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2003


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Learning from demonstration and adaptation of biped locomotion with dynamical movement primitives

Nakanishi, J., Morimoto, J., Endo, G., Schaal, S., Kawato, M.

In Workshop on Robot Learning by Demonstration, IEEE International Conference on Intelligent Robots and Systems (IROS 2003), Las Vegas, NV, Oct. 27-31, 2003, clmc (inproceedings)

Abstract
In this paper, we report on our research for learning biped locomotion from human demonstration. Our ultimate goal is to establish a design principle of a controller in order to achieve natural human-like locomotion. We suggest dynamical movement primitives as a CPG of a biped robot, an approach we have previously proposed for learning and encoding complex human movements. Demonstrated trajectories are learned through the movement primitives by locally weighted regression, and the frequency of the learned trajectories is adjusted automatically by a novel frequency adaptation algorithm based on phase resetting and entrainment of oscillators. Numerical simulations demonstrate the effectiveness of the proposed locomotion controller.

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link (url) [BibTex]

2003


link (url) [BibTex]


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Movement planning and imitation by shaping nonlinear attractors

Schaal, S.

In Proceedings of the 12th Yale Workshop on Adaptive and Learning Systems, Yale University, New Haven, CT, 2003, clmc (inproceedings)

Abstract
Given the continuous stream of movements that biological systems exhibit in their daily activities, an account for such versatility and creativity has to assume that movement sequences consist of segments, executed either in sequence or with partial or complete overlap. Therefore, a fundamental question that has pervaded research in motor control both in artificial and biological systems revolves around identifying movement primitives (a.k.a. units of actions, basis behaviors, motor schemas, etc.). What are the fundamental building blocks that are strung together, adapted to, and created for ever new behaviors? This paper summarizes results that led to the hypothesis of Dynamic Movement Primitives (DMP). DMPs are units of action that are formalized as stable nonlinear attractor systems. They are useful for autonomous robotics as they are highly flexible in creating complex rhythmic (e.g., locomotion) and discrete (e.g., a tennis swing) behaviors that can quickly be adapted to the inevitable perturbations of a dy-namically changing, stochastic environment. Moreover, DMPs provide a formal framework that also lends itself to investigations in computational neuroscience. A recent finding that allows creating DMPs with the help of well-understood statistical learning methods has elevated DMPs from a more heuristic to a principled modeling approach, and, moreover, created a new foundation for imitation learning. Theoretical insights, evaluations on a humanoid robot, and behavioral and brain imaging data will serve to outline the framework of DMPs for a general approach to motor control and imitation in robotics and biology.

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link (url) [BibTex]

link (url) [BibTex]


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Synthetic gecko foot-hair micro/nano-structures for future wall-climbing robots

Sitti, M., Fearing, R. S.

In Robotics and Automation, 2003. Proceedings. ICRA’03. IEEE International Conference on, 1, pages: 1164-1170, 2003 (inproceedings)

pi

[BibTex]

[BibTex]


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Grain boundary faceting phase transition and thermal grooving in Cu

Straumal, B. B., Polyakov, S. A., Bischoff, E., Mittemeijer, E. J., Gust, W.

In Proceedings of the International Conference on Diffusion, Segregation and Stresses in Materials, 216/217, pages: 93-100, Diffusion and Defect Data, Pt. A, Defect and Diffusion Forum, Scitec Publ., Moscow, 2003 (inproceedings)

mms

[BibTex]

[BibTex]


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Biomimetic propulsion for a swimming surgical micro-robot

Edd, J., Payen, S., Rubinsky, B., Stoller, M. L., Sitti, M.

In Intelligent Robots and Systems, 2003.(IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on, 3, pages: 2583-2588, 2003 (inproceedings)

pi

Project Page [BibTex]

Project Page [BibTex]


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Coercivity mechanism in nanocrystalline and bonded magnets

Goll, D., Kronmüller, H.

In Bonded Magnets. Proceedings of the NATO Advanced Research Workshop on Science and Technology of Bonded Magnets, 118, pages: 115-127, NATO Science Series: Series 2, Mathematics, Physics and Chemistry, Kluwer Acad. Publ., Newark, USA, 2003 (inproceedings)

mms

[BibTex]

[BibTex]


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Investigation of Electromigration in Copper Interconnects by Noise Measurements

Emelianov, V., Ganesan, G., Puzic, A., Schulz, S., Eizenberg, M., Habermeier, H., Stoll, H.

In Noise as a Tool for Studying Materials, pages: 271-281, Proceedings of SPIE, Santa Fe, New Mexico, 2003 (inproceedings)

mms

[BibTex]

[BibTex]


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Attractive people: Assembling loose-limbed models using non-parametric belief propagation

Sigal, L., Isard, M. I., Sigelman, B. H., Black, M. J.

In Advances in Neural Information Processing Systems 16, NIPS, pages: 1539-1546, (Editors: S. Thrun and L. K. Saul and B. Schölkopf), MIT Press, 2003 (inproceedings)

Abstract
The detection and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes, and the high dimensionality of articulated body models. To cope with these problems we represent the 3D human body as a graphical model in which the relationships between the body parts are represented by conditional probability distributions. We formulate the pose estimation problem as one of probabilistic inference over a graphical model where the random variables correspond to the individual limb parameters (position and orientation). Because the limbs are described by 6-dimensional vectors encoding pose in 3-space, discretization is impractical and the random variables in our model must be continuous-valued. To approximate belief propagation in such a graph we exploit a recently introduced generalization of the particle filter. This framework facilitates the automatic initialization of the body-model from low level cues and is robust to occlusion of body parts and scene clutter.

ps

pdf (color) pdf (black and white) [BibTex]

pdf (color) pdf (black and white) [BibTex]


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Neural decoding of cursor motion using a Kalman filter

(Nominated: Best student paper)

Wu, W., Black, M. J., Gao, Y., Bienenstock, E., Serruya, M., Shaikhouni, A., Donoghue, J. P.

In Advances in Neural Information Processing Systems 15, pages: 133-140, MIT Press, 2003 (inproceedings)

ps

pdf [BibTex]

pdf [BibTex]