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2006


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Learning operational space control

Peters, J., Schaal, S.

In Robotics: Science and Systems II (RSS 2006), pages: 255-262, (Editors: Gaurav S. Sukhatme and Stefan Schaal and Wolfram Burgard and Dieter Fox), Cambridge, MA: MIT Press, RSS , 2006, clmc (inproceedings)

Abstract
While operational space control is of essential importance for robotics and well-understood from an analytical point of view, it can be prohibitively hard to achieve accurate control in face of modeling errors, which are inevitable in complex robots, e.g., humanoid robots. In such cases, learning control methods can offer an interesting alternative to analytical control algorithms. However, the resulting learning problem is ill-defined as it requires to learn an inverse mapping of a usually redundant system, which is well known to suffer from the property of non-covexity of the solution space, i.e., the learning system could generate motor commands that try to steer the robot into physically impossible configurations. A first important insight for this paper is that, nevertheless, a physically correct solution to the inverse problem does exits when learning of the inverse map is performed in a suitable piecewise linear way. The second crucial component for our work is based on a recent insight that many operational space controllers can be understood in terms of a constraint optimal control problem. The cost function associated with this optimal control problem allows us to formulate a learning algorithm that automatically synthesizes a globally consistent desired resolution of redundancy while learning the operational space controller. From the view of machine learning, the learning problem corresponds to a reinforcement learning problem that maximizes an immediate reward and that employs an expectation-maximization policy search algorithm. Evaluations on a three degrees of freedom robot arm illustrate the feasability of our suggested approach.

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link (url) [BibTex]

2006


link (url) [BibTex]


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Reinforcement Learning for Parameterized Motor Primitives

Peters, J., Schaal, S.

In Proceedings of the 2006 International Joint Conference on Neural Networks, pages: 73-80, IJCNN, 2006, clmc (inproceedings)

Abstract
One of the major challenges in both action generation for robotics and in the understanding of human motor control is to learn the "building blocks of movement generation", called motor primitives. Motor primitives, as used in this paper, are parameterized control policies such as splines or nonlinear differential equations with desired attractor properties. While a lot of progress has been made in teaching parameterized motor primitives using supervised or imitation learning, the self-improvement by interaction of the system with the environment remains a challenging problem. In this paper, we evaluate different reinforcement learning approaches for improving the performance of parameterized motor primitives. For pursuing this goal, we highlight the difficulties with current reinforcement learning methods, and outline both established and novel algorithms for the gradient-based improvement of parameterized policies. We compare these algorithms in the context of motor primitive learning, and show that our most modern algorithm, the Episodic Natural Actor-Critic outperforms previous algorithms by at least an order of magnitude. We demonstrate the efficiency of this reinforcement learning method in the application of learning to hit a baseball with an anthropomorphic robot arm.

am ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Ab-initio calculations: I. Basic principles of the density functional electron theory and combination with phenomenological theories

Fähnle, M.

In Structural defects in ordered alloys and intermetallics. Characterization and modelling, pages: IX-1-IX-10, COST and CNRS, Bonascre [Ariege, France], 2006 (inproceedings)

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[BibTex]

[BibTex]


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Hard magnetic FePt thin films and nanostructures in L1(0) phases

Goll, D., Breitling, A., Goo, N. H., Sigle, W., Hirscher, M., Schütz, G.

In 13, pages: 97-101, Beijing, PR China, 2006 (inproceedings)

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[BibTex]

[BibTex]


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Ab-initio calculations: II. Application to atomic defects, phase diagrams, dislocations

Fähnle, M.

In Structural defects in ordered alloys and intermetallics. Characterization and modelling, pages: XIV-1-XIV-11, COST and CNRS, Bonascre [Ariege, France], 2006 (inproceedings)

mms

[BibTex]

[BibTex]


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Residual stress analysis in reed pipe brass tongues of historic organs

Manescu, A., Giuliani, A., Fiori, F., Baretzky, B.

In Residual Stresses VII. 7th Europen Conference on Residual Stresses (ECRS7), pages: 969-974, Trans Tech, Berlin [Germany], 2006 (inproceedings)

mms

[BibTex]

[BibTex]


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High-pressure influence on the kinetics of grain boundary segregation in the Cu-Bi system

Chang, L.-S., Straumal, B., Rabkin, E., Lojkowski, W., Gust, W.

In 258-260, pages: 390-396, Aveiro (Portugal), 2006 (inproceedings)

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[BibTex]

[BibTex]

2002


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Learning rhythmic movements by demonstration using nonlinear oscillators

Ijspeert, J. A., Nakanishi, J., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2002), pages: 958-963, Piscataway, NJ: IEEE, Lausanne, Sept.30-Oct.4 2002, 2002, clmc (inproceedings)

Abstract
Locally weighted learning (LWL) is a class of statistical learning techniques that provides useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of robotic systems. This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks. We discuss two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly. In contrast to the traditional beliefs that LWL methods cannot work well in high-dimensional spaces, we provide new algorithms that have been tested in up to 50 dimensional learning problems. The applicability of our LWL algorithms is demonstrated in various robot learning examples, including the learning of devil-sticking, pole-balancing of a humanoid robot arm, and inverse-dynamics learning for a seven degree-of-freedom robot.

am

link (url) [BibTex]

2002


link (url) [BibTex]


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Pressure Isotherms of Hydrogen Adsorption in Carbon Nanostructures

Chen, X., Dettlaff-Weglikowska, U., Haluska, M., Hulman, M., Roth, S., Hirscher, M., Becher, M.

In Making Functional Materials with Nanotubes, pages: Z9.11.1-Z9.11.6, Materials Research Society Symposium Proceedings, MRS, Boston [Mass.], 2002 (inproceedings)

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[BibTex]

[BibTex]


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Hydrogen Storage in Carbon SWNTs: Atomic or Molecular?

Haluska, M., Hirscher, M., Becher, M., Dettlaff-Weglikowska, U., Chen, X., Roth, S.

In Structural and Electronic Properties of Molecular Nanostructures, pages: 601-605, AIP Conference Proceedings, AIP, Kirchberg, Tirol [Austria], 2002 (inproceedings)

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[BibTex]

[BibTex]


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Hydrogen Storage in Nanostructured Carbon Materials at Room Temperature

Chen, X., Dettlaff-Weglikowska, U., Haluska, M., Hirscher, M., Becher, M., Roth, S.

In Structural and Electronic Properties of Molecular Nanostructures, pages: 597-600, AIP Conference Proceedings, AIP, Kirchberg, Tirol [Austria], 2002 (inproceedings)

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[BibTex]

[BibTex]


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Reliable stair climbing in the simple hexapod ’RHex’

Moore, E. Z., Campbell, D., Grimminger, F., Buehler, M.

In Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 3, pages: 2222-2227 vol.3, May 2002 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Movement imitation with nonlinear dynamical systems in humanoid robots

Ijspeert, J. A., Nakanishi, J., Schaal, S.

In International Conference on Robotics and Automation (ICRA2002), Washinton, May 11-15 2002, 2002, clmc (inproceedings)

Abstract
Locally weighted learning (LWL) is a class of statistical learning techniques that provides useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of robotic systems. This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks. We discuss two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly. In contrast to the traditional beliefs that LWL methods cannot work well in high-dimensional spaces, we provide new algorithms that have been tested in up to 50 dimensional learning problems. The applicability of our LWL algorithms is demonstrated in various robot learning examples, including the learning of devil-sticking, pole-balancing of a humanoid robot arm, and inverse-dynamics learning for a seven degree-of-freedom robot.

am

link (url) [BibTex]

link (url) [BibTex]


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A locally weighted learning composite adaptive controller with structure adaptation

Nakanishi, J., Farrell, J. A., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2002), Lausanne, Sept.30-Oct.4 2002, 2002, clmc (inproceedings)

Abstract
This paper introduces a provably stable adaptive learning controller which employs nonlinear function approximation with automatic growth of the learning network according to the nonlinearities and the working domain of the control system. The unknown function in the dynamical system is approximated by piecewise linear models using a nonparametric regression technique. Local models are allocated as necessary and their parameters are optimized on-line. Inspired by composite adaptive control methods, the pro-posed learning adaptive control algorithm uses both the tracking error and the estimation error to up-date the parameters. We provide Lyapunov analyses that demonstrate the stability properties of the learning controller. Numerical simulations illustrate rapid convergence of the tracking error and the automatic structure adaptation capability of the function approximator. This paper introduces a provably stable adaptive learning controller which employs nonlinear function approximation with automatic growth of the learning network according to the nonlinearities and the working domain of the control system. The unknown function in the dynamical system is approximated by piecewise linear models using a nonparametric regression technique. Local models are allocated as necessary and their parameters are optimized on-line. Inspired by composite adaptive control methods, the pro-posed learning adaptive control algorithm uses both the tracking error and the estimation error to up-date the parameters. We provide Lyapunov analyses that demonstrate the stability properties of the learning controller. Numerical simulations illustrate rapid convergence of the tracking error and the automatic structure adaptation capability of the function approximator

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link (url) [BibTex]

link (url) [BibTex]


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Micromagnetism and the microstructure of the cell walls in Sm2Co17 based permanent magnets

Goll, D., Hadjipanayis, G. C., Kronmüller, H.

In Proceedings of the 17th International Workshop on Rare-Earth Magnets and their Applications, pages: 696-703, Rinton Press, Newark, Delaware, USA, 2002 (inproceedings)

mms

[BibTex]

[BibTex]


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Ab-initio study of the influence of epitaxial strain on magnetoelastic properties

Komelj, M., Fähnle, M.

In Atomistic Aspects of Epitaxial Growth, pages: 439-447, NATO Science series: Series 2, Mathematics, Physics, and Chemistry, Kluwer Academic Publishers, Dassia, Corfu [Greece], 2002 (inproceedings)

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[BibTex]

[BibTex]

2001


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Humanoid oculomotor control based on concepts of computational neuroscience

Shibata, T., Vijayakumar, S., Conradt, J., Schaal, S.

In Humanoids2001, Second IEEE-RAS International Conference on Humanoid Robots, 2001, clmc (inproceedings)

Abstract
Oculomotor control in a humanoid robot faces similar problems as biological oculomotor systems, i.e., the stabilization of gaze in face of unknown perturbations of the body, selective attention, the complexity of stereo vision and dealing with large information processing delays. In this paper, we suggest control circuits to realize three of the most basic oculomotor behaviors - the vestibulo-ocular and optokinetic reflex (VOR-OKR) for gaze stabilization, smooth pursuit for tracking moving objects, and saccades for overt visual attention. Each of these behaviors was derived from inspirations from computational neuroscience, which proves to be a viable strategy to explore novel control mechanisms for humanoid robotics. Our implementations on a humanoid robot demonstrate good performance of the oculomotor behaviors that appears natural and human-like.

am

link (url) [BibTex]

2001


link (url) [BibTex]


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Computational micromagnetism of magnetic structures and magnetization processes in thin plantelets and small particles

Kronmüller, H., Hertel, R.

In Magnetic Storage Sstems Beyond 2000, 41, pages: 345-362, Nato Science Series II: Mathematics, Physics and Chemistry, Kluwer Academic Publishers, Rhodos, Greece, 2001 (inproceedings)

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[BibTex]

[BibTex]


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Hydrogen storage in mechanically treated single wall carbon nanotrubes

Haluska, M., Hulman, M., Hirscher, M., Becher, M., Roth, S., Stepanek, I., Bernier, P.

In Electronic Properties of Molecular Nanostructures: XV International Winterschool/Euroconference, 591, pages: 603-608, American Institute of Physics Conference Proceedings, AIP, Kirchberg [Austria], 2001 (inproceedings)

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[BibTex]

[BibTex]


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Isotopic mass and lattice constant of Si and Ge: X-Ray standing wave measurements

Zegenhagen, J., Kazimirov, A., Cao, L. X., Konuma, M., Sozontov, E., Plachke, D., Carstanjen, H. D., Bilger, G., Haller, E., Kohn, V., Cardona, M.

In Proceedings of the 25th Conference on the Physics of Semiconductors, 87, pages: 125-127, Springer proceedings in physics, Springer, Osaka, Japan, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Positron Annihilation Studies on Stable and Undercooled Metal Melts at the Stuttgart Pelletron

Stoll, H., Siegle, A., Major, J.

In Application of Accelerators in Research and Industry, 576, pages: 749-752, AIP Conference Proceedings, Denton, Texas, USA, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Trajectory formation for imitation with nonlinear dynamical systems

Ijspeert, A., Nakanishi, J., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2001), pages: 752-757, Weilea, Hawaii, Oct.29-Nov.3, 2001, clmc (inproceedings)

Abstract
This article explores a new approach to learning by imitation and trajectory formation by representing movements as mixtures of nonlinear differential equations with well-defined attractor dynamics. An observed movement is approximated by finding a best fit of the mixture model to its data by a recursive least squares regression technique. In contrast to non-autonomous movement representations like splines, the resultant movement plan remains an autonomous set of nonlinear differential equations that forms a control policy which is robust to strong external perturbations and that can be modified by additional perceptual variables. This movement policy remains the same for a given target, regardless of the initial conditions, and can easily be re-used for new targets. We evaluate the trajectory formation system (TFS) in the context of a humanoid robot simulation that is part of the Virtual Trainer (VT) project, which aims at supervising rehabilitation exercises in stroke-patients. A typical rehabilitation exercise was collected with a Sarcos Sensuit, a device to record joint angular movement from human subjects, and approximated and reproduced with our imitation techniques. Our results demonstrate that multi-joint human movements can be encoded successfully, and that this system allows robust modifications of the movement policy through external variables.

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link (url) [BibTex]

link (url) [BibTex]


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Real-time statistical learning for robotics and human augmentation

Schaal, S., Vijayakumar, S., D’Souza, A., Ijspeert, A., Nakanishi, J.

In International Symposium on Robotics Research, (Editors: Jarvis, R. A.;Zelinsky, A.), Lorne, Victoria, Austrialia Nov.9-12, 2001, clmc (inproceedings)

Abstract
Real-time modeling of complex nonlinear dynamic processes has become increasingly important in various areas of robotics and human augmentation. To address such problems, we have been developing special statistical learning methods that meet the demands of on-line learning, in particular the need for low computational complexity, rapid learning, and scalability to high-dimensional spaces. In this paper, we introduce a novel algorithm that possesses all the necessary properties by combining methods from probabilistic and nonparametric learning. We demonstrate the applicability of our methods for three different applications in humanoid robotics, i.e., the on-line learning of a full-body inverse dynamics model, an inverse kinematics model, and imitation learning. The latter application will also introduce a novel method to shape attractor landscapes of dynamical system by means of statis-tical learning.

am

link (url) [BibTex]

link (url) [BibTex]


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Submicrometer spatially resolved measurements of mechanical properties and correlation to microstructure and composition

Kunert, M., Baretzky, B., Baker, S. P., Mittemeijer, E. J.

In Fundamentals of Nanoindentation and Nanotribology II, 649, pages: Q3.2.1-Q3.2.6, Materials Research Society Symposium Proceedings, MRS, Boston, MA, USA, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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The six-jump diffusion cycles in B2-compounds

Drautz, R., Meyer, B., Fähnle, M.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, pages: 417-422, Defect and Diffusion Forum, Scitec Publications Ltd., Paris, France, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Ionic nitriding of austenitic and ferritic steel with the aid of a high aperture hall current accelerator

Straumal, B. B., Vershinin, N. F., Friesel, M., Ishenko, S. A., Gust, W.

In Diffusion in Materials DIMAT2000, 194, pages: 1457-1462, Defect and Diffusion Forum, Trans Tech, Paris, France, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Robust learning of arm trajectories through human demonstration

Billard, A., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2001), Piscataway, NJ: IEEE, Maui, Hawaii, Oct.29-Nov.3, 2001, clmc (inproceedings)

Abstract
We present a model, composed of hierarchy of artificial neural networks, for robot learning by demonstration. The model is implemented in a dynamic simulation of a 41 degrees of freedom humanoid for reproducing 3D human motion of the arm. Results show that the model requires few information about the desired trajectory and learns on-line the relevant features of movement. It can generalize across a small set of data to produce a qualitatively good reproduction of the demonstrated trajectory. Finally, it is shown that reproduction of the trajectory after learning is robust against perturbations.

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link (url) [BibTex]

link (url) [BibTex]


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First proof of slow trapping of positronium in polymers by an Age-Momentum-Correlation (AMOC) experiment

Dauwe, C., Balcaen, N., van Waeyenberge, B., van Petegem, S., Stoll, H.

In Positron Annihilation. Proceedings of the 12th International Conference on Positron Annihilation, 363/365, pages: 254-256, Materials Science Forum, Trans Tech Publications Ltd., München, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Positron-age-momentum correlation

Stoll, H., Bandzuch, P., Siegle, A.

In Positron Annihilation: Proceedings of the 12th International Conference on Positron Annihilation, 363-365, pages: 547-551, Materials Science Forum, Trans Tech Publications Ltd., München, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Nanocrystalline and nanostructured high-performance permanent magnets

Goll, D., Hadjipanayis, G. C., Kronmüller, H.

In Applications of Ferromagnetic and Optical Materials, Storage and Magnetoelectronics, 674, pages: U2.4.1-U2.4.12, Materials Research Society Symposium Proceedings, MRS, San Francisco, Calif., 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Ion beam analysis with monolayer depth resolution using the electrostatic spectrometer at the MPI Stuttgart

Plachke, D., Blohm, G., Fischer, T., Khellaf, A., Kruse, O., Stoll, H., Carstanjen, H. D.

In Proceedings of the 16th International Conference on Applications of Accelerators in Research and Industry, 576, pages: 458-462, American Institute of Physics Conference Proceedings, AIP, Denton, Texas, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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From the electronic structure to the macroscopiy behavior: A multi-scale analysis of plasticity in intermetallic compounds

Fähnle, M., Kohlhammer, S., Bester, G.

In Influences of Interface and Dislocation Behavior on Microstructure Evolution, 652, pages: Y4.5.1.-Y4.5.12, Materials Research Society Symposium Proceedings, MRS, Boston, Mass., USA, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Influence of the microstructure on the magnetic properties of giant-magnetostrictive TbDyFe films

Hirscher, M., Winzek, B., Fischer, S. F., Kronmüller, H.

In Smart Materials. Proceedings of the 1st Caesarium, pages: 23-37, Springer, Bonn, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Overt visual attention for a humanoid robot

Vijayakumar, S., Conradt, J., Shibata, T., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2001), 2001, clmc (inproceedings)

Abstract
The goal of our research is to investigate the interplay between oculomotor control, visual processing, and limb control in humans and primates by exploring the computational issues of these processes with a biologically inspired artificial oculomotor system on an anthropomorphic robot. In this paper, we investigate the computational mechanisms for visual attention in such a system. Stimuli in the environment excite a dynamical neural network that implements a saliency map, i.e., a winner-take-all competition between stimuli while simultenously smoothing out noise and suppressing irrelevant inputs. In real-time, this system computes new targets for the shift of gaze, executed by the head-eye system of the robot. The redundant degrees-of- freedom of the head-eye system are resolved through a learned inverse kinematics with optimization criterion. We also address important issues how to ensure that the coordinate system of the saliency map remains correct after movement of the robot. The presented attention system is built on principled modules and generally applicable for any sensory modality.

am

link (url) [BibTex]

link (url) [BibTex]


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Materials analysis with monolayer depth resolution using MeV ion beams

Carstanjen, H. D.

In 117, Las Vegas, USA, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Flux-line pinning in low-angle grain boundaries.

Albrecht, J., Leonhardt, S., Kronmüller, H.

In Proceedings 10th International Workshop on Critical Currents (IWCC 2001), pages: 41-43, Göttingen, Germany, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Learning inverse kinematics

D’Souza, A., Vijayakumar, S., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2001), Piscataway, NJ: IEEE, Maui, Hawaii, Oct.29-Nov.3, 2001, clmc (inproceedings)

Abstract
Real-time control of the endeffector of a humanoid robot in external coordinates requires computationally efficient solutions of the inverse kinematics problem. In this context, this paper investigates learning of inverse kinematics for resolved motion rate control (RMRC) employing an optimization criterion to resolve kinematic redundancies. Our learning approach is based on the key observations that learning an inverse of a non uniquely invertible function can be accomplished by augmenting the input representation to the inverse model and by using a spatially localized learning approach. We apply this strategy to inverse kinematics learning and demonstrate how a recently developed statistical learning algorithm, Locally Weighted Projection Regression, allows efficient learning of inverse kinematic mappings in an incremental fashion even when input spaces become rather high dimensional. The resulting performance of the inverse kinematics is comparable to Liegeois ([1]) analytical pseudo inverse with optimization. Our results are illustrated with a 30 degree-of-freedom humanoid robot.

am

link (url) [BibTex]

link (url) [BibTex]


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Biomimetic smooth pursuit based on fast learning of the target dynamics

Shibata, T., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2001), 2001, clmc (inproceedings)

Abstract
Following a moving target with a narrow-view foveal vision system is one of the essential oculomotor behaviors of humans and humanoids. This oculomotor behavior, called ``Smooth Pursuit'', requires accurate tracking control which cannot be achieved by a simple visual negative feedback controller due to the significant delays in visual information processing. In this paper, we present a biologically inspired and control theoretically sound smooth pursuit controller consisting of two cascaded subsystems. One is an inverse model controller for the oculomotor system, and the other is a learning controller for the dynamics of the visual target. The latter controller learns how to predict the target's motion in head coordinates such that tracking performance can be improved. We investigate our smooth pursuit system in simulations and experiments on a humanoid robot. By using a fast on-line statistical learning network, our humanoid oculomotor system is able to acquire high performance smooth pursuit after about 5 seconds of learning despite significant processing delays in the syste

am

link (url) [BibTex]

link (url) [BibTex]


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Measurement of the low-temperature self-diffusivity of lithium by elastic recoil detection analysis

Wieland, O., Carstanjen, H. D.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, 194/199, pages: 35-41, Defect and Diffusion Forum, Scitec Publications Ltd., Paris, France, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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From the electronic structure to the macroscopic behaviour: a multi-scale analysis of plasticity in intermetallic compounds

Fähnle, M., Kohlhammer, S., Bester, G.

In Influences of Interface and Dislocation Behavior on Microstructure Evolution, 652, pages: Y.4.5.1-Y.4.5.12, Materials Research Society Symposium Proceedings, MRS, Boston, Mass., 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Enhancement of the critical current density of YBa2Cu3O7-8-films by substracte irradiation

Leonhardt, S., Albrecht, J., Warthmann, R., Kronmüller, H.

In High-Tc Superconductors and Related Applications: Materials Science, Fundamental Properties, and Some Future Electronic Applications. Proceedings of the NATO Advanced Study Institute, 86, pages: 529-534, NATO Science Series 3. High Technology, Kluwer Academic Publishers, Albena, Bulgaria, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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AMOC studies of positronium in fine MgO powder

van Waeyenberge, B., Dauwe, C., Stoll, H.

In Positron Annihilation. Proceedings of the 12th International Conference on Positron Annihilation, 363/365, pages: 401-403, Materials Science Forum, Trans Tech Publications Ltd., München, 2001 (inproceedings)

mms

[BibTex]

[BibTex]


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Atomic defects and electronic structure of B2-FeAl, CoAl and NiAl

Fähnle, M., Meyer, B., Bester, G., Majer, J., Börnsen, N.

In Proceedings of DIMAT 2000, the Fifth International Conference on Diffusion in Materials, 194/199, pages: 279-285, Defect and Diffusion Forum, Scitec Publications Ltd., Paris, France, 2001 (inproceedings)

mms

[BibTex]

[BibTex]

1998


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Programmable pattern generators

Schaal, S., Sternad, D.

In 3rd International Conference on Computational Intelligence in Neuroscience, pages: 48-51, Research Triangle Park, NC, Oct. 24-28, October 1998, clmc (inproceedings)

Abstract
This paper explores the idea to create complex human-like arm movements from movement primitives based on nonlinear attractor dynamics. Each degree-of-freedom of an arm is assumed to have two independent abilities to create movement, one through a discrete dynamic system, and one through a rhythmic system. The discrete system creates point-to-point movements based on internal or external target specifications. The rhythmic system can add an additional oscillatory movement relative to the current position of the discrete system. In the present study, we develop appropriate dynamic systems that can realize the above model, motivate the particular choice of the systems from a biological and engineering point of view, and present simulation results of the performance of such movement primitives. Implementation results on a Sarcos Dexterous Arm are discussed.

am

link (url) [BibTex]

1998


link (url) [BibTex]


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Robust local learning in high dimensional spaces

Vijayakumar, S., Schaal, S.

In 5th Joint Symposium on Neural Computation, pages: 186-193, Institute for Neural Computation, University of California, San Diego, San Diego, CA, 1998, clmc (inproceedings)

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 this 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.

am

[BibTex]

[BibTex]


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Local dimensionality reduction

Schaal, S., Vijayakumar, S., Atkeson, C. G.

In Advances in Neural Information Processing Systems 10, pages: 633-639, (Editors: Jordan, M. I.;Kearns, M. J.;Solla, S. A.), MIT Press, Cambridge, MA, 1998, clmc (inproceedings)

Abstract
If globally high dimensional data has locally only low dimensional distributions, it is advantageous to perform a local dimensionality reduction before further processing the data. In this paper we examine several techniques for local dimensionality reduction in the context of locally weighted linear regression. As possible candidates, we derive local versions of factor analysis regression, principle component regression, principle component regression on joint distributions, and partial least squares regression. After outlining the statistical bases of these methods, we perform Monte Carlo simulations to evaluate their robustness with respect to violations of their statistical assumptions. One surprising outcome is that locally weighted partial least squares regression offers the best average results, thus outperforming even factor analysis, the theoretically most appealing of our candidate techniques.

am

link (url) [BibTex]

link (url) [BibTex]


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Biomimetic gaze stabilization based on a study of the vestibulocerebellum

Shibata, T., Schaal, S.

In European Workshop on Learning Robots, pages: 84-94, Edinburgh, UK, 1998, clmc (inproceedings)

Abstract
Accurate oculomotor control is one of the essential pre-requisites for successful visuomotor coordination. In this paper, we suggest a biologically inspired control system for learning gaze stabilization with a biomimetic robotic oculomotor system. In a stepwise fashion, we develop a control circuit for the vestibulo-ocular reflex (VOR) and the opto-kinetic response (OKR), and add a nonlinear learning network to allow adaptivity. We discuss the parallels and differences of our system with biological oculomotor control and suggest solutions how to deal with nonlinearities and time delays in the control system. In simulation and actual robot studies, we demonstrate that our system can learn gaze stabilization in real time in only a few seconds with high final accuracy.

am

link (url) [BibTex]

link (url) [BibTex]


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Towards biomimetic vision

Shibata, T., Schaal, S.

In International Conference on Intelligence Robots and Systems, pages: 872-879, Victoria, Canada, 1998, clmc (inproceedings)

Abstract
Oculomotor control is the foundation of most biological visual systems, as well as an important component in the entire perceptual-motor system. We review some of the most basic principles of biological oculomotor systems, and explore their usefulness from both the biological and computational point of view. As an example of biomimetic oculomotor control, we present the state of our implementations and experimental results using the vestibulo-ocular-reflex and opto-kinetic-reflex paradigm

am

link (url) [BibTex]

link (url) [BibTex]