel, M.

Journal of Machine Learning Research, 14(1):843-865, March 2013 (article)

Abstract
Four decades after their invention, quasi-Newton methods are still state of the art in unconstrained numerical optimization. Although not usually interpreted thus, these are learning algorithms that fit a local quadratic approximation to the objective function. We show that many, including the most popular, quasi-Newton methods can be interpreted as approximations of Bayesian linear regression under varying prior assumptions. This new notion elucidates some shortcomings of classical algorithms, and lights the way to a novel nonparametric quasi-Newton method, which is able to make more efficient use of available information at computational cost similar to its predecessors.

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website+code pdf link (url) [BibTex]

website+code pdf link (url) [BibTex]


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The Randomized Dependence Coefficient

Lopez-Paz, D., Hennig, P., Schölkopf, B.

Neural Information Processing Systems (NIPS), 2013 (poster)

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PDF [BibTex]

PDF [BibTex]


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Analytical probabilistic modeling for radiation therapy treatment planning

Bangert, M., Hennig, P., Oelfke, U.

Physics in Medicine and Biology, 58(16):5401-5419, 2013 (article)

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PDF DOI [BibTex]

PDF DOI [BibTex]


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Optimal control of reaching includes kinematic constraints

Mistry, M., Theodorou, E., Schaal, S., Kawato, M.

Journal of Neurophysiology, 2013, clmc (article)

Abstract
We investigate adaptation under a reaching task with an acceleration-based force field perturbation designed to alter the nominal straight hand trajectory in a potentially benign manner:pushing the hand of course in one direction before subsequently restoring towards the target. In this particular task, an explicit strategy to reduce motor effort requires a distinct deviation from the nominal rectilinear hand trajectory. Rather, our results display a clear directional preference during learning, as subjects adapted perturbed curved trajectories towards their initial baselines. We model this behavior using the framework of stochastic optimal control theory and an objective function that trades-of the discordant requirements of 1) target accuracy, 2) motor effort, and 3) desired trajectory. Our work addresses the underlying objective of a reaching movement, and we suggest that robustness, particularly against internal model uncertainly, is as essential to the reaching task as terminal accuracy and energy effciency.

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PDF [BibTex]

PDF [BibTex]


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Dynamical Movement Primitives: Learning Attractor Models for Motor Behaviors

Ijspeert, A., Nakanishi, J., Pastor, P., Hoffmann, H., Schaal, S.

Neural Computation, (25):328-373, 2013, clmc (article)

Abstract
Nonlinear dynamical systems have been used in many disciplines to model complex behaviors, including biological motor control, robotics, perception, economics, traffic prediction, and neuroscience. While often the unexpected emergent behavior of nonlinear systems is the focus of investigations, it is of equal importance to create goal-directed behavior (e.g., stable locomotion from a system of coupled oscillators under perceptual guidance). Modeling goal-directed behavior with nonlinear systems is, however, rather difficult due to the parameter sensitivity of these systems, their complex phase transitions in response to subtle parameter changes, and the difficulty of analyzing and predicting their long-term behavior; intuition and time-consuming parameter tuning play a major role. This letter presents and reviews dynamical movement primitives, a line of research for modeling attractor behaviors of autonomous nonlinear dynamical systems with the help of statistical learning techniques. The essence of our approach is to start with a simple dynamical system, such as a set of linear differential equations, and transform those into a weakly nonlinear system with prescribed attractor dynamics by meansof a learnable autonomous forcing term. Both point attractors and limit cycle attractors of almost arbitrary complexity can be generated. We explain the design principle of our approach and evaluate its properties in several example applications in motor control and robotics.

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link (url) [BibTex]

link (url) [BibTex]


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Two-dimensional magnetic micro-module reconfigurations based on inter-modular interactions

Miyashita, S., Diller, E., Sitti, M.

The International Journal of Robotics Research, 32(5):591-613, SAGE Publications Sage UK: London, England, 2013 (article)

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[BibTex]

[BibTex]


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Contact compliance effects in the frictional response of bioinspired fibrillar adhesives

Piccardo, M., Chateauminois, A., Fretigny, C., Pugno, N. M., Sitti, M.

Journal of The Royal Society Interface, 10(83):20130182, The Royal Society, 2013 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Co-chairs

VINCENT, Julian, ZHU, Di, DAI, Zhendong, CHEN, Da, JIANG, Lei, KANG, Le, REN, Luquan, XUE, Qunji, Zhao, Chunsheng, BARNES, Jon, others

2013 (article)

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[BibTex]

[BibTex]


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Topological Control of Cell Sheet Migration by the 3D Microenvironment

Song, J., Kim, Y. T., Hazar, M., LeDuc, P. R., Davidson, L. A., Sitti, M.

Biophysical Journal, 104(2):147a, Elsevier, 2013 (article)

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[BibTex]

[BibTex]


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Independent control of multiple magnetic microrobots in three dimensions

Diller, E., Giltinan, J., Sitti, M.

The International Journal of Robotics Research, 32(5):614-631, SAGE Publications Sage UK: London, England, 2013 (article)

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[BibTex]

[BibTex]


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Modular micro-robotic assembly through magnetic actuation and thermal bonding

Diller, E., Zhang, N., Sitti, M.

Journal of Micro-Bio Robotics, 8(3-4):121-131, Springer Berlin Heidelberg, 2013 (article)

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[BibTex]

[BibTex]


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A simulation and design tool for a passive rotation flapping wing mechanism

Arabagi, V., Hines, L., Sitti, M.

IEEE/ASME Transactions on Mechatronics, 18(2):787-798, 2013 (article)

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Project Page [BibTex]

Project Page [BibTex]


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GECKO-INSPIRED POLYMER ADHESIVES

Menguc, Yigit, Metin, Metin

Polymer Adhesion, Friction, and Lubrication, pages: 351, Wiley, 2013 (article)

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[BibTex]

[BibTex]


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Near and far-wall effects on the three-dimensional motion of bacteria-driven microbeads

Edwards, M. R., Wright Carlsen, R., Sitti, M.

Applied Physics Letters, 102(14):143701, AIP, 2013 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Magnetically Actuated Soft Capsule With the Multimodal Drug Release Function

Yim, S., Goyal, K., Sitti, M.

IEEE/ASME Trans. on Mechatronics, 18(4):1413-1418, IEEE, 2013 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Optimal distribution of contact forces with inverse-dynamics control

Righetti, L., Buchli, J., Mistry, M., Kalakrishnan, M., Schaal, S.

The International Journal of Robotics Research, 32(3):280-298, March 2013 (article)

Abstract
The development of legged robots for complex environments requires controllers that guarantee both high tracking performance and compliance with the environment. More specifically the control of the contact interaction with the environment is of crucial importance to ensure stable, robust and safe motions. In this contribution we develop an inverse-dynamics controller for floating-base robots under contact constraints that can minimize any combination of linear and quadratic costs in the contact constraints and the commands. Our main result is the exact analytical derivation of the controller. Such a result is particularly relevant for legged robots as it allows us to use torque redundancy to directly optimize contact interactions. For example, given a desired locomotion behavior, we can guarantee the minimization of contact forces to reduce slipping on difficult terrains while ensuring high tracking performance of the desired motion. The main advantages of the controller are its simplicity, computational efficiency and robustness to model inaccuracies. We present detailed experimental results on simulated humanoid and quadruped robots as well as a real quadruped robot. The experiments demonstrate that the controller can greatly improve the robustness of locomotion of the robots.1

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Tank-like module-based climbing robot using passive compliant joints

Seo, T., Sitti, M.

IEEE/ASME Transactions on Mechatronics, 18(1):397-408, 2013 (article)

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[BibTex]

[BibTex]


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Enhanced fabrication and characterization of gecko-inspired mushroom-tipped microfiber adhesives

Song, J., Mengüç, Y., Sitti, M.

Journal of Adhesion Science and Technology, 27(17):1921-1932, Routledge, 2013 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Micro-scale mobile robotics

Diller, E., Sitti, M.

Foundations and Trends in Robotics, 2(3):143-259, Now Publishers Incorporated, 2013 (article)

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[BibTex]

[BibTex]


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Survey and Introduction to the Focused Section on Bio-Inspired Mechatronics

Sitti, M., Menciassi, A., Ijspeert, A., Low, K. H., Kim, S.

Mechatronics, IEEE/ASME Transactions on, 18(2):409-418, DOI: 10.1109/TMECH.2012. 2233492, 2013 (article)

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[BibTex]

[BibTex]

2011


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Learning, planning, and control for quadruped locomotion over challenging terrain

Kalakrishnan, Mrinal, Buchli, Jonas, Pastor, Peter, Mistry, Michael, Schaal, S.

International Journal of Robotics Research, 30(2):236-258, February 2011 (article)

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[BibTex]

2011


[BibTex]


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Design and application of a wire-driven bidirectional telescopic mechanism for workspace expansion with a focus on shipbuilding tasks

Lee, D., Chang, D., Shin, Y., Son, D., Kim, T., Lee, K., Kim, J.

Advanced Robotics, 25, 2011 (article)

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[BibTex]

[BibTex]


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Bayesian robot system identification with input and output noise

Ting, J., D’Souza, A., Schaal, S.

Neural Networks, 24(1):99-108, 2011, clmc (article)

Abstract
For complex robots such as humanoids, model-based control is highly beneficial for accurate tracking while keeping negative feedback gains low for compliance. However, in such multi degree-of-freedom lightweight systems, conventional identification of rigid body dynamics models using CAD data and actuator models is inaccurate due to unknown nonlinear robot dynamic effects. An alternative method is data-driven parameter estimation, but significant noise in measured and inferred variables affects it adversely. Moreover, standard estimation procedures may give physically inconsistent results due to unmodeled nonlinearities or insufficiently rich data. This paper addresses these problems, proposing a Bayesian system identification technique for linear or piecewise linear systems. Inspired by Factor Analysis regression, we develop a computationally efficient variational Bayesian regression algorithm that is robust to ill-conditioned data, automatically detects relevant features, and identifies input and output noise. We evaluate our approach on rigid body parameter estimation for various robotic systems, achieving an error of up to three times lower than other state-of-the-art machine learning methods

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link (url) [BibTex]

link (url) [BibTex]


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Learning variable impedance control

Buchli, J., Stulp, F., Theodorou, E., Schaal, S.

International Journal of Robotics Research, 2011, clmc (article)

Abstract
One of the hallmarks of the performance, versatility, and robustness of biological motor control is the ability to adapt the impedance of the overall biomechanical system to different task requirements and stochastic disturbances. A transfer of this principle to robotics is desirable, for instance to enable robots to work robustly and safely in everyday human environments. It is, however, not trivial to derive variable impedance controllers for practical high degree-of-freedom (DOF) robotic tasks. In this contribution, we accomplish such variable impedance control with the reinforcement learning (RL) algorithm PISq ({f P}olicy {f I}mprovement with {f P}ath {f I}ntegrals). PISq is a model-free, sampling based learning method derived from first principles of stochastic optimal control. The PISq algorithm requires no tuning of algorithmic parameters besides the exploration noise. The designer can thus fully focus on cost function design to specify the task. From the viewpoint of robotics, a particular useful property of PISq is that it can scale to problems of many DOFs, so that reinforcement learning on real robotic systems becomes feasible. We sketch the PISq algorithm and its theoretical properties, and how it is applied to gain scheduling for variable impedance control. We evaluate our approach by presenting results on several simulated and real robots. We consider tasks involving accurate tracking through via-points, and manipulation tasks requiring physical contact with the environment. In these tasks, the optimal strategy requires both tuning of a reference trajectory emph{and} the impedance of the end-effector. The results show that we can use path integral based reinforcement learning not only for planning but also to derive variable gain feedback controllers in realistic scenarios. Thus, the power of variable impedance control is made available to a wide variety of robotic systems and practical applications.

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link (url) [BibTex]

link (url) [BibTex]


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Waalbot II: Adhesion recovery and improved performance of a climbing robot using fibrillar adhesives

Murphy, M. P., Kute, C., Mengüç, Y., Sitti, M.

The International Journal of Robotics Research, 30(1):118-133, SAGE Publications Sage UK: London, England, 2011 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Automated 2-D nanoparticle manipulation using atomic force microscopy

Onal, C. D., Ozcan, O., Sitti, M.

IEEE Transactions on Nanotechnology, 10(3):472-481, IEEE, 2011 (article)

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[BibTex]

[BibTex]


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Biaxial mechanical modeling of the small intestine

Bellini, C., Glass, P., Sitti, M., Di Martino, E. S.

Journal of the mechanical behavior of biomedical materials, 4(8):1727-1740, Elsevier, 2011 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Understanding haptics by evolving mechatronic systems

Loeb, G. E., Tsianos, G.A., Fishel, J.A., Wettels, N., Schaal, S.

Progress in Brain Research, 192, pages: 129, 2011 (article)

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[BibTex]

[BibTex]


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Assembly and disassembly of magnetic mobile micro-robots towards deterministic 2-D reconfigurable micro-systems

Diller, E., Pawashe, C., Floyd, S., Sitti, M.

The International Journal of Robotics Research, 30(14):1667-1680, SAGE Publications Sage UK: London, England, 2011 (article)

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[BibTex]

[BibTex]


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Modeling of stochastic motion of bacteria propelled spherical microbeads

Arabagi, V., Behkam, B., Cheung, E., Sitti, M.

Journal of Applied Physics, 109(11):114702, AIP, 2011 (article)

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Project Page [BibTex]

Project Page [BibTex]


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The effect of aspect ratio on adhesion and stiffness for soft elastic fibres

Aksak, B., Hui, C., Sitti, M.

Journal of The Royal Society Interface, 8(61):1166-1175, The Royal Society, 2011 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Enhancing adhesion of biologically inspired polymer microfibers with a viscous oil coating

Cheung, E., Sitti, M.

The Journal of Adhesion, 87(6):547-557, Taylor & Francis Group, 2011 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Piezoelectric polymer fiber arrays for tactile sensing applications

Sümer, B., Aksak, B., Şsahin, K., Chuengsatiansup, K., Sitti, M.

Sensor Letters, 9(2):457-463, American Scientific Publishers, 2011 (article)

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Project Page [BibTex]

Project Page [BibTex]


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Control methodologies for a heterogeneous group of untethered magnetic micro-robots

Floyd, S., Diller, E., Pawashe, C., Sitti, M.

The International Journal of Robotics Research, 30(13):1553-1565, SAGE Publications, 2011 (article)

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[BibTex]

[BibTex]