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2019


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Interactive Augmented Reality for Robot-Assisted Surgery

Forte, M. P., Kuchenbecker, K. J.

Workshop extended abstract presented as a podium presentation at the IROS Workshop on Legacy Disruptors in Applied Telerobotics, Macau, November 2019 (misc) Accepted

hi

Project Page [BibTex]

2019


Project Page [BibTex]


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High-Fidelity Multiphysics Finite Element Modeling of Finger-Surface Interactions with Tactile Feedback

Serhat, G., Kuchenbecker, K. J.

Work-in-progress paper (2 pages) presented at the IEEE World Haptics Conference (WHC), Tokyo, Japan, July 2019 (misc)

Abstract
In this study, we develop a high-fidelity finite element (FE) analysis framework that enables multiphysics simulation of the human finger in contact with a surface that is providing tactile feedback. We aim to elucidate a variety of physical interactions that can occur at finger-surface interfaces, including contact, friction, vibration, and electrovibration. We also develop novel FE-based methods that will allow prediction of nonconventional features such as real finger-surface contact area and finger stickiness. We envision using the developed computational tools for efficient design and optimization of haptic devices by replacing expensive and lengthy experimental procedures with high-fidelity simulation.

hi

[BibTex]

[BibTex]


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Fingertip Friction Enhances Perception of Normal Force Changes

Gueorguiev, D., Lambert, J., Thonnard, J., Kuchenbecker, K. J.

Work-in-progress paper (2 pages) presented at the IEEE World Haptics Conference (WHC), Tokyo, Japan, July 2019 (misc)

Abstract
Using a force-controlled robotic platform, we tested the human perception of positive and negative modulations in normal force during passive dynamic touch, which also induced a strong related change in the finger-surface lateral force. In a two-alternative forced-choice task, eleven participants had to detect brief variations in the normal force compared to a constant controlled pre-stimulation force of 1 N and report whether it had increased or decreased. The average 75% just noticeable difference (JND) was found to be around 0.25 N for detecting the peak change and 0.30 N for correctly reporting the increase or the decrease. Interestingly, the friction coefficient of a subject’s fingertip positively correlated with his or her performance at detecting the change and reporting its direction, which suggests that humans may use the lateral force as a sensory cue to perceive variations in the normal force.

hi

[BibTex]

[BibTex]


Inflatable Haptic Sensor for the Torso of a Hugging Robot
Inflatable Haptic Sensor for the Torso of a Hugging Robot

Block, A. E., Kuchenbecker, K. J.

Work-in-progress paper (2 pages) presented at the IEEE World Haptics Conference (WHC), Tokyo, Japan, July 2019 (misc)

Abstract
During hugs, humans naturally provide and intuit subtle non-verbal cues that signify the strength and duration of an exchanged hug. Personal preferences for this close interaction may vary greatly between people; robots do not currently have the abilities to perceive or understand these preferences. This work-in-progress paper discusses designing, building, and testing a novel inflatable torso that can simultaneously soften a robot and act as a tactile sensor to enable more natural and responsive hugging. Using PVC vinyl, a microphone, and a barometric pressure sensor, we created a small test chamber to demonstrate a proof of concept for the full torso. While contacting the chamber in several ways common in hugs (pat, squeeze, scratch, and rub), we recorded data from the two sensors. The preliminary results suggest that the complementary haptic sensing channels allow us to detect coarse and fine contacts typically experienced during hugs, regardless of user hand placement.

hi

Project Page [BibTex]

Project Page [BibTex]


Understanding the Pull-off Force of the Human Fingerpad
Understanding the Pull-off Force of the Human Fingerpad

Nam, S., Kuchenbecker, K. J.

Work-in-progress paper (2 pages) presented at the IEEE World Haptics Conference (WHC), Tokyo, Japan, July 2019 (misc)

Abstract
To understand the adhesive force that occurs when a finger pulls off of a smooth surface, we built an apparatus to measure the fingerpad’s moisture, normal force, and real contact area over time during interactions with a glass plate. We recorded a total of 450 trials (45 interactions by each of ten human subjects), capturing a wide range of values across the aforementioned variables. The experimental results showed that the pull-off force increases with larger finger contact area and faster detachment rate. Additionally, moisture generally increases the contact area of the finger, but too much moisture can restrict the increase in the pull-off force.

hi

[BibTex]

[BibTex]


The Haptician and the Alphamonsters
The Haptician and the Alphamonsters

Forte, M. P., L’Orsa, R., Mohan, M., Nam, S., Kuchenbecker, K. J.

Student Innovation Challenge on Implementing Haptics in Virtual Reality Environment presented at the IEEE World Haptics Conference, Tokyo, Japan, July 2019, Maria Paola Forte, Rachael L'Orsa, Mayumi Mohan, and Saekwang Nam contributed equally to this publication (misc)

Abstract
Dysgraphia is a neurological disorder characterized by writing disabilities that affects between 7% and 15% of children. It presents itself in the form of unfinished letters, letter distortion, inconsistent letter size, letter collision, etc. Traditional therapeutic exercises require continuous assistance from teachers or occupational therapists. Autonomous partial or full haptic guidance can produce positive results, but children often become bored with the repetitive nature of such activities. Conversely, virtual rehabilitation with video games represents a new frontier for occupational therapy due to its highly motivational nature. Virtual reality (VR) adds an element of novelty and entertainment to therapy, thus motivating players to perform exercises more regularly. We propose leveraging the HTC VIVE Pro and the EXOS Wrist DK2 to create an immersive spellcasting “exergame” (exercise game) that helps motivate children with dysgraphia to improve writing fluency.

hi

Student Innovation Challenge – Virtual Reality [BibTex]

Student Innovation Challenge – Virtual Reality [BibTex]


Implementation of a 6-{DOF} Parallel Continuum Manipulator for Delivering Fingertip Tactile Cues
Implementation of a 6-DOF Parallel Continuum Manipulator for Delivering Fingertip Tactile Cues

Young, E. M., Kuchenbecker, K. J.

IEEE Transactions on Haptics, 12(3):295-306, June 2019 (article)

Abstract
Existing fingertip haptic devices can deliver different subsets of tactile cues in a compact package, but we have not yet seen a wearable six-degree-of-freedom (6-DOF) display. This paper presents the Fuppeteer (short for Fingertip Puppeteer), a device that is capable of controlling the position and orientation of a flat platform, such that any combination of normal and shear force can be delivered at any location on any human fingertip. We build on our previous work of designing a parallel continuum manipulator for fingertip haptics by presenting a motorized version in which six flexible Nitinol wires are actuated via independent roller mechanisms and proportional-derivative controllers. We evaluate the settling time and end-effector vibrations observed during system responses to step inputs. After creating a six-dimensional lookup table and adjusting simulated inputs using measured Jacobians, we show that the device can make contact with all parts of the fingertip with a mean error of 1.42 mm. Finally, we present results from a human-subject study. A total of 24 users discerned 9 evenly distributed contact locations with an average accuracy of 80.5%. Translational and rotational shear cues were identified reasonably well near the center of the fingertip and more poorly around the edges.

hi

DOI [BibTex]


Explorations of Shape-Changing Haptic Interfaces for Blind and Sighted Pedestrian Navigation
Explorations of Shape-Changing Haptic Interfaces for Blind and Sighted Pedestrian Navigation

Spiers, A., Kuchenbecker, K. J.

pages: 6, Workshop paper (6 pages) presented at the CHI 2019 Workshop on Hacking Blind Navigation, May 2019 (misc) Accepted

Abstract
Since the 1960s, technologists have worked to develop systems that facilitate independent navigation by vision-impaired (VI) pedestrians. These devices vary in terms of conveyed information and feedback modality. Unfortunately, many such prototypes never progress beyond laboratory testing. Conversely, smartphone-based navigation systems for sighted pedestrians have grown in robustness and capabilities, to the point of now being ubiquitous. How can we leverage the success of sighted navigation technology, which is driven by a larger global market, as a way to progress VI navigation systems? We believe one possibility is to make common devices that benefit both VI and sighted individuals, by providing information in a way that does not distract either user from their tasks or environment. To this end we have developed physical interfaces that eschew visual, audio or vibratory feedback, instead relying on the natural human ability to perceive the shape of a handheld object.

hi

[BibTex]

[BibTex]


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Bimanual Wrist-Squeezing Haptic Feedback Changes Speed-Force Tradeoff in Robotic Surgery Training

Cao, E., Machaca, S., Bernard, T., Wolfinger, B., Patterson, Z., Chi, A., Adrales, G. L., Kuchenbecker, K. J., Brown, J. D.

Extended abstract presented as an ePoster at the Annual Meeting of the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES), Baltimore, USA, April 2019 (misc) Accepted

hi

[BibTex]

[BibTex]


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Interactive Augmented Reality for Robot-Assisted Surgery

Forte, M. P., Kuchenbecker, K. J.

Extended abstract presented as an Emerging Technology ePoster at the Annual Meeting of the Society of American Gastrointestinal and Endoscopic Surgeons (SAGES), Baltimore, Maryland, USA, April 2019 (misc) Accepted

hi

Project Page [BibTex]

Project Page [BibTex]


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A Design Tool for Therapeutic Social-Physical Human-Robot Interactions

Mohan, M., Kuchenbecker, K. J.

Workshop paper (3 pages) presented at the HRI Pioneers Workshop, Daegu, South Korea, March 2019 (misc)

Abstract
We live in an aging society; social-physical human-robot interaction has the potential to keep our elderly adults healthy by motivating them to exercise. After summarizing prior work, this paper proposes a tool that can be used to design exercise and therapy interactions to be performed by an upper-body humanoid robot. The interaction design tool comprises a teleoperation system that transmits the operator’s arm motions, head motions and facial expression along with an interface to monitor and assess the motion of the user interacting with the robot. We plan to use this platform to create dynamic and intuitive exercise interactions.

hi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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How Does It Feel to Clap Hands with a Robot?

Fitter, N. T., Kuchenbecker, K. J.

International Journal of Social Robotics, 2019 (article) Accepted

Abstract
Future robots may need lighthearted physical interaction capabilities to connect with people in meaningful ways. To begin exploring how users perceive playful human–robot hand-to-hand interaction, we conducted a study with 20 participants. Each user played simple hand-clapping games with the Rethink Robotics Baxter Research Robot during a 1-h-long session involving 24 randomly ordered conditions that varied in facial reactivity, physical reactivity, arm stiffness, and clapping tempo. Survey data and experiment recordings demonstrate that this interaction is viable: all users successfully completed the experiment and mentioned enjoying at least one game without prompting. Hand-clapping tempo was highly salient to users, and human-like robot errors were more widely accepted than mechanical errors. Furthermore, perceptions of Baxter varied in the following statistically significant ways: facial reactivity increased the robot’s perceived pleasantness and energeticness; physical reactivity decreased pleasantness, energeticness, and dominance; higher arm stiffness increased safety and decreased dominance; and faster tempo increased energeticness and increased dominance. These findings can motivate and guide roboticists who want to design social–physical human–robot interactions.

hi

[BibTex]

[BibTex]


Toward Expert-Sourcing of a Haptic Device Repository
Toward Expert-Sourcing of a Haptic Device Repository

Seifi, H., Ip, J., Agrawal, A., Kuchenbecker, K. J., MacLean, K. E.

Glasgow, UK, 2019 (misc)

Abstract
Haptipedia is an online taxonomy, database, and visualization that aims to accelerate ideation of new haptic devices and interactions in human-computer interaction, virtual reality, haptics, and robotics. The current version of Haptipedia (105 devices) was created through iterative design, data entry, and evaluation by our team of experts. Next, we aim to greatly increase the number of devices and keep Haptipedia updated by soliciting data entry and verification from haptics experts worldwide.

hi

link (url) [BibTex]

link (url) [BibTex]


Automated Generation of Reactive Programs from Human Demonstration for Orchestration of Robot Behaviors
Automated Generation of Reactive Programs from Human Demonstration for Orchestration of Robot Behaviors

Berenz, V., Bjelic, A., Mainprice, J.

ArXiv, 2019 (article)

Abstract
Social robots or collaborative robots that have to interact with people in a reactive way are difficult to program. This difficulty stems from the different skills required by the programmer: to provide an engaging user experience the behavior must include a sense of aesthetics while robustly operating in a continuously changing environment. The Playful framework allows composing such dynamic behaviors using a basic set of action and perception primitives. Within this framework, a behavior is encoded as a list of declarative statements corresponding to high-level sensory-motor couplings. To facilitate non-expert users to program such behaviors, we propose a Learning from Demonstration (LfD) technique that maps motion capture of humans directly to a Playful script. The approach proceeds by identifying the sensory-motor couplings that are active at each step using the Viterbi path in a Hidden Markov Model (HMM). Given these activation patterns, binary classifiers called evaluations are trained to associate activations to sensory data. Modularity is increased by clustering the sensory-motor couplings, leading to a hierarchical tree structure. The novelty of the proposed approach is that the learned behavior is encoded not in terms of trajectories in a task space, but as couplings between sensory information and high-level motor actions. This provides advantages in terms of behavioral generalization and reactivity displayed by the robot.

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Support Video link (url) [BibTex]

2012


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From Dynamic Movement Primitives to Associative Skill Memories

Pastor, P., Kalakrishnan, M., Meier, F., Stulp, F., Buchli, J., Theodorou, E., Schaal, S.

Robotics and Autonomous Systems, 2012 (article)

am

Project Page [BibTex]

2012


Project Page [BibTex]


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Model-free reinforcement learning of impedance control in stochastic environments

Stulp, Freek, Buchli, Jonas, Ellmer, Alice, Mistry, Michael, Theodorou, Evangelos A., Schaal, S.

Autonomous Mental Development, IEEE Transactions on, 4(4):330-341, 2012 (article)

am

[BibTex]

[BibTex]


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Reinforcement Learning with Sequences of Motion Primitives for Robust Manipulation

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

IEEE Transactions on Robotics, 2012 (article)

am

[BibTex]

[BibTex]

2009


Valero-Cuevas, F., Hoffmann, H., Kurse, M. U., Kutch, J. J., Theodorou, E. A.

IEEE Reviews in Biomedical Engineering – (All authors have equally contributed), (2):110?135, 2009, clmc (article)

Abstract
Computational models of the neuromuscular system hold the potential to allow us to reach a deeper understanding of neuromuscular function and clinical rehabilitation by complementing experimentation. By serving as a means to distill and explore specific hypotheses, computational models emerge from prior experimental data and motivate future experimental work. Here we review computational tools used to understand neuromuscular function including musculoskeletal modeling, machine learning, control theory, and statistical model analysis. We conclude that these tools, when used in combination, have the potential to further our understanding of neuromuscular function by serving as a rigorous means to test scientific hypotheses in ways that complement and leverage experimental data.

am

link (url) [BibTex]

2009


link (url) [BibTex]


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On-line learning and modulation of periodic movements with nonlinear dynamical systems

Gams, A., Ijspeert, A., Schaal, S., Lenarčič, J.

Autonomous Robots, 27(1):3-23, 2009, clmc (article)

Abstract
Abstract  The paper presents a two-layered system for (1) learning and encoding a periodic signal without any knowledge on its frequency and waveform, and (2) modulating the learned periodic trajectory in response to external events. The system is used to learn periodic tasks on a humanoid HOAP-2 robot. The first layer of the system is a dynamical system responsible for extracting the fundamental frequency of the input signal, based on adaptive frequency oscillators. The second layer is a dynamical system responsible for learning of the waveform based on a built-in learning algorithm. By combining the two dynamical systems into one system we can rapidly teach new trajectories to robots without any knowledge of the frequency of the demonstration signal. The system extracts and learns only one period of the demonstration signal. Furthermore, the trajectories are robust to perturbations and can be modulated to cope with a dynamic environment. The system is computationally inexpensive, works on-line for any periodic signal, requires no additional signal processing to determine the frequency of the input signal and can be applied in parallel to multiple dimensions. Additionally, it can adapt to changes in frequency and shape, e.g. to non-stationary signals, such as hand-generated signals and human demonstrations.

am

link (url) [BibTex]

link (url) [BibTex]


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Local dimensionality reduction for non-parametric regression

Hoffman, H., Schaal, S., Vijayakumar, S.

Neural Processing Letters, 2009, clmc (article)

Abstract
Locally-weighted regression is a computationally-efficient technique for non-linear regression. However, for high-dimensional data, this technique becomes numerically brittle and computationally too expensive if many local models need to be maintained simultaneously. Thus, local linear dimensionality reduction combined with locally-weighted regression seems to be a promising solution. In this context, we review linear dimensionality-reduction methods, compare their performance on nonparametric locally-linear regression, and discuss their ability to extend to incremental learning. The considered methods belong to the following three groups: (1) reducing dimensionality only on the input data, (2) modeling the joint input-output data distribution, and (3) optimizing the correlation between projection directions and output data. Group 1 contains principal component regression (PCR); group 2 contains principal component analysis (PCA) in joint input and output space, factor analysis, and probabilistic PCA; and group 3 contains reduced rank regression (RRR) and partial least squares (PLS) regression. Among the tested methods, only group 3 managed to achieve robust performance even for a non-optimal number of components (factors or projection directions). In contrast, group 1 and 2 failed for fewer components since these methods rely on the correct estimate of the true intrinsic dimensionality. In group 3, PLS is the only method for which a computationally-efficient incremental implementation exists. Thus, PLS appears to be ideally suited as a building block for a locally-weighted regressor in which projection directions are incrementally added on the fly.

am

link (url) [BibTex]

link (url) [BibTex]


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Incorporating Muscle Activation-Contraction dynamics to an optimal control framework for finger movements

Theodorou, Evangelos A., Valero-Cuevas, Francisco J.

Abstracts of Neural Control of Movement Conference (NCM 2009), 2009, clmc (article)

Abstract
Recent experimental and theoretical work [1] investigated the neural control of contact transition between motion and force during tapping with the index finger as a nonlinear optimization problem. Such transitions from motion to well-directed contact force are a fundamental part of dexterous manipulation. There are 3 alternative hypotheses of how this transition could be accomplished by the nervous system as a function of changes in direction and magnitude of the torque vector controlling the finger. These hypotheses are 1) an initial change in direction with a subsequent change in magnitude of the torque vector; 2) an initial change in magnitude with a subsequent directional change of the torque vector; and 3) a simultaneous and proportionally equal change of both direction and magnitude of the torque vector. Experimental work in [2] shows that the nervous system selects the first strategy, and in [1] we suggest that this may in fact be the optimal strategy. In [4] the framework of Iterative Linear Quadratic Optimal Regulator (ILQR) was extended to incorporate motion and force control. However, our prior simulation work assumed direct and instantaneous control of joint torques, which ignores the known delays and filtering properties of skeletal muscle. In this study, we implement an ILQR controller for a more biologically plausible biomechanical model of the index finger than [4], and add activation-contraction dynamics to the system to simulate muscle function. The planar biomechanical model includes the kinematics of the 3 joints while the applied torques are driven by activation?contraction dynamics with biologically plausible time constants [3]. In agreement with our experimental work [2], the task is to, within 500 ms, move the finger from a given resting configuration to target configuration with a desired terminal velocity. ILQR does not only stabilize the finger dynamics according to the objective function, but it also generates smooth joint space trajectories with minimal tuning and without an a-priori initial control policy (which is difficult to find for highly dimensional biomechanical systems). Furthemore, the use of this optimal control framework and the addition of activation-contraction dynamics considers the full nonlinear dynamics of the index finger and produces a sequence of postures which are compatible with experimental motion data [2]. These simulations combined with prior experimental results suggest that optimal control is a strong candidate for the generation of finger movements prior to abrupt motion-to-force transitions. This work is funded in part by grants NIH R01 0505520 and NSF EFRI-0836042 to Dr. Francisco J. Valero- Cuevas 1 Venkadesan M, Valero-Cuevas FJ. 
Effects of neuromuscular lags on controlling contact transitions. 
Philosophical Transactions of the Royal Society A: 2008. 2 Venkadesan M, Valero-Cuevas FJ. 
Neural Control of Motion-to-Force Transitions with the Fingertip. 
J. Neurosci., Feb 2008; 28: 1366 - 1373; 3 Zajac. Muscle and tendon: properties, models, scaling, and application to biomechanics and motor control. Crit Rev Biomed Eng, 17 4. Weiwei Li., Francisco Valero Cuevas: ?Linear Quadratic Optimal Control of Contact Transition with Fingertip ? ACC 2009

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PDF [BibTex]

PDF [BibTex]


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On-line learning and modulation of periodic movements with nonlinear dynamical systems

Gams, A., Ijspeert, A., Schaal, S., Lenarčič, J.

Autonomous Robots, 27(1):3-23, 2009, clmc (article)

Abstract
Abstract  The paper presents a two-layered system for (1) learning and encoding a periodic signal without any knowledge on its frequency and waveform, and (2) modulating the learned periodic trajectory in response to external events. The system is used to learn periodic tasks on a humanoid HOAP-2 robot. The first layer of the system is a dynamical system responsible for extracting the fundamental frequency of the input signal, based on adaptive frequency oscillators. The second layer is a dynamical system responsible for learning of the waveform based on a built-in learning algorithm. By combining the two dynamical systems into one system we can rapidly teach new trajectories to robots without any knowledge of the frequency of the demonstration signal. The system extracts and learns only one period of the demonstration signal. Furthermore, the trajectories are robust to perturbations and can be modulated to cope with a dynamic environment. The system is computationally inexpensive, works on-line for any periodic signal, requires no additional signal processing to determine the frequency of the input signal and can be applied in parallel to multiple dimensions. Additionally, it can adapt to changes in frequency and shape, e.g. to non-stationary signals, such as hand-generated signals and human demonstrations.

am

link (url) [BibTex]

link (url) [BibTex]

2007


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The new robotics - towards human-centered machines

Schaal, S.

HFSP Journal Frontiers of Interdisciplinary Research in the Life Sciences, 1(2):115-126, 2007, clmc (article)

Abstract
Research in robotics has moved away from its primary focus on industrial applications. The New Robotics is a vision that has been developed in past years by our own university and many other national and international research instiutions and addresses how increasingly more human-like robots can live among us and take over tasks where our current society has shortcomings. Elder care, physical therapy, child education, search and rescue, and general assistance in daily life situations are some of the examples that will benefit from the New Robotics in the near future. With these goals in mind, research for the New Robotics has to embrace a broad interdisciplinary approach, ranging from traditional mathematical issues of robotics to novel issues in psychology, neuroscience, and ethics. This paper outlines some of the important research problems that will need to be resolved to make the New Robotics a reality.

am

link (url) [BibTex]

2007


link (url) [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.

am

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.

am

link (url) [BibTex]

2000


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.

am

link (url) [BibTex]

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.

am

link (url) [BibTex]

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.

am

link (url) [BibTex]

1999


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.

am

link (url) [BibTex]

link (url) [BibTex]

1993


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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.

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[BibTex]

1993


[BibTex]