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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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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]

1998


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Tele-nanorobotics using an atomic force microscope as a nanorobot and sensor

Sitti, M., Hashimoto, H.

Advanced Robotics, 13(4):417-436, Taylor & Francis, 1998 (article)

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[BibTex]

1998


[BibTex]


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Constructive incremental learning from only local information

Schaal, S., Atkeson, C. G.

Neural Computation, 10(8):2047-2084, 1998, clmc (article)

Abstract
We introduce a constructive, incremental learning system for regression problems that models data by means of spatially localized linear models. In contrast to other approaches, the size and shape of the receptive field of each locally linear model as well as the parameters of the locally linear model itself are learned independently, i.e., without the need for competition or any other kind of communication. Independent learning is accomplished by incrementally minimizing a weighted local cross validation error. As a result, we obtain a learning system that can allocate resources as needed while dealing with the bias-variance dilemma in a principled way. The spatial localization of the linear models increases robustness towards negative interference. Our learning system can be interpreted as a nonparametric adaptive bandwidth smoother, as a mixture of experts where the experts are trained in isolation, and as a learning system which profits from combining independent expert knowledge on the same problem. This paper illustrates the potential learning capabilities of purely local learning and offers an interesting and powerful approach to learning with receptive fields. 

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link (url) [BibTex]

link (url) [BibTex]


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Local adaptive subspace regression

Vijayakumar, S., Schaal, S.

Neural Processing Letters, 7(3):139-149, 1998, clmc (article)

Abstract
Incremental learning of sensorimotor transformations in high dimensional spaces is one of the basic prerequisites for the success of autonomous robot devices as well as biological movement systems. So far, due to sparsity of data in high dimensional spaces, learning in such settings requires a significant amount of prior knowledge about the learning task, usually provided by a human expert. In this paper we suggest a partial revision of the view. Based on empirical studies, we observed that, despite being globally high dimensional and sparse, data distributions from physical movement systems are locally low dimensional and dense. Under this assumption, we derive a learning algorithm, Locally Adaptive Subspace Regression, that exploits this property by combining a dynamically growing local dimensionality reduction technique  as a preprocessing step with a nonparametric learning technique, locally weighted regression, that also learns the region of validity of the regression. The usefulness of the algorithm and the validity of its assumptions are illustrated for a synthetic data set, and for data of the inverse dynamics of human arm movements and an actual 7 degree-of-freedom anthropomorphic robot arm. 

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link (url) [BibTex]

link (url) [BibTex]

1995


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Memory-based neural networks for robot learning

Atkeson, C. G., Schaal, S.

Neurocomputing, 9, pages: 1-27, 1995, clmc (article)

Abstract
This paper explores a memory-based approach to robot learning, using memory-based neural networks to learn models of the task to be performed. Steinbuch and Taylor presented neural network designs to explicitly store training data and do nearest neighbor lookup in the early 1960s. In this paper their nearest neighbor network is augmented with a local model network, which fits a local model to a set of nearest neighbors. This network design is equivalent to a statistical approach known as locally weighted regression, in which a local model is formed to answer each query, using a weighted regression in which nearby points (similar experiences) are weighted more than distant points (less relevant experiences). We illustrate this approach by describing how it has been used to enable a robot to learn a difficult juggling task. Keywords: memory-based, robot learning, locally weighted regression, nearest neighbor, local models.

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link (url) [BibTex]

1995


link (url) [BibTex]


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In vivo diabetic wound healing with nanofibrous scaffolds modified with gentamicin and recombinant human epidermal growth factor

Dwivedi, C., Pandey, I., Pandey, H., Patil, S., Mishra, S. B., Pandey, A. C., Zamboni, P., Ramteke, P. W., Singh, A. V.

Journal of Biomedical Materials Research Part A, 106(3):641-651, March (article)

Abstract
Abstract Diabetic wounds are susceptible to microbial infection. The treatment of these wounds requires a higher payload of growth factors. With this in mind, the strategy for this study was to utilize a novel payload comprising of Eudragit RL/RS 100 nanofibers carrying the bacterial inhibitor gentamicin sulfate (GS) in concert with recombinant human epidermal growth factor (rhEGF); an accelerator of wound healing. GS containing Eudragit was electrospun to yield nanofiber scaffolds, which were further modified by covalent immobilization of rhEGF to their surface. This novel fabricated nanoscaffold was characterized using scanning electron microscopy, Fourier transform infrared spectroscopy, and X‐ray diffraction. The thermal behavior of the nanoscaffold was determined using thermogravimetric analysis and differential scanning calorimetry. In the in vitro antibacterial assays, the nanoscaffolds exhibited comparable antibacterial activity to pure gentemicin powder. In vivo work using female C57/BL6 mice, the nanoscaffolds induced faster wound healing activity in dorsal wounds compared to the control. The paradigm in this study presents a robust in vivo model to enhance the applicability of drug delivery systems in wound healing applications. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 641–651, 2018.

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link (url) DOI [BibTex]


link (url) DOI [BibTex]


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Robotics Research

Tong, Chi Hay, Furgale, Paul, Barfoot, Timothy D, Guizilini, Vitor, Ramos, Fabio, Chen, Yushan, T\uumová, Jana, Ulusoy, Alphan, Belta, Calin, Tenorth, Moritz, others

(article)

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[BibTex]

[BibTex]