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2016


A New Perspective and Extension of the Gaussian Filter
A New Perspective and Extension of the Gaussian Filter

Wüthrich, M., Trimpe, S., Garcia Cifuentes, C., Kappler, D., Schaal, S.

The International Journal of Robotics Research, 35(14):1731-1749, December 2016 (article)

Abstract
The Gaussian Filter (GF) is one of the most widely used filtering algorithms; instances are the Extended Kalman Filter, the Unscented Kalman Filter and the Divided Difference Filter. The GF represents the belief of the current state by a Gaussian distribution, whose mean is an affine function of the measurement. We show that this representation can be too restrictive to accurately capture the dependences in systems with nonlinear observation models, and we investigate how the GF can be generalized to alleviate this problem. To this end, we view the GF as the solution to a constrained optimization problem. From this new perspective, the GF is seen as a special case of a much broader class of filters, obtained by relaxing the constraint on the form of the approximate posterior. On this basis, we outline some conditions which potential generalizations have to satisfy in order to maintain the computational efficiency of the GF. We propose one concrete generalization which corresponds to the standard GF using a pseudo measurement instead of the actual measurement. Extending an existing GF implementation in this manner is trivial. Nevertheless, we show that this small change can have a major impact on the estimation accuracy.

PDF DOI Project Page [BibTex]

2016

PDF DOI Project Page [BibTex]


Implications of Action-Oriented Paradigm Shifts in Cognitive Science
Implications of Action-Oriented Paradigm Shifts in Cognitive Science

Dominey, P. F., Prescott, T. J., Bohg, J., Engel, A. K., Gallagher, S., Heed, T., Hoffmann, M., Knoblich, G., Prinz, W., Schwartz, A.

In The Pragmatic Turn - Toward Action-Oriented Views in Cognitive Science, 18, pages: 333-356, 20, Strüngmann Forum Reports, vol. 18, J. Lupp, series editor, (Editors: Andreas K. Engel and Karl J. Friston and Danica Kragic), The MIT Press, 18th Ernst Strüngmann Forum, May 2016 (incollection) In press

Abstract
An action-oriented perspective changes the role of an individual from a passive observer to an actively engaged agent interacting in a closed loop with the world as well as with others. Cognition exists to serve action within a landscape that contains both. This chapter surveys this landscape and addresses the status of the pragmatic turn. Its potential influence on science and the study of cognition are considered (including perception, social cognition, social interaction, sensorimotor entrainment, and language acquisition) and its impact on how neuroscience is studied is also investigated (with the notion that brains do not passively build models, but instead support the guidance of action). A review of its implications in robotics and engineering includes a discussion of the application of enactive control principles to couple action and perception in robotics as well as the conceptualization of system design in a more holistic, less modular manner. Practical applications that can impact the human condition are reviewed (e.g. educational applications, treatment possibilities for developmental and psychopathological disorders, the development of neural prostheses). All of this foreshadows the potential societal implications of the pragmatic turn. The chapter concludes that an action-oriented approach emphasizes a continuum of interaction between technical aspects of cognitive systems and robotics, biology, psychology, the social sciences, and the humanities, where the individual is part of a grounded cultural system.

The Pragmatic Turn - Toward Action-Oriented Views in Cognitive Science 18th Ernst Strüngmann Forum Bibliography Chapter link (url) [BibTex]

The Pragmatic Turn - Toward Action-Oriented Views in Cognitive Science 18th Ernst Strüngmann Forum Bibliography Chapter link (url) [BibTex]


Learning Action-Perception Cycles in Robotics: A Question of Representations and Embodiment
Learning Action-Perception Cycles in Robotics: A Question of Representations and Embodiment

Bohg, J., Kragic, D.

In The Pragmatic Turn - Toward Action-Oriented Views in Cognitive Science, 18, pages: 309-320, 18, Strüngmann Forum Reports, vol. 18, J. Lupp, series editor, (Editors: Andreas K. Engel and Karl J. Friston and Danica Kragic), The MIT Press, 18th Ernst Strüngmann Forum, May 2016 (incollection) In press

Abstract
Since the 1950s, robotics research has sought to build a general-purpose agent capable of autonomous, open-ended interaction with realistic, unconstrained environments. Cognition is perceived to be at the core of this process, yet understanding has been challenged because cognition is referred to differently within and across research areas, and is not clearly defined. The classic robotics approach is decomposition into functional modules which perform planning, reasoning, and problem-solving or provide input to these mechanisms. Although advancements have been made and numerous success stories reported in specific niches, this systems-engineering approach has not succeeded in building such a cognitive agent. The emergence of an action-oriented paradigm offers a new approach: action and perception are no longer separable into functional modules but must be considered in a complete loop. This chapter reviews work on different mechanisms for action- perception learning and discusses the role of embodiment in the design of the underlying representations and learning. It discusses the evaluation of agents and suggests the development of a new embodied Turing Test. Appropriate scenarios need to be devised in addition to current competitions, so that abilities can be tested over long time periods.

18th Ernst Strüngmann Forum The Pragmatic Turn- Toward Action-Oriented Views in Cognitive Science Bibliography Chapter link (url) [BibTex]

18th Ernst Strüngmann Forum The Pragmatic Turn- Toward Action-Oriented Views in Cognitive Science Bibliography Chapter link (url) [BibTex]


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Probabilistic Inference for Determining Options in Reinforcement Learning

Daniel, C., van Hoof, H., Peters, J., Neumann, G.

Machine Learning, Special Issue, 104(2):337-357, (Editors: Gärtner, T., Nanni, M., Passerini, A. and Robardet, C.), European Conference on Machine Learning im Machine Learning, Journal Track, 2016, Best Student Paper Award of ECML-PKDD 2016 (article)

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Locally Weighted Regression for Control

Ting, J., Meier, F., Vijayakumar, S., Schaal, S.

In Encyclopedia of Machine Learning and Data Mining, pages: 1-14, Springer US, Boston, MA, 2016 (inbook)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Event-based Sampling for Reducing Communication Load in Realtime Human Motion Analysis by Wireless Inertial Sensor Networks

Laidig, D., Trimpe, S., Seel, T.

Current Directions in Biomedical Engineering, 2(1):711-714, De Gruyter, 2016 (article)

PDF DOI [BibTex]

PDF DOI [BibTex]


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Momentum Control with Hierarchical Inverse Dynamics on a Torque-Controlled Humanoid

Herzog, A., Rotella, N., Mason, S., Grimminger, F., Schaal, S., Righetti, L.

Autonomous Robots, 40(3):473-491, 2016 (article)

Abstract
Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled humanoid where model inaccuracies, sensor noise and real-time computation requirements can be problematic. Using a reformulation of existing algorithms, we propose a simplification of the problem that allows to achieve real-time control. Momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior and improve performance. Extensive experiments on various balancing and tracking tasks show very robust performance in the face of unknown disturbances, even when the humanoid is standing on one foot. Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.

link (url) DOI [BibTex]


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Bioinspired Motor Control for Articulated Robots [From the Guest Editors]

Vitiello, Nicola, Ijspeert, Auke J, Schaal, S.

IEEE Robotics {\&} Automation Magazine, 23(1):20-21, 2016 (article)

[BibTex]

[BibTex]

2015


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Lernende Roboter

Trimpe, S.

In Jahrbuch der Max-Planck-Gesellschaft, Max Planck Society, May 2015, (popular science article in German) (inbook)

link (url) [BibTex]

2015

link (url) [BibTex]


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Autonomous Robots

Schaal, S.

In Jahrbuch der Max-Planck-Gesellschaft, May 2015 (incollection)

[BibTex]

[BibTex]


Sensory synergy as environmental input integration
Sensory synergy as environmental input integration

Alnajjar, F., Itkonen, M., Berenz, V., Tournier, M., Nagai, C., Shimoda, S.

Frontiers in Neuroscience, 8, pages: 436, 2015 (article)

Abstract
The development of a method to feed proper environmental inputs back to the central nervous system (CNS) remains one of the challenges in achieving natural movement when part of the body is replaced with an artificial device. Muscle synergies are widely accepted as a biologically plausible interpretation of the neural dynamics between the CNS and the muscular system. Yet the sensorineural dynamics of environmental feedback to the CNS has not been investigated in detail. In this study, we address this issue by exploring the concept of sensory synergy. In contrast to muscle synergy, we hypothesize that sensory synergy plays an essential role in integrating the overall environmental inputs to provide low-dimensional information to the CNS. We assume that sensor synergy and muscle synergy communicate using these low-dimensional signals. To examine our hypothesis, we conducted posture control experiments involving lateral disturbance with 9 healthy participants. Proprioceptive information represented by the changes on muscle lengths were estimated by using the musculoskeletal model analysis software SIMM. Changes on muscles lengths were then used to compute sensory synergies. The experimental results indicate that the environmental inputs were translated into the two dimensional signals and used to move the upper limb to the desired position immediately after the lateral disturbance. Participants who showed high skill in posture control were found to be likely to have a strong correlation between sensory and muscle signaling as well as high coordination between the utilized sensory synergies. These results suggest the importance of integrating environmental inputs into suitable low-dimensional signals before providing them to the CNS. This mechanism should be essential when designing the prosthesis’ sensory system to make the controller simpler

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Active Reward Learning with a Novel Acquisition Function

Daniel, C., Kroemer, O., Viering, M., Metz, J., Peters, J.

Autonomous Robots, 39(3):389-405, 2015 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Learning Movement Primitive Attractor Goals and Sequential Skills from Kinesthetic Demonstrations

Manschitz, S., Kober, J., Gienger, M., Peters, J.

Robotics and Autonomous Systems, 74, Part A, pages: 97-107, 2015 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Bayesian Optimization for Learning Gaits under Uncertainty

Calandra, R., Seyfarth, A., Peters, J., Deisenroth, M.

Annals of Mathematics and Artificial Intelligence, pages: 1-19, 2015 (article)

DOI [BibTex]

DOI [BibTex]


Tacit Learning for Emergence of Task-Related Behaviour through Signal Accumulation
Tacit Learning for Emergence of Task-Related Behaviour through Signal Accumulation

Berenz, V., Alnajjar, F., Hayashibe, M., Shimoda, S.

In Emergent Trends in Robotics and Intelligent Systems: Where is the Role of Intelligent Technologies in the Next Generation of Robots?, pages: 31-38, Springer International Publishing, Cham, 2015 (inbook)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Robot Learning

Peters, J., Lee, D., Kober, J., Nguyen-Tuong, D., Bagnell, J. A., Schaal, S.

In Springer Handbook of Robotics 2nd Edition, pages: 1371-1394, Springer Berlin Heidelberg, Berlin, Heidelberg, 2015 (incollection)

[BibTex]

[BibTex]

2011


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Learning, planning, and control for quadruped locomotion over challenging terrain

Kalakrishnan, Mrinal, Buchli, Jonas, Pastor, Peter, Mistry, Michael, Schaal, S.

International Journal of Robotics Research, 30(2):236-258, February 2011 (article)

[BibTex]

2011

[BibTex]


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Bayesian robot system identification with input and output noise

Ting, J., D’Souza, A., Schaal, S.

Neural Networks, 24(1):99-108, 2011, clmc (article)

Abstract
For complex robots such as humanoids, model-based control is highly beneficial for accurate tracking while keeping negative feedback gains low for compliance. However, in such multi degree-of-freedom lightweight systems, conventional identification of rigid body dynamics models using CAD data and actuator models is inaccurate due to unknown nonlinear robot dynamic effects. An alternative method is data-driven parameter estimation, but significant noise in measured and inferred variables affects it adversely. Moreover, standard estimation procedures may give physically inconsistent results due to unmodeled nonlinearities or insufficiently rich data. This paper addresses these problems, proposing a Bayesian system identification technique for linear or piecewise linear systems. Inspired by Factor Analysis regression, we develop a computationally efficient variational Bayesian regression algorithm that is robust to ill-conditioned data, automatically detects relevant features, and identifies input and output noise. We evaluate our approach on rigid body parameter estimation for various robotic systems, achieving an error of up to three times lower than other state-of-the-art machine learning methods

link (url) [BibTex]

link (url) [BibTex]


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Learning variable impedance control

Buchli, J., Stulp, F., Theodorou, E., Schaal, S.

International Journal of Robotics Research, 2011, clmc (article)

Abstract
One of the hallmarks of the performance, versatility, and robustness of biological motor control is the ability to adapt the impedance of the overall biomechanical system to different task requirements and stochastic disturbances. A transfer of this principle to robotics is desirable, for instance to enable robots to work robustly and safely in everyday human environments. It is, however, not trivial to derive variable impedance controllers for practical high degree-of-freedom (DOF) robotic tasks. In this contribution, we accomplish such variable impedance control with the reinforcement learning (RL) algorithm PISq ({f P}olicy {f I}mprovement with {f P}ath {f I}ntegrals). PISq is a model-free, sampling based learning method derived from first principles of stochastic optimal control. The PISq algorithm requires no tuning of algorithmic parameters besides the exploration noise. The designer can thus fully focus on cost function design to specify the task. From the viewpoint of robotics, a particular useful property of PISq is that it can scale to problems of many DOFs, so that reinforcement learning on real robotic systems becomes feasible. We sketch the PISq algorithm and its theoretical properties, and how it is applied to gain scheduling for variable impedance control. We evaluate our approach by presenting results on several simulated and real robots. We consider tasks involving accurate tracking through via-points, and manipulation tasks requiring physical contact with the environment. In these tasks, the optimal strategy requires both tuning of a reference trajectory emph{and} the impedance of the end-effector. The results show that we can use path integral based reinforcement learning not only for planning but also to derive variable gain feedback controllers in realistic scenarios. Thus, the power of variable impedance control is made available to a wide variety of robotic systems and practical applications.

link (url) [BibTex]

link (url) [BibTex]


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Understanding haptics by evolving mechatronic systems

Loeb, G. E., Tsianos, G.A., Fishel, J.A., Wettels, N., Schaal, S.

Progress in Brain Research, 192, pages: 129, 2011 (article)

[BibTex]

[BibTex]


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Intelligent Mobility—Autonomous Outdoor Robotics at the DFKI

Joyeux, S., Schwendner, J., Kirchner, F., Babu, A., Grimminger, F., Machowinski, J., Paranhos, P., Gaudig, C.

KI, 25(2):133-139, May 2011 (article)

DOI [BibTex]

DOI [BibTex]

2003


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Computational approaches to motor learning by imitation

Schaal, S., Ijspeert, A., Billard, A.

Philosophical Transaction of the Royal Society of London: Series B, Biological Sciences, 358(1431):537-547, 2003, clmc (article)

Abstract
Movement imitation requires a complex set of mechanisms that map an observed movement of a teacher onto one's own movement apparatus. Relevant problems include movement recognition, pose estimation, pose tracking, body correspondence, coordinate transformation from external to egocentric space, matching of observed against previously learned movement, resolution of redundant degrees-of-freedom that are unconstrained by the observation, suitable movement representations for imitation, modularization of motor control, etc. All of these topics by themselves are active research problems in computational and neurobiological sciences, such that their combination into a complete imitation system remains a daunting undertaking - indeed, one could argue that we need to understand the complete perception-action loop. As a strategy to untangle the complexity of imitation, this paper will examine imitation purely from a computational point of view, i.e. we will review statistical and mathematical approaches that have been suggested for tackling parts of the imitation problem, and discuss their merits, disadvantages and underlying principles. Given the focus on action recognition of other contributions in this special issue, this paper will primarily emphasize the motor side of imitation, assuming that a perceptual system has already identified important features of a demonstrated movement and created their corresponding spatial information. Based on the formalization of motor control in terms of control policies and their associated performance criteria, useful taxonomies of imitation learning can be generated that clarify different approaches and future research directions.

link (url) [BibTex]

2003

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

link (url) [BibTex]


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Biomimetic gaze stabilization

Shibata, T., Schaal, S.

In Robot learning: an Interdisciplinary approach, pages: 31-52, (Editors: Demiris, J.;Birk, A.), World Scientific, 2000, clmc (inbook)

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.

link (url) [BibTex]

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]

link (url) [BibTex]

1993


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Learning passive motor control strategies with genetic algorithms

Schaal, S., Sternad, D.

In 1992 Lectures in complex systems, pages: 913-918, (Editors: Nadel, L.;Stein, D.), Addison-Wesley, Redwood City, CA, 1993, clmc (inbook)

Abstract
This study investigates learning passive motor control strategies. Passive control is understood as control without active error correction; the movement is stabilized by particular properties of the controlling dynamics. We analyze the task of juggling a ball on a racket. An approximation to the optimal solution of the task is derived by means of optimization theory. In order to model the learning process, the problem is coded for a genetic algorithm in representations without sensory or with sensory information. For all representations the genetic algorithm is able to find passive control strategies, but learning speed and the quality of the outcome are significantly different. A comparison with data from human subjects shows that humans seem to apply yet different movement strategies to the ones proposed. For the feedback representation some implications arise for learning from demonstration.

link (url) [BibTex]

1993

link (url) [BibTex]


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A genetic algorithm for evolution from an ecological perspective

Sternad, D., Schaal, S.

In 1992 Lectures in Complex Systems, pages: 223-231, (Editors: Nadel, L.;Stein, D.), Addison-Wesley, Redwood City, CA, 1993, clmc (inbook)

Abstract
In the population model presented, an evolutionary dynamic is explored which is based on the operator characteristics of genetic algorithms. An essential modification in the genetic algorithms is the inclusion of a constraint in the mixing of the gene pool. The pairing for the crossover is governed by a selection principle based on a complementarity criterion derived from the theoretical tenet of perception-action (P-A) mutuality of ecological psychology. According to Swenson and Turvey [37] P-A mutuality underlies evolution and is an integral part of its thermodynamics. The present simulation tested the contribution of P-A-cycles in evolutionary dynamics. A numerical experiment compares the population's evolution with and without this intentional component. The effect is measured in the difference of the rate of energy dissipation, as well as in three operationalized aspects of complexity. The results support the predicted increase in the rate of energy dissipation, paralleled by an increase in the average heterogeneity of the population. Furthermore, the spatio-temporal evolution of the system is tested for the characteristic power-law relations of a nonlinear system poised in a critical state. The frequency distribution of consecutive increases in population size shows a significantly different exponent in functional relationship.

[BibTex]

[BibTex]


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Design concurrent calculation: A CAD- and data-integrated approach

Schaal, S., Ehrlenspiel, K.

Journal of Engineering Design, 4, pages: 71-85, 1993, clmc (article)

Abstract
Besides functional regards, product design demands increasingly more for further reaching considerations. Quality alone cannot suffice anymore to compete in the market; design for manufacturability, for assembly, for recycling, etc., are well-known keywords. Those can largely be reduced to the necessity of design for costs. This paper focuses on a CAD-based approach to design concurrent calculation. It will discuss how, in the meantime well-established, tools like feature technology, knowledge-based systems, and relational databases can be blended into one coherent concept to achieve an entirely CAD- and data-integrated cost information tool. This system is able to extract data from the CAD-system, combine it with data about the company specific manufacturing environment, and subsequently autonomously evaluate manufacturability aspects and costs of the given CAD-model. Within minutes the designer gets quantitative in-formation about the major cost sources of his/her design. Additionally, some alternative methods for approximating manu-facturing times from empirical data, namely neural networks and local weighted regression, are introduced.

[BibTex]

[BibTex]

1992


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Ins CAD integrierte Kostenkalkulation (CAD-Integrated Cost Calculation)

Ehrlenspiel, K., Schaal, S.

Konstruktion 44, 12, pages: 407-414, 1992, clmc (article)

[BibTex]

1992

[BibTex]


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Informationssysteme mit CAD (Information systems within CAD)

Schaal, S.

In CAD/CAM Grundlagen, pages: 199-204, (Editors: Milberg, J.), Springer, Buchreihe CIM-TT. Berlin, 1992, clmc (inbook)

[BibTex]

[BibTex]