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2005


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A new methodology for robot control design

Peters, J., Mistry, M., Udwadia, F. E., Schaal, S.

In The 5th ASME International Conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC 2005), Long Beach, CA, Sept. 24-28, 2005, clmc (inproceedings)

Abstract
Gauss principle of least constraint and its generalizations have provided a useful insights for the development of tracking controllers for mechanical systems (Udwadia,2003). Using this concept, we present a novel methodology for the design of a specific class of robot controllers. With our new framework, we demonstrate that well-known and also several novel nonlinear robot control laws can be derived from this generic framework, and show experimental verifications on a Sarcos Master Arm robot for some of these controllers. We believe that the suggested approach unifies and simplifies the design of optimal nonlinear control laws for robots obeying rigid body dynamics equations, both with or without external constraints, holonomic or nonholonomic constraints, with over-actuation or underactuation, as well as open-chain and closed-chain kinematics.

am

link (url) [BibTex]

2005


link (url) [BibTex]


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Geckobot and waalbot: Small-scale wall climbing robots

Unver, O., Murphy, M., Sitti, M.

In Infotech@ Aerospace, pages: 6940, 2005 (incollection)

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[BibTex]

[BibTex]


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Fusion of biomedical microcapsule endoscope and microsystem technology

Kim, Tae Song, Kim, Byungkyu, Cho, Dongil Dan, Song, Si Young, Dario, P, Sitti, M

In Solid-State Sensors, Actuators and Microsystems, 2005. Digest of Technical Papers. TRANSDUCERS’05. The 13th International Conference on, 1, pages: 9-14, 2005 (inproceedings)

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[BibTex]

[BibTex]


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Atomic force microscope based two-dimensional assembly of micro/nanoparticles

Tafazzoli, A., Pawashe, C., Sitti, M.

In Assembly and Task Planning: From Nano to Macro Assembly and Manufacturing, 2005.(ISATP 2005). The 6th IEEE International Symposium on, pages: 230-235, 2005 (inproceedings)

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[BibTex]

[BibTex]


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Synthesis of the nanocrystalline MgS and its interaction with hydrogen

Goo, N. H., Hirscher, M.

{Journal of Alloys and Compounds}, 404, pages: 503-506, 2005 (article)

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[BibTex]

[BibTex]


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Time-scales of electronic processes in Fe3O4 - An attempt to resolve a recently accentuated controversy

Fähnle, M., Kronmüller, H., Walz, F.

{Physica B}, 369, pages: 177-180, 2005 (article)

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[BibTex]

[BibTex]


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Bending of magnetic avalanches in MgB2 thin films

Albrecht, J., Matveev, A., Djupmyr, M., Schütz, G., Stuhlhofer, B., Habermeier, H.

{Applied Physics Letters}, 87, 2005 (article)

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[BibTex]

[BibTex]


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Magnetic pinning of flux lines in heterostructures of cuprates and manganites

Albrecht, J., Soltan, S., Habermeier, H.-U.

{Physical Review B}, 72, 2005 (article)

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[BibTex]


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On the pair-potential modelling of alloy surfaces

Drautz, R., Fähnle, M.

{Surface Science}, 585, pages: 108-112, 2005 (article)

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[BibTex]

[BibTex]


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Crystal field parameters at the (0001) surface of rare-earth metals: an ab initio study

Welsch, F., Fähnle, M., Jensen, P. J.

{Journal of Physics: Condensed Matter}, 17, pages: 2061-2072, 2005 (article)

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[BibTex]

[BibTex]


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Spatially resolved ferromagnetic resonance: Imaging of ferromagnetic eigenmodes

Puzic, A., Van Waeyenberge, B., Chou, K. W., Fischer, P., Stoll, H., Schütz, G., Tyliszczak, T., Rott, K., Brückl, H., Reiss, G., Neudecker, I., Haug, T., Buess, M., Back, C. H.

{Journal of Applied Physics}, 97, 2005 (article)

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DOI [BibTex]

DOI [BibTex]


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Defects distribution of Pr2Fe14B hard magnetic magnet from amorphous to nanostructures characterized by positron annihilation spectroscopy

Wu, Y. C., Sprengel, W., Reimann, K., Reichle, K. J., Goll, D., Würschum, R., Schaefer, H. E.

In PRICM 5. Proceedings of the Fifth Pacific RIM International Conference on Advanced Materials and Processing, 475-479, pages: 2123-2126, Materials Science Forum, Trans Tech, Beijing, China, 2005 (inproceedings)

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[BibTex]

[BibTex]


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Implementing sub-ns time resolution into magnetic X-ray microscopies

Puzic, A., Stoll, H., Fischer, P., Van Waeyenberge, B., Raabe, J., Denbeaux, G., Haug, T., Weiss, D., Schütz, G.

In T115, pages: 1029-1031, Malmö/Lund, Sweden, 2005 (inproceedings)

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[BibTex]

[BibTex]


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Proton magnetic resonance spectra of YH3 and LuH3

Brady, S. K., Conradi, M. S., Majer, G., Barnes, R. G.

{Physical Review B}, 72, 2005 (article)

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[BibTex]

[BibTex]


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Hydrogen storage in spherical nanoporous carbons

Terres, E., Panella, B., Hayashi, T., Kim, Y. A., Endo, M., Dominguez, J. M., Hirscher, M., Terrones, H., Terrones, H.

{Chemical Physics Letters}, 403(4-6):363-366, 2005 (article)

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[BibTex]

[BibTex]


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Faceting and migration of twin grain boundaries in zinc

Straumal, B. B., Rabkin, E., Sursaeva, V. G., Goruakova, A. S.

{Zeitschrift f\"ur Metallkunde}, 96(2):161-166, 2005 (article)

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[BibTex]

[BibTex]


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Arm movement experiments with joint space force fields using an exoskeleton robot

Mistry, M., Mohajerian, P., Schaal, S.

In IEEE Ninth International Conference on Rehabilitation Robotics, pages: 408-413, Chicago, Illinois, June 28-July 1, 2005, clmc (inproceedings)

Abstract
A new experimental platform permits us to study a novel variety of issues of human motor control, particularly full 3-D movements involving the major seven degrees-of-freedom (DOF) of the human arm. We incorporate a seven DOF robot exoskeleton, and can minimize weight and inertia through gravity, Coriolis, and inertia compensation, such that subjects' arm movements are largely unaffected by the manipulandum. Torque perturbations can be individually applied to any or all seven joints of the human arm, thus creating novel dynamic environments, or force fields, for subjects to respond and adapt to. Our first study investigates a joint space force field where the shoulder velocity drives a disturbing force in the elbow joint. Results demonstrate that subjects learn to compensate for the force field within about 100 trials, and from the strong presence of aftereffects when removing the field in some randomized catch trials, that an inverse dynamics, or internal model, of the force field is formed by the nervous system. Interestingly, while post-learning hand trajectories return to baseline, joint space trajectories remained changed in response to the field, indicating that besides learning a model of the force field, the nervous system also chose to exploit the space to minimize the effects of the force field on the realization of the endpoint trajectory plan. Further applications for our apparatus include studies in motor system redundancy resolution and inverse kinematics, as well as rehabilitation.

am

link (url) [BibTex]

link (url) [BibTex]


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A unifying framework for the control of robotics systems

Peters, J., Mistry, M., Udwadia, F. E., Cory, R., Nakanishi, J., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2005), pages: 1824-1831, Edmonton, Alberta, Canada, Aug. 2-6, 2005, clmc (inproceedings)

Abstract
Recently, [1] suggested to derive tracking controllers for mechanical systems using a generalization of GaussÕ principle of least constraint. This method al-lows us to reformulate control problems as a special class of optimal control. We take this line of reasoning one step further and demonstrate that well-known and also several novel nonlinear robot control laws can be derived from this generic methodology. We show experimental verifications on a Sar-cos Master Arm robot for some of the the derived controllers.We believe that the suggested approach offers a promising unification and simplification of nonlinear control law design for robots obeying rigid body dynamics equa-tions, both with or without external constraints, with over-actuation or under-actuation, as well as open-chain and closed-chain kinematics.

am

link (url) [BibTex]

link (url) [BibTex]


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A new endoscopic microcapsule robot using beetle inspired microfibrillar adhesives

Cheung, E., Karagozler, M. E., Park, S., Kim, B., Sitti, M.

In Advanced Intelligent Mechatronics. Proceedings, 2005 IEEE/ASME International Conference on, pages: 551-557, 2005 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Learning to Feel the Physics of a Body

Der, R., Hesse, F., Martius, G.

In Computational Intelligence for Modelling, Control and Automation, CIMCA 2005 , 2, pages: 252-257, Washington, DC, USA, 2005 (inproceedings)

Abstract
Despite the tremendous progress in robotic hardware and in both sensorial and computing efficiencies the performance of contemporary autonomous robots is still far below that of simple animals. This has triggered an intensive search for alternative approaches to the control of robots. The present paper exemplifies a general approach to the self-organization of behavior which has been developed and tested in various examples in recent years. We apply this approach to an underactuated snake like artifact with a complex physical behavior which is not known to the controller. Due to the weak forces available, the controller so to say has to develop a kind of feeling for the body which is seen to emerge from our approach in a natural way with meandering and rotational collective modes being observed in computer simulation experiments.

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[BibTex]

[BibTex]


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Nanostructures with high surface area for hydrogen storage

Hirscher, M., Panella, B.

{Journal of Alloys and Compounds}, 404, pages: 399-401, 2005 (article)

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[BibTex]

[BibTex]


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Timescale settling and nature of electron transport in magnetite - General considerations in view of new magnetic after-effect results on dilutely Ti4+-doped Fe3O4

Walz, F., Brabers, V. A. M., Brabers, J. H. V. J., Kronmüller, H.

{Journal of Physics: Condensed Matter}, 17(42):6763-6781, 2005 (article)

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[BibTex]

[BibTex]


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Topological k-space refinement of the configurational energy of alloys

Shchyglo, O., Bugaev, V. N., Drautz, R., Udyansky, A., Reichert, H., Dosch, H.

{Physical Review B}, 72(14), 2005 (article)

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[BibTex]

[BibTex]


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Large surface area nanostructures for hydrogen storage

Hirscher, M., Panella, B.

{Annales de Chimie}, 30(5):519-529, 2005 (article)

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[BibTex]

[BibTex]


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Electronic and magnetic properties of ligand-free FePt nanoparticles

Boyen, H., Fauth, K., Stahl, B., Ziemann, P., Kästle, G., Weigl, F., Banhart, F., He\ssler, M., Schütz, G., Gajbhiye, N. S., Ellrich, J., Hahn, H., Büttner, M., Garnier, M. G., Oelhafen, P.

{Advanced Materials}, 17(5):574-578, 2005 (article)

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DOI [BibTex]

DOI [BibTex]


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Identification of extrinsic Mn contributions in Ga1-xMnxAs by field-dependent magnetic circular X-ray dichroism

Rader, O., Fauth, K., Gould, C., Rüster, C., Schott, G. M., Schmidt, G., Brunner, K., Molenkamp, L. W., Schütz, G., Kronast, F., Dürr, H. A., Eberhardt, W., Gudat, W.

{Journal of Electron Spectroscopy and Related Phenomena}, 144(Sp. issue):789-792, 2005 (article)

mms

DOI [BibTex]

DOI [BibTex]


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Fundamentals of interface phenomena in advanced bulk nanoscale materials

Baretzky, B., Baró, M. D., Grabovetskaya, G. P., Gubicza, J., Ivanov, M. B., Kolobov, Y. R., Langdon, T. G., Lendvai, J., Lipnitskii, A. G., Mazilkin, A. A., Nazarov, A. A., Nogués, J., Ovidko, I. A., Protasova, S. G., Raab, G. I., Révész, Á., Skiba, N. V., Sort, J., Starink, M. J., Straumal, B. B., Suriñach, S., Ungár, T., Zhilyaev, A. P.

{Reviews on Advanced Materials Science}, 9(1):45-108, 2005 (article)

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[BibTex]

[BibTex]


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Formation of nanostructure during high-pressure torsion of Al-Zn, Al-Mg and Al-Zn-Mg alloys

Mazilkin, A. A., Kogtenkova, O. A., Straumal, B. B., Ruslan, Z, Valiev, Z., Baretzky, B.

{Defect and Diffusion Forum}, 237-240, pages: 739-744, 2005 (article)

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[BibTex]

[BibTex]


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Micromagnetic simulation as a bridge between magnetic-force and magnetic-transmission X-ray microscopy

Bolte, M., Eiselt, R., Eimüller, T.

{Journal of Magnetism and Magnetic Materials}, 290, pages: 723-726, 2005 (article)

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[BibTex]

[BibTex]


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Grain-boundary melting phase transition in the Cu-Bi system

Divinski, S., Lohmann, M., Herzig, C., Straumal, B., Baretzky, B., Gust, W.

{Physical Review B}, 71, 2005 (article)

mms

[BibTex]

[BibTex]

1997


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Locally weighted learning

Atkeson, C. G., Moore, A. W., Schaal, S.

Artificial Intelligence Review, 11(1-5):11-73, 1997, clmc (article)

Abstract
This paper surveys locally weighted learning, a form of lazy learning and memory-based learning, and focuses on locally weighted linear regression. The survey discusses distance functions, smoothing parameters, weighting functions, local model structures, regularization of the estimates and bias, assessing predictions, handling noisy data and outliers, improving the quality of predictions by tuning fit parameters, interference between old and new data, implementing locally weighted learning efficiently, and applications of locally weighted learning. A companion paper surveys how locally weighted learning can be used in robot learning and control. Keywords: locally weighted regression, LOESS, LWR, lazy learning, memory-based learning, least commitment learning, distance functions, smoothing parameters, weighting functions, global tuning, local tuning, interference.

am

link (url) [BibTex]

1997


link (url) [BibTex]


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Locally weighted learning for control

Atkeson, C. G., Moore, A. W., Schaal, S.

Artificial Intelligence Review, 11(1-5):75-113, 1997, clmc (article)

Abstract
Lazy learning methods provide useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of complex systems. This paper surveys ways in which locally weighted learning, a type of lazy learning, has been applied by us to control tasks. We explain various forms that control tasks can take, and how this affects the choice of learning paradigm. The discussion section explores the interesting impact that explicitly remembering all previous experiences has on the problem of learning to control. Keywords: locally weighted regression, LOESS, LWR, lazy learning, memory-based learning, least commitment learning, forward models, inverse models, linear quadratic regulation (LQR), shifting setpoint algorithm, dynamic programming.

am

link (url) [BibTex]

link (url) [BibTex]


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Learning from demonstration

Schaal, S.

In Advances in Neural Information Processing Systems 9, pages: 1040-1046, (Editors: Mozer, M. C.;Jordan, M.;Petsche, T.), MIT Press, Cambridge, MA, 1997, clmc (inproceedings)

Abstract
By now it is widely accepted that learning a task from scratch, i.e., without any prior knowledge, is a daunting undertaking. Humans, however, rarely attempt to learn from scratch. They extract initial biases as well as strategies how to approach a learning problem from instructions and/or demonstrations of other humans. For learning control, this paper investigates how learning from demonstration can be applied in the context of reinforcement learning. We consider priming the Q-function, the value function, the policy, and the model of the task dynamics as possible areas where demonstrations can speed up learning. In general nonlinear learning problems, only model-based reinforcement learning shows significant speed-up after a demonstration, while in the special case of linear quadratic regulator (LQR) problems, all methods profit from the demonstration. In an implementation of pole balancing on a complex anthropomorphic robot arm, we demonstrate that, when facing the complexities of real signal processing, model-based reinforcement learning offers the most robustness for LQR problems. Using the suggested methods, the robot learns pole balancing in just a single trial after a 30 second long demonstration of the human instructor. 

am

link (url) [BibTex]

link (url) [BibTex]


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Robot learning from demonstration

Atkeson, C. G., Schaal, S.

In Machine Learning: Proceedings of the Fourteenth International Conference (ICML ’97), pages: 12-20, (Editors: Fisher Jr., D. H.), Morgan Kaufmann, Nashville, TN, July 8-12, 1997, 1997, clmc (inproceedings)

Abstract
The goal of robot learning from demonstration is to have a robot learn from watching a demonstration of the task to be performed. In our approach to learning from demonstration the robot learns a reward function from the demonstration and a task model from repeated attempts to perform the task. A policy is computed based on the learned reward function and task model. Lessons learned from an implementation on an anthropomorphic robot arm using a pendulum swing up task include 1) simply mimicking demonstrated motions is not adequate to perform this task, 2) a task planner can use a learned model and reward function to compute an appropriate policy, 3) this model-based planning process supports rapid learning, 4) both parametric and nonparametric models can be learned and used, and 5) incorporating a task level direct learning component, which is non-model-based, in addition to the model-based planner, is useful in compensating for structural modeling errors and slow model learning. 

am

link (url) [BibTex]

link (url) [BibTex]


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Local dimensionality reduction for locally weighted learning

Vijayakumar, S., Schaal, S.

In International Conference on Computational Intelligence in Robotics and Automation, pages: 220-225, Monteray, CA, July10-11, 1997, 1997, 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 the view. Based on empirical studies, it can been 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 local dimensionality reduction as a preprocessing step with a nonparametric learning technique, locally weighted regression. The usefulness of the algorithm and the validity of its assumptions are illustrated for a synthetic data set and data of the inverse dynamics of an actual 7 degree-of-freedom anthropomorphic robot arm.

am

link (url) [BibTex]

link (url) [BibTex]


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Learning tasks from a single demonstration

Atkeson, C. G., Schaal, S.

In IEEE International Conference on Robotics and Automation (ICRA97), 2, pages: 1706-1712, Piscataway, NJ: IEEE, Albuquerque, NM, 20-25 April, 1997, clmc (inproceedings)

Abstract
Learning a complex dynamic robot manoeuvre from a single human demonstration is difficult. This paper explores an approach to learning from demonstration based on learning an optimization criterion from the demonstration and a task model from repeated attempts to perform the task, and using the learned criterion and model to compute an appropriate robot movement. A preliminary version of the approach has been implemented on an anthropomorphic robot arm using a pendulum swing up task as an example

am

link (url) [BibTex]

link (url) [BibTex]

1995


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A kendama learning robot based on a dynamic optimization theory

Miyamoto, H., Gandolfo, F., Gomi, H., Schaal, S., Koike, Y., Osu, R., Nakano, E., Kawato, M.

In Preceedings of the 4th IEEE International Workshop on Robot and Human Communication (RO-MAN’95), pages: 327-332, Tokyo, July 1995, clmc (inproceedings)

am

[BibTex]

1995


[BibTex]


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Visual tracking for moving multiple objects: an integration of vision and control

Sitti, M, Bozma, I, Denker, A

In Industrial Electronics, 1995. ISIE’95., Proceedings of the IEEE International Symposium on, 2, pages: 535-540, 1995 (inproceedings)

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[BibTex]

[BibTex]


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Batting a ball: Dynamics of a rhythmic skill

Sternad, D., Schaal, S., Atkeson, C. G.

In Studies in Perception and Action, pages: 119-122, (Editors: Bardy, B.;Bostma, R.;Guiard, Y.), Erlbaum, Hillsdayle, NJ, 1995, clmc (inbook)

am

[BibTex]

[BibTex]


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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.

am

link (url) [BibTex]

link (url) [BibTex]