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15 results (View BibTeX file of all listed publications)

2005

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Composite adaptive control with locally weighted statistical learning

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

Neural Networks, 18(1):71-90, January 2005, clmc (article)

Abstract
This paper introduces a provably stable learning adaptive control framework with statistical learning. The proposed algorithm 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 proposed learning adaptive control algorithm uses both the tracking error and the estimation error to update the parameters. We first discuss statistical learning of nonlinear functions, and motivate our choice of the locally weighted learning framework. Second, we begin with a class of first order SISO systems for theoretical development of our learning adaptive control framework, and present a stability proof including a parameter projection method that is needed to avoid potential singularities during adaptation. Then, we generalize our adaptive controller to higher order SISO systems, and discuss further extension to MIMO problems. Finally, we evaluate our theoretical control framework in numerical simulations to illustrate the effectiveness of the proposed learning adaptive controller for rapid convergence and high accuracy of control.

link (url) [BibTex]

2005

Nakanishi, J., Farrell, J. A., Schaal, S. Composite adaptive control with locally weighted statistical learning Neural Networks, 18(1):71-90, January 2005, clmc (article)

link (url) [BibTex]

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A model of smooth pursuit based on learning of the target dynamics using only retinal signals

Shibata, T., Tabata, H., Schaal, S., Kawato, M.

Neural Networks, 18, pages: 213-225, 2005, clmc (article)

Abstract
While the predictive nature of the primate smooth pursuit system has been evident through several behavioural and neurophysiological experiments, few models have attempted to explain these results comprehensively. The model we propose in this paper in line with previous models employing optimal control theory; however, we hypothesize two new issues: (1) the medical superior temporal (MST) area in the cerebral cortex implements a recurrent neural network (RNN) in order to predict the current or future target velocity, and (2) a forward model of the target motion is acquired by on-line learning. We use stimulation studies to demonstrate how our new model supports these hypotheses.

link (url) [BibTex]

Shibata, T., Tabata, H., Schaal, S., Kawato, M. A model of smooth pursuit based on learning of the target dynamics using only retinal signals Neural Networks, 18, pages: 213-225, 2005, clmc (article)

link (url) [BibTex]

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Parametric and Non-Parametric approaches for nonlinear tracking of moving objects

Hidaka, Y, Theodorou, E.

Technical Report-2005-1, 2005, clmc (article)

PDF [BibTex]

Hidaka, Y, Theodorou, E. Parametric and Non-Parametric approaches for nonlinear tracking of moving objects Technical Report-2005-1, 2005, clmc (article)

PDF [BibTex]

2001

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Synchronized robot drumming by neural oscillator

Kotosaka, S., Schaal, S.

Journal of the Robotics Society of Japan, 19(1):116-123, 2001, clmc (article)

Abstract
Sensory-motor integration is one of the key issues in robotics. In this paper, we propose an approach to rhythmic arm movement control that is synchronized with an external signal based on exploiting a simple neural oscillator network. Trajectory generation by the neural oscillator is a biologically inspired method that can allow us to generate a smooth and continuous trajectory. The parameter tuning of the oscillators is used to generate a synchronized movement with wide intervals. We adopted the method for the drumming task as an example task. By using this method, the robot can realize synchronized drumming with wide drumming intervals in real time. The paper also shows the experimental results of drumming by a humanoid robot.

[BibTex]

2001

Kotosaka, S., Schaal, S. Synchronized robot drumming by neural oscillator Journal of the Robotics Society of Japan, 19(1):116-123, 2001, clmc (article)

[BibTex]

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Origins and violations of the 2/3 power law in rhythmic 3D movements

Schaal, S., Sternad, D.

Experimental Brain Research, 136, pages: 60-72, 2001, clmc (article)

Abstract
The 2/3 power law, the nonlinear relationship between tangential velocity and radius of curvature of the endeffector trajectory, has been suggested as a fundamental constraint of the central nervous system in the formation of rhythmic endpoint trajectories. However, studies on the 2/3 power law have largely been confined to planar drawing patterns of relatively small size. With the hypothesis that this strategy overlooks nonlinear effects that are constitutive in movement generation, the present experiments tested the validity of the power law in elliptical patterns which were not confined to a planar surface and which were performed by the unconstrained 7-DOF arm with significant variations in pattern size and workspace orientation. Data were recorded from five human subjects where the seven joint angles and the endpoint trajectories were analyzed. Additionally, an anthropomorphic 7-DOF robot arm served as a "control subject" whose endpoint trajectories were generated on the basis of the human joint angle data, modeled as simple harmonic oscillations. Analyses of the endpoint trajectories demonstrate that the power law is systematically violated with increasing pattern size, in both exponent and the goodness of fit. The origins of these violations can be explained analytically based on smooth rhythmic trajectory formation and the kinematic structure of the human arm. We conclude that in unconstrained rhythmic movements, the power law seems to be a by-product of a movement system that favors smooth trajectories, and that it is unlikely to serve as a primary movement generating principle. Our data rather suggests that subjects employed smooth oscillatory pattern generators in joint space to realize the required movement patterns.

link (url) [BibTex]

Schaal, S., Sternad, D. Origins and violations of the 2/3 power law in rhythmic 3D movements Experimental Brain Research, 136, pages: 60-72, 2001, clmc (article)

link (url) [BibTex]

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Graph-matching vs. entropy-based methods for object detection
Neural Networks, 14(3):345-354, 2001, clmc (article)

Abstract
Labeled Graph Matching (LGM) has been shown successful in numerous ob-ject vision tasks. This method is the basis for arguably the best face recognition system in the world. We present an algorithm for visual pattern recognition that is an extension of LGM ("LGM+"). We compare the performance of LGM and LGM+ algorithms with a state of the art statistical method based on Mutual Information Maximization (MIM). We present an adaptation of the MIM method for multi-dimensional Gabor wavelet features. The three pattern recognition methods were evaluated on an object detection task, using a set of stimuli on which none of the methods had been tested previously. The results indicate that while the performance of the MIM method operating upon Gabor wavelets is superior to the same method operating on pixels and to LGM, it is surpassed by LGM+. LGM+ offers a significant improvement in performance over LGM without losing LGMâ??s virtues of simplicity, biological plausibility, and a computational cost that is 2-3 orders of magnitude lower than that of the MIM algorithm. 

link (url) [BibTex]

Graph-matching vs. entropy-based methods for object detection Neural Networks, 14(3):345-354, 2001, clmc (article)

link (url) [BibTex]

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Biomimetic gaze stabilization based on feedback-error learning with nonparametric regression networks

Shibata, T., Schaal, S.

Neural Networks, 14(2):201-216, 2001, clmc (article)

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, stereo vision, and dealing with large information processing delays. Given the nonlinearities of the geometry of binocular vision as well as the possible nonlinearities of the oculomotor plant, it is desirable to accomplish accurate control of these behaviors through learning approaches. This paper develops a learning control system for the phylogenetically oldest behaviors of oculomotor control, the stabilization reflexes of gaze. In a step-wise procedure, we demonstrate how control theoretic reasonable choices of control components result in an oculomotor control system that resembles the known functional anatomy of the primate oculomotor system. The core of the learning system is derived from the biologically inspired principle of feedback-error learning combined with a state-of-the-art non-parametric statistical learning network. With this circuitry, we demonstrate that our humanoid robot is able to acquire high performance visual stabilization reflexes after about 40 s of learning despite significant nonlinearities and processing delays in the system.

link (url) [BibTex]

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Fast learning of biomimetic oculomotor control with nonparametric regression networks (in Japanese)

Shibata, T., Schaal, S.

Journal of the Robotics Society of Japan, 19(4):468-479, 2001, clmc (article)

[BibTex]

Shibata, T., Schaal, S. Fast learning of biomimetic oculomotor control with nonparametric regression networks (in Japanese) Journal of the Robotics Society of Japan, 19(4):468-479, 2001, clmc (article)

[BibTex]

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Bouncing a ball: Tuning into dynamic stability

Sternad, D., Duarte, M., Katsumata, H., Schaal, S.

Journal of Experimental Psychology: Human Perception and Performance, 27(5):1163-1184, 2001, clmc (article)

Abstract
Rhythmically bouncing a ball with a racket was investigated and modeled with a nonlinear map. Model analyses provided a variable defining a dynamically stable solution that obviates computationally expensive corrections. Three experiments evaluated whether dynamic stability is optimized and what perceptual support is necessary for stable behavior. Two hypotheses were tested: (a) Performance is stable if racket acceleration is negative at impact, and (b) variability is lowest at an impact acceleration between -4 and -1 m/s2. In Experiment 1 participants performed the task, eyes open or closed, bouncing a ball confined to a 1-dimensional trajectory. Experiment 2 eliminated constraints on racket and ball trajectory. Experiment 3 excluded visual or haptic information. Movements were performed with negative racket accelerations in the range of highest stability. Performance with eyes closed was more variable, leaving acceleration unaffected. With haptic information, performance was more stable than with visual information alone.

[BibTex]

Sternad, D., Duarte, M., Katsumata, H., Schaal, S. Bouncing a ball: Tuning into dynamic stability Journal of Experimental Psychology: Human Perception and Performance, 27(5):1163-1184, 2001, clmc (article)

[BibTex]

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Biomimetic oculomotor control

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

Adaptive Behavior, 9(3/4):189-207, 2001, clmc (article)

Abstract
Oculomotor control in a humanoid robot faces similar problems as biological oculomotor systems, i.e., capturing targets accurately on a very narrow fovea, dealing with large delays in the control system, the stabilization of gaze in face of unknown perturbations of the body, selective attention, and the complexity of stereo vision. In this paper, we suggest control circuits to realize three of the most basic oculomotor behaviors and their integration - 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 and the mechanism for their integration was derived with inspiration from computational theories as well as behavioral and physiological data in neuroscience. Our implementations on a humanoid robot demonstrate good performance of the oculomotor behaviors, which proves to be a viable strategy to explore novel control mechanisms for humanoid robotics. Conversely, insights gained from our models have been able to directly influence views and provide new directions for computational neuroscience research.

link (url) [BibTex]

Shibata, T., Vijayakumar, S., Conradt, J., Schaal, S. Biomimetic oculomotor control Adaptive Behavior, 9(3/4):189-207, 2001, clmc (article)

link (url) [BibTex]

2000

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A brachiating robot controller

Nakanishi, J., Fukuda, T., Koditschek, D. E.

IEEE Transactions on Robotics and Automation, 16(2):109-123, 2000, clmc (article)

Abstract
We report on our empirical studies of a new controller for a two-link brachiating robot. Motivated by the pendulum-like motion of an apeâ??s brachiation, we encode this task as the output of a â??target dynamical system.â? Numerical simulations indicate that the resulting controller solves a number of brachiation problems that we term the â??ladder,â? â??swing-up,â? and â??ropeâ? problems. Preliminary analysis provides some explanation for this success. The proposed controller is implemented on a physical system in our laboratory. The robot achieves behaviors including â??swing locomotionâ? and â??swing upâ? and is capable of continuous locomotion over several rungs of a ladder. We discuss a number of formal questions whose answers will be required to gain a full understanding of the strengths and weaknesses of this approach.

link (url) [BibTex]

2000

Nakanishi, J., Fukuda, T., Koditschek, D. E. A brachiating robot controller IEEE Transactions on Robotics and Automation, 16(2):109-123, 2000, clmc (article)

link (url) [BibTex]

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Interaction of rhythmic and discrete pattern generators in single joint movements

Sternad, D., Dean, W. J., Schaal, S.

Human Movement Science, 19(4):627-665, 2000, clmc (article)

Abstract
The study investigates a single-joint movement task that combines a translatory and cyclic component with the objective to investigate the interaction of discrete and rhythmic movement elements. Participants performed an elbow movement in the horizontal plane, oscillating at a prescribed frequency around one target and shifting to a second target upon a trigger signal, without stopping the oscillation. Analyses focused on extracting the mutual influences of the rhythmic and the discrete component of the task. Major findings are: (1) The onset of the discrete movement was confined to a limited phase window in the rhythmic cycle. (2) Its duration was influenced by the period of oscillation. (3) The rhythmic oscillation was "perturbed" by the discrete movement as indicated by phase resetting. On the basis of these results we propose a model for the coordination of discrete and rhythmic actions (K. Matsuoka, Sustained oscillations generated by mutually inhibiting neurons with adaptations, Biological Cybernetics 52 (1985) 367-376; Mechanisms of frequency and pattern control in the neural rhythm generators, Biological Cybernetics 56 (1987) 345-353). For rhythmic movements an oscillatory pattern generator is developed following models of half-center oscillations (D. Bullock, S. Grossberg, The VITE model: a neural command circuit for generating arm and articulated trajectories, in: J.A.S. Kelso, A.J. Mandel, M. F. Shlesinger (Eds.), Dynamic Patterns in Complex Systems. World Scientific. Singapore. 1988. pp. 305-326). For discrete movements a point attractor dynamics is developed close to the VITE model For each joint degree of freedom both pattern generators co-exist but exert mutual inhibition onto each other. The suggested modeling framework provides a unified account for both discrete and rhythmic movements on the basis of neuronal circuitry. Simulation results demonstrated that the effects observed in human performance can be replicated using the two pattern generators with a mutually inhibiting coupling.

link (url) [BibTex]

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Dynamics of a bouncing ball in human performance

Sternad, D., Duarte, M., Katsumata, H., Schaal, S.

Physical Review E, 63(011902):1-8, 2000, clmc (article)

Abstract
On the basis of a modified bouncing-ball model, we investigated whether human movements utilize principles of dynamic stability in their performance of a similar movement task. Stability analyses of the model provided predictions about conditions indicative of a dynamically stable period-one regime. In a series of experiments, human subjects bounced a ball rhythmically on a racket and displayed these conditions supporting that they attuned to and exploited the dynamic stability properties of the task.

link (url) [BibTex]

Sternad, D., Duarte, M., Katsumata, H., Schaal, S. Dynamics of a bouncing ball in human performance Physical Review E, 63(011902):1-8, 2000, clmc (article)

link (url) [BibTex]

1999

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Is imitation learning the route to humanoid robots?

Schaal, S.

Trends in Cognitive Sciences, 3(6):233-242, 1999, clmc (article)

Abstract
This review will focus on two recent developments in artificial intelligence and neural computation: learning from imitation and the development of humanoid robots. It will be postulated that the study of imitation learning offers a promising route to gain new insights into mechanisms of perceptual motor control that could ultimately lead to the creation of autonomous humanoid robots. This hope is justified because imitation learning channels research efforts towards three important issues: efficient motor learning, the connection between action and perception, and modular motor control in form of movement primitives. In order to make these points, first, a brief review of imitation learning will be given from the view of psychology and neuroscience. In these fields, representations and functional connections between action and perception have been explored that contribute to the understanding of motor acts of other beings. The recent discovery that some areas in the primate brain are active during both movement perception and execution provided a first idea of the possible neural basis of imitation. Secondly, computational approaches to imitation learning will be described, initially from the perspective of traditional AI and robotics, and then with a focus on neural network models and statistical learning research. Parallels and differences between biological and computational approaches to imitation will be highlighted. The review will end with an overview of current projects that actually employ imitation learning for humanoid robots.

link (url) [BibTex]

1999

Schaal, S. Is imitation learning the route to humanoid robots? Trends in Cognitive Sciences, 3(6):233-242, 1999, clmc (article)

link (url) [BibTex]

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Segmentation of endpoint trajectories does not imply segmented control

Sternad, D., Schaal, D.

Experimental Brain Research, 124(1):118-136, 1999, clmc (article)

Abstract
While it is generally assumed that complex movements consist of a sequence of simpler units, the quest to define these units of action, or movement primitives, still remains an open question. In this context, two hypotheses of movement segmentation of endpoint trajectories in 3D human drawing movements are re-examined: (1) the stroke-based segmentation hypothesis based on the results that the proportionality coefficient of the 2/3 power law changes discontinuously with each new â??strokeâ?, and (2) the segmentation hypothesis inferred from the observation of piecewise planar endpoint trajectories of 3D drawing movements. In two experiments human subjects performed a set of elliptical and figure-8 patterns of different sizes and orientations using their whole arm in 3D. The kinematic characteristics of the endpoint trajectories and the seven joint angles of the arm were analyzed. While the endpoint trajectories produced similar segmentation features as reported in the literature, analyses of the joint angles show no obvious segmentation but rather continuous oscillatory patterns. By approximating the joint angle data of human subjects with sinusoidal trajectories, and by implementing this model on a 7-degree-of-freedom anthropomorphic robot arm, it is shown that such a continuous movement strategy can produce exactly the same features as observed by the above segmentation hypotheses. The origin of this apparent segmentation of endpoint trajectories is traced back to the nonlinear transformations of the forward kinematics of human arms. The presented results demonstrate that principles of discrete movement generation may not be reconciled with those of rhythmic movement as easily as has been previously suggested, while the generalization of nonlinear pattern generators to arm movements can offer an interesting alternative to approach the question of units of action.

link (url) [BibTex]

Sternad, D., Schaal, D. Segmentation of endpoint trajectories does not imply segmented control Experimental Brain Research, 124(1):118-136, 1999, clmc (article)

link (url) [BibTex]