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2018


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Role of symmetry in driven propulsion at low Reynolds number

Sachs, J., Morozov, K. I., Kenneth, O., Qiu, T., Segreto, N., Fischer, P., Leshansky, A. M.

Phys. Rev. E, 98(6):063105, American Physical Society, December 2018 (article)

Abstract
We theoretically and experimentally investigate low-Reynolds-number propulsion of geometrically achiral planar objects that possess a dipole moment and that are driven by a rotating magnetic field. Symmetry considerations (involving parity, $\widehat{P}$, and charge conjugation, $\widehat{C}$) establish correspondence between propulsive states depending on orientation of the dipolar moment. Although basic symmetry arguments do not forbid individual symmetric objects to efficiently propel due to spontaneous symmetry breaking, they suggest that the average ensemble velocity vanishes. Some additional arguments show, however, that highly symmetrical ($\widehat{P}$-even) objects exhibit no net propulsion while individual less symmetrical ($\widehat{C}\widehat{P}$-even) propellers do propel. Particular magnetization orientation, rendering the shape $\widehat{C}\widehat{P}$-odd, yields unidirectional motion typically associated with chiral structures, such as helices. If instead of a structure with a permanent dipole we consider a polarizable object, some of the arguments have to be modified. For instance, we demonstrate a truly achiral ($\widehat{P}$- and $\widehat{C}\widehat{P}$-even) planar shape with an induced electric dipole that can propel by electro-rotation. We thereby show that chirality is not essential for propulsion due to rotation-translation coupling at low Reynolds number.

pf

link (url) DOI Project Page [BibTex]

2018


link (url) DOI Project Page [BibTex]


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Optical and Thermophoretic Control of Janus Nanopen Injection into Living Cells

Maier, C. M., Huergo, M. A., Milosevic, S., Pernpeintner, C., Li, M., Singh, D. P., Walker, D., Fischer, P., Feldmann, J., Lohmüller, T.

Nano Letters, 18, pages: 7935–7941, November 2018 (article) Accepted

Abstract
Devising strategies for the controlled injection of functional nanoparticles and reagents into living cells paves the way for novel applications in nanosurgery, sensing, and drug delivery. Here, we demonstrate the light-controlled guiding and injection of plasmonic Janus nanopens into living cells. The pens are made of a gold nanoparticle attached to a dielectric alumina shaft. Balancing optical and thermophoretic forces in an optical tweezer allows single Janus nanopens to be trapped and positioned on the surface of living cells. While the optical injection process involves strong heating of the plasmonic side, the temperature of the alumina stays significantly lower, thus allowing the functionalization with fluorescently labeled, single-stranded DNA and, hence, the spatially controlled injection of genetic material with an untethered nanocarrier.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl content nanoroboter werden ins auge injiziert
A swarm of slippery micropropellers penetrates the vitreous body of the eye

Wu, Z., Troll, J., Jeong, H. H., Wei, Q., Stang, M., Ziemssen, F., Wang, Z., Dong, M., Schnichels, S., Qiu, T., Fischer, P.

Science Advances, 4(11):eaat4388, November 2018 (article)

Abstract
The intravitreal delivery of therapeutic agents promises major benefits in the field of ocular medicine. Traditional delivery methods rely on the random, passive diffusion of molecules, which do not allow for the rapid delivery of a concentrated cargo to a defined region at the posterior pole of the eye. The use of particles promises targeted delivery but faces the challenge that most tissues including the vitreous have a tight macromolecular matrix that acts as a barrier and prevents its penetration. Here, we demonstrate novel intravitreal delivery microvehicles slippery micropropellers that can be actively propelled through the vitreous humor to reach the retina. The propulsion is achieved by helical magnetic micropropellers that have a liquid layer coating to minimize adhesion to the surrounding biopolymeric network. The submicrometer diameter of the propellers enables the penetration of the biopolymeric network and the propulsion through the porcine vitreous body of the eye over centimeter distances. Clinical optical coherence tomography is used to monitor the movement of the propellers and confirm their arrival on the retina near the optic disc. Overcoming the adhesion forces and actively navigating a swarm of micropropellers in the dense vitreous humor promise practical applications in ophthalmology.

pf

Video: Nanorobots propel through the eye link (url) DOI [BibTex]

Video: Nanorobots propel through the eye link (url) DOI [BibTex]


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Gait learning for soft microrobots controlled by light fields

Rohr, A. V., Trimpe, S., Marco, A., Fischer, P., Palagi, S.

In International Conference on Intelligent Robots and Systems (IROS) 2018, pages: 6199-6206, International Conference on Intelligent Robots and Systems 2018, October 2018 (inproceedings)

Abstract
Soft microrobots based on photoresponsive materials and controlled by light fields can generate a variety of different gaits. This inherent flexibility can be exploited to maximize their locomotion performance in a given environment and used to adapt them to changing environments. However, because of the lack of accurate locomotion models, and given the intrinsic variability among microrobots, analytical control design is not possible. Common data-driven approaches, on the other hand, require running prohibitive numbers of experiments and lead to very sample-specific results. Here we propose a probabilistic learning approach for light-controlled soft microrobots based on Bayesian Optimization (BO) and Gaussian Processes (GPs). The proposed approach results in a learning scheme that is highly data-efficient, enabling gait optimization with a limited experimental budget, and robust against differences among microrobot samples. These features are obtained by designing the learning scheme through the comparison of different GP priors and BO settings on a semisynthetic data set. The developed learning scheme is validated in microrobot experiments, resulting in a 115% improvement in a microrobot’s locomotion performance with an experimental budget of only 20 tests. These encouraging results lead the way toward self-adaptive microrobotic systems based on lightcontrolled soft microrobots and probabilistic learning control.

ics pf

arXiv IEEE Xplore DOI Project Page [BibTex]

arXiv IEEE Xplore DOI Project Page [BibTex]


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A Value-Driven Eldercare Robot: Virtual and Physical Instantiations of a Case-Supported Principle-Based Behavior Paradigm

Anderson, M., Anderson, S., Berenz, V.

Proceedings of the IEEE, pages: 1,15, October 2018 (article)

Abstract
In this paper, a case-supported principle-based behavior paradigm is proposed to help ensure ethical behavior of autonomous machines. We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Such a consensus is likely to emerge in many areas in which autonomous systems are apt to be deployed and for the actions they are liable to undertake. We believe that this is the case since we are more likely to agree on how machines ought to treat us than on how human beings ought to treat one another. Given such a consensus, particular cases of ethical dilemmas where ethicists agree on the ethically relevant features and the right course of action can be used to help discover principles that balance these features when they are in conflict. Such principles not only help ensure ethical behavior of complex and dynamic systems but also can serve as a basis for justification of this behavior. The requirements, methods, implementation, and evaluation components of the paradigm are detailed as well as its instantiation in both a simulated and real robot functioning in the domain of eldercare.

am

link (url) DOI [BibTex]


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Nanoscale robotic agents in biological fluids and tissues

Palagi, S., Walker, D. Q. T., Fischer, P.

In The Encyclopedia of Medical Robotics, 2, pages: 19-42, 2, (Editors: Desai, J. P. and Ferreira, A.), World Scientific, October 2018 (inbook)

Abstract
Nanorobots are untethered structures of sub-micron size that can be controlled in a non-trivial way. Such nanoscale robotic agents are envisioned to revolutionize medicine by enabling minimally invasive diagnostic and therapeutic procedures. To be useful, nanorobots must be operated in complex biological fluids and tissues, which are often difficult to penetrate. In this chapter, we first discuss potential medical applications of motile nanorobots. We briefly present the challenges related to swimming at such small scales and we survey the rheological properties of some biological fluids and tissues. We then review recent experimental results in the development of nanorobots and in particular their design, fabrication, actuation, and propulsion in complex biological fluids and tissues. Recent work shows that their nanoscale dimension is a clear asset for operation in biological tissues, since many biological tissues consist of networks of macromolecules that prevent the passage of larger micron-scale structures, but contain dynamic pores through which nanorobots can move.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Fast spatial scanning of 3D ultrasound fields via thermography

Melde, K., Qiu, T., Fischer, P.

Applied Physics Letters, 113(13):133503, September 2018 (article)

Abstract
We propose and demonstrate a thermographic method that allows rapid scanning of ultrasound fields in a volume to yield 3D maps of the sound intensity. A thin sound-absorbing membrane is continuously translated through a volume of interest while a thermal camera records the evolution of its surface temperature. The temperature rise is a function of the absorbed sound intensity, such that the thermal image sequence can be combined to reveal the sound intensity distribution in the traversed volume. We demonstrate the mapping of ultrasound fields, which is several orders of magnitude faster than scanning with a hydrophone. Our results are in very good agreement with theoretical simulations.

pf

link (url) DOI Project Page [BibTex]


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Playful: Reactive Programming for Orchestrating Robotic Behavior

Berenz, V., Schaal, S.

IEEE Robotics Automation Magazine, 25(3):49-60, September 2018 (article) In press

Abstract
For many service robots, reactivity to changes in their surroundings is a must. However, developing software suitable for dynamic environments is difficult. Existing robotic middleware allows engineers to design behavior graphs by organizing communication between components. But because these graphs are structurally inflexible, they hardly support the development of complex reactive behavior. To address this limitation, we propose Playful, a software platform that applies reactive programming to the specification of robotic behavior.

am

playful website playful_IEEE_RAM link (url) DOI [BibTex]


Thumb xl screen shot 2018 09 19 at 09.33.59
ClusterNet: Instance Segmentation in RGB-D Images

Shao, L., Tian, Y., Bohg, J.

arXiv, September 2018, Submitted to ICRA'19 (article) Submitted

Abstract
We propose a method for instance-level segmentation that uses RGB-D data as input and provides detailed information about the location, geometry and number of {\em individual\/} objects in the scene. This level of understanding is fundamental for autonomous robots. It enables safe and robust decision-making under the large uncertainty of the real-world. In our model, we propose to use the first and second order moments of the object occupancy function to represent an object instance. We train an hourglass Deep Neural Network (DNN) where each pixel in the output votes for the 3D position of the corresponding object center and for the object's size and pose. The final instance segmentation is achieved through clustering in the space of moments. The object-centric training loss is defined on the output of the clustering. Our method outperforms the state-of-the-art instance segmentation method on our synthesized dataset. We show that our method generalizes well on real-world data achieving visually better segmentation results.

am

link (url) [BibTex]

link (url) [BibTex]


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Leveraging Contact Forces for Learning to Grasp

Merzic, H., Bogdanovic, M., Kappler, D., Righetti, L., Bohg, J.

arXiv, September 2018, Submitted to ICRA'19 (article) Submitted

Abstract
Grasping objects under uncertainty remains an open problem in robotics research. This uncertainty is often due to noisy or partial observations of the object pose or shape. To enable a robot to react appropriately to unforeseen effects, it is crucial that it continuously takes sensor feedback into account. While visual feedback is important for inferring a grasp pose and reaching for an object, contact feedback offers valuable information during manipulation and grasp acquisition. In this paper, we use model-free deep reinforcement learning to synthesize control policies that exploit contact sensing to generate robust grasping under uncertainty. We demonstrate our approach on a multi-fingered hand that exhibits more complex finger coordination than the commonly used two- fingered grippers. We conduct extensive experiments in order to assess the performance of the learned policies, with and without contact sensing. While it is possible to learn grasping policies without contact sensing, our results suggest that contact feedback allows for a significant improvement of grasping robustness under object pose uncertainty and for objects with a complex shape.

am mg

video arXiv [BibTex]

video arXiv [BibTex]


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Diffusion Measurements of Swimming Enzymes with Fluorescence Correlation Spectroscopy

Günther, J., Börsch, M., Fischer, P.

Accounts of Chemical Research, 51(9):1911-1920, August 2018 (article)

Abstract
Self-propelled chemical motors are chemically powered micro- or nanosized swimmers. The energy required for these motors’ active motion derives from catalytic chemical reactions and the transformation of a fuel dissolved in the solution. While self-propulsion is now well established for larger particles, it is still unclear if enzymes, nature’s nanometer-sized catalysts, are potentially also self-powered nanomotors. Because of its small size, any increase in an enzyme’s diffusion due to active self-propulsion must be observed on top of the enzyme’s passive Brownian motion, which dominates at this scale. Fluorescence correlation spectroscopy (FCS) is a sensitive method to quantify the diffusion properties of single fluorescently labeled molecules in solution. FCS experiments have shown a general increase in the diffusion constant of a number of enzymes when the enzyme is catalytically active. Diffusion enhancements after addition of the enzyme’s substrate (and sometimes its inhibitor) of up to 80\% have been reported, which is at least 1 order of magnitude higher than what theory would predict. However, many factors contribute to the FCS signal and in particular the shape of the autocorrelation function, which underlies diffusion measurements by fluorescence correlation spectroscopy. These effects need to be considered to establish if and by how much the catalytic activity changes an enzyme’s diffusion.We carefully review phenomena that can play a role in FCS experiments and the determination of enzyme diffusion, including the dissociation of enzyme oligomers upon interaction with the substrate, surface binding of the enzyme to glass during the experiment, conformational changes upon binding, and quenching of the fluorophore. We show that these effects can cause changes in the FCS signal that behave similar to an increase in diffusion. However, in the case of the enzymes F1-ATPase and alkaline phosphatase, we demonstrate that there is no measurable increase in enzyme diffusion. Rather, dissociation and conformational changes account for the changes in the FCS signal in the former and fluorophore quenching in the latter. Within the experimental accuracy of our FCS measurements, we do not observe any change in diffusion due to activity for the enzymes we have investigated.We suggest useful control experiments and additional tests for future FCS experiments that should help establish if the observed diffusion enhancement is real or if it is due to an experimental or data analysis artifact. We show that fluorescence lifetime and mean intensity measurements are essential in order to identify the nature of the observed changes in the autocorrelation function. While it is clear from theory that chemically active enzymes should also act as self-propelled nanomotors, our FCS measurements show that the associated increase in diffusion is much smaller than previously reported. Further experiments are needed to quantify the contribution of the enzymes’ catalytic activity to their self-propulsion. We hope that our findings help to establish a useful protocol for future FCS studies in this field and help establish by how much the diffusion of an enzyme is enhanced through catalytic activity.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Uphill production of dihydrogen by enzymatic oxidation of glucose without an external energy source

Suraniti, E., Merzeau, P., Roche, J., Gounel, S., Mark, A. G., Fischer, P., Mano, N., Kuhn, A.

Nature Communications, 9(1):3229, August 2018 (article)

Abstract
Chemical systems do not allow the coupling of energy from several simple reactions to drive a subsequent reaction, which takes place in the same medium and leads to a product with a higher energy than the one released during the first reaction. Gibbs energy considerations thus are not favorable to drive e.g., water splitting by the direct oxidation of glucose as a model reaction. Here, we show that it is nevertheless possible to carry out such an energetically uphill reaction, if the electrons released in the oxidation reaction are temporarily stored in an electromagnetic system, which is then used to raise the electrons' potential energy so that they can power the electrolysis of water in a second step. We thereby demonstrate the general concept that lower energy delivering chemical reactions can be used to enable the formation of higher energy consuming reaction products in a closed system.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Chemical micromotors self-assemble and self-propel by spontaneous symmetry breaking

Yu, T., Chuphal, P., Thakur, S., Reigh, S. Y., Singh, D. P., Fischer, P.

Chem. Comm., 54, pages: 11933-11936, August 2018 (article)

Abstract
Self-propelling chemical motors have thus far required the fabrication of Janus particles with an asymmetric catalyst distribution. Here, we demonstrate that simple, isotropic colloids can spontaneously assemble to yield dimer motors that self-propel. In a mixture of isotropic titanium dioxide colloids with photo-chemical catalytic activity and passive silica colloids, light illumination causes diffusiophoretic attractions between the active and passive particles and leads to the formation of dimers. The dimers constitute a symmetry-broken motor, whose dynamics can be fully controlled by the illumination conditions. Computer simulations reproduce the dynamics of the colloids and are in good agreement with experiments. The current work presents a simple route to obtain large numbers of self-propelling chemical motors from a dispersion of spherically symmetric colloids through spontaneous symmetry breaking.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A machine from machines

Fischer, P.

Nature Physics, 14, pages: 1072–1073, July 2018 (misc)

Abstract
Building spinning microrotors that self-assemble and synchronize to form a gear sounds like an impossible feat. However, it has now been achieved using only a single type of building block -- a colloid that self-propels.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Chemotaxis of Active Janus Nanoparticles

Popescu, M. N., Uspal, W. E., Bechinger, C., Fischer, P.

Nano Letters, 18(9):5345–5349, July 2018 (article)

Abstract
While colloids and molecules in solution exhibit passive Brownian motion, particles that are partially covered with a catalyst, which promotes the transformation of a fuel dissolved in the solution, can actively move. These active Janus particles are known as “chemical nanomotors” or self-propelling “swimmers” and have been realized with a range of catalysts, sizes, and particle geometries. Because their active translation depends on the fuel concentration, one expects that active colloidal particles should also be able to swim toward a fuel source. Synthesizing and engineering nanoparticles with distinct chemotactic properties may enable important developments, such as particles that can autonomously swim along a pH gradient toward a tumor. Chemotaxis requires that the particles possess an active coupling of their orientation to a chemical gradient. In this Perspective we provide a simple, intuitive description of the underlying mechanisms for chemotaxis, as well as the means to analyze and classify active particles that can show positive or negative chemotaxis. The classification provides guidance for engineering a specific response and is a useful organizing framework for the quantitative analysis and modeling of chemotactic behaviors. Chemotaxis is emerging as an important focus area in the field of active colloids and promises a number of fascinating applications for nanoparticles and particle-based delivery.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Probabilistic Recurrent State-Space Models

Doerr, A., Daniel, C., Schiegg, M., Nguyen-Tuong, D., Schaal, S., Toussaint, M., Trimpe, S.

In Proceedings of the International Conference on Machine Learning (ICML), International Conference on Machine Learning (ICML), July 2018 (inproceedings)

Abstract
State-space models (SSMs) are a highly expressive model class for learning patterns in time series data and for system identification. Deterministic versions of SSMs (e.g., LSTMs) proved extremely successful in modeling complex time-series data. Fully probabilistic SSMs, however, unfortunately often prove hard to train, even for smaller problems. To overcome this limitation, we propose a scalable initialization and training algorithm based on doubly stochastic variational inference and Gaussian processes. In the variational approximation we propose in contrast to related approaches to fully capture the latent state temporal correlations to allow for robust training.

am ics

arXiv pdf Project Page [BibTex]

arXiv pdf Project Page [BibTex]


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Real-time Perception meets Reactive Motion Generation

(Best Systems Paper Finalists - Amazon Robotics Best Paper Awards in Manipulation)

Kappler, D., Meier, F., Issac, J., Mainprice, J., Garcia Cifuentes, C., Wüthrich, M., Berenz, V., Schaal, S., Ratliff, N., Bohg, J.

IEEE Robotics and Automation Letters, 3(3):1864-1871, July 2018 (article)

Abstract
We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-predict environment dynamics. Our approach emphasizes the importance of continuous, real-time perception and its tight integration with reactive motion generation methods. We present a fully integrated system where real-time object and robot tracking as well as ambient world modeling provides the necessary input to feedback controllers and continuous motion optimizers. Specifically, they provide attractive and repulsive potentials based on which the controllers and motion optimizer can online compute movement policies at different time intervals. We extensively evaluate the proposed system on a real robotic platform in four scenarios that exhibit either challenging workspace geometry or a dynamic environment. We compare the proposed integrated system with a more traditional sense-plan-act approach that is still widely used. In 333 experiments, we show the robustness and accuracy of the proposed system.

am

arxiv video video link (url) DOI Project Page [BibTex]


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Colloidal Chemical Nanomotors

Alarcon-Correa, M.

Colloidal Chemical Nanomotors, pages: 150, Cuvillier Verlag, MPI-IS , June 2018 (phdthesis)

Abstract
Synthetic sophisticated nanostructures represent a fundamental building block for the development of nanotechnology. The fabrication of nanoparticles complex in structure and material composition is key to build nanomachines that can operate as man-made nanoscale motors, which autonomously convert external energy into motion. To achieve this, asymmetric nanoparticles were fabricated combining a physical vapor deposition technique known as NanoGLAD and wet chemical synthesis. This thesis primarily concerns three complex colloidal systems that have been developed: i)Hollow nanocup inclusion complexes that have a single Au nanoparticle in their pocket. The Au particle can be released with an external trigger. ii)The smallest self-propelling nanocolloids that have been made to date, which give rise to a local concentration gradient that causes enhanced diffusion of the particles. iii)Enzyme-powered pumps that have been assembled using bacteriophages as biological nanoscaffolds. This construct also can be used for enzyme recovery after heterogeneous catalysis.

pf

[BibTex]

[BibTex]


Thumb xl screen shot 2018 03 22 at 10.40.47 am
Oncilla robot: a versatile open-source quadruped research robot with compliant pantograph legs

Sproewitz, A., Tuleu, A., Ajallooeian, M., Vespignani, M., Moeckel, R., Eckert, P., D’Haene, M., Degrave, J., Nordmann, A., Schrauwen, B., Steil, J., Ijspeert, A. J.

Frontiers in Robotics and AI, 5(67), June 2018, arXiv: 1803.06259 (article)

Abstract
We present Oncilla robot, a novel mobile, quadruped legged locomotion machine. This large-cat sized, 5.1 robot is one of a kind of a recent, bioinspired legged robot class designed with the capability of model-free locomotion control. Animal legged locomotion in rough terrain is clearly shaped by sensor feedback systems. Results with Oncilla robot show that agile and versatile locomotion is possible without sensory signals to some extend, and tracking becomes robust when feedback control is added (Ajaoolleian 2015). By incorporating mechanical and control blueprints inspired from animals, and by observing the resulting robot locomotion characteristics, we aim to understand the contribution of individual components. Legged robots have a wide mechanical and control design parameter space, and a unique potential as research tools to investigate principles of biomechanics and legged locomotion control. But the hardware and controller design can be a steep initial hurdle for academic research. To facilitate the easy start and development of legged robots, Oncilla-robot's blueprints are available through open-source. [...]

dlg

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


Thumb xl screen shot 2018 04 18 at 11.01.27 am
Learning from Outside the Viability Kernel: Why we Should Build Robots that can Fail with Grace

Heim, S., Sproewitz, A.

Proceedings of SIMPAR 2018, pages: 55-61, IEEE, 2018 IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), May 2018 (conference)

dlg

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Bioinspired microrobots

Palagi, S., Fischer, P.

Nature Reviews Materials, 3, pages: 113–124, May 2018 (article)

Abstract
Microorganisms can move in complex media, respond to the environment and self-organize. The field of microrobotics strives to achieve these functions in mobile robotic systems of sub-millimetre size. However, miniaturization of traditional robots and their control systems to the microscale is not a viable approach. A promising alternative strategy in developing microrobots is to implement sensing, actuation and control directly in the materials, thereby mimicking biological matter. In this Review, we discuss design principles and materials for the implementation of robotic functionalities in microrobots. We examine different biological locomotion strategies, and we discuss how they can be artificially recreated in magnetic microrobots and how soft materials improve control and performance. We show that smart, stimuli-responsive materials can act as on-board sensors and actuators and that ‘active matter’ enables autonomous motion, navigation and collective behaviours. Finally, we provide a critical outlook for the field of microrobotics and highlight the challenges that need to be overcome to realize sophisticated microrobots, which one day might rival biological machines.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Soft Miniaturized Linear Actuators Wirelessly Powered by Rotating Permanent Magnets

Qiu, T., Palagi, S., Sachs, J., Fischer, P.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 3595-3600, May 2018 (inproceedings)

Abstract
Wireless actuation by magnetic fields allows for the operation of untethered miniaturized devices, e.g. in biomedical applications. Nevertheless, generating large controlled forces over relatively large distances is challenging. Magnetic torques are easier to generate and control, but they are not always suitable for the tasks at hand. Moreover, strong magnetic fields are required to generate a sufficient torque, which are difficult to achieve with electromagnets. Here, we demonstrate a soft miniaturized actuator that transforms an externally applied magnetic torque into a controlled linear force. We report the design, fabrication and characterization of both the actuator and the magnetic field generator. We show that the magnet assembly, which is based on a set of rotating permanent magnets, can generate strong controlled oscillating fields over a relatively large workspace. The actuator, which is 3D-printed, can lift a load of more than 40 times its weight. Finally, we show that the actuator can be further miniaturized, paving the way towards strong, wirelessly powered microactuators.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Impact of Trunk Orientation for Dynamic Bipedal Locomotion

Drama, O.

Dynamic Walking Conference, May 2018 (talk)

Abstract
Impact of trunk orientation for dynamic bipedal locomotion My research revolves around investigating the functional demands of bipedal running, with focus on stabilizing trunk orientation. When we think about postural stability, there are two critical questions we need to answer: What are the necessary and sufficient conditions to achieve and maintain trunk stability? I am concentrating on how morphology affects control strategies in achieving trunk stability. In particular, I denote the trunk pitch as the predominant morphology parameter and explore the requirements it imposes on a chosen control strategy. To analyze this, I use a spring loaded inverted pendulum model extended with a rigid trunk, which is actuated by a hip motor. The challenge for the controller design here is to have a single hip actuator to achieve two coupled tasks of moving the legs to generate motion and stabilizing the trunk. I enforce orthograde and pronograde postures and aim to identify the effect of these trunk orientations on the hip torque and ground reaction profiles for different control strategies.

dlg

Impact of trunk orientation for dynamic bipedal locomotion [DW 2018] link (url) Project Page [BibTex]


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Online Learning of a Memory for Learning Rates

(nominated for best paper award)

Meier, F., Kappler, D., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018, accepted (inproceedings)

Abstract
The promise of learning to learn for robotics rests on the hope that by extracting some information about the learning process itself we can speed up subsequent similar learning tasks. Here, we introduce a computationally efficient online meta-learning algorithm that builds and optimizes a memory model of the optimal learning rate landscape from previously observed gradient behaviors. While performing task specific optimization, this memory of learning rates predicts how to scale currently observed gradients. After applying the gradient scaling our meta-learner updates its internal memory based on the observed effect its prediction had. Our meta-learner can be combined with any gradient-based optimizer, learns on the fly and can be transferred to new optimization tasks. In our evaluations we show that our meta-learning algorithm speeds up learning of MNIST classification and a variety of learning control tasks, either in batch or online learning settings.

am

pdf video code [BibTex]

pdf video code [BibTex]


Thumb xl screen shot 2018 02 03 at 9.09.06 am
Shaping in Practice: Training Wheels to Learn Fast Hopping Directly in Hardware

Heim, S., Ruppert, F., Sarvestani, A., Sproewitz, A.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, pages: 5076-5081, IEEE, International Conference on Robotics and Automation, May 2018 (inproceedings)

Abstract
Learning instead of designing robot controllers can greatly reduce engineering effort required, while also emphasizing robustness. Despite considerable progress in simulation, applying learning directly in hardware is still challenging, in part due to the necessity to explore potentially unstable parameters. We explore the of concept shaping the reward landscape with training wheels; temporary modifications of the physical hardware that facilitate learning. We demonstrate the concept with a robot leg mounted on a boom learning to hop fast. This proof of concept embodies typical challenges such as instability and contact, while being simple enough to empirically map out and visualize the reward landscape. Based on our results we propose three criteria for designing effective training wheels for learning in robotics.

dlg

Video Youtube link (url) Project Page [BibTex]

Video Youtube link (url) Project Page [BibTex]


Thumb xl learning ct w asm block diagram detailed
Learning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks

Sutanto, G., Su, Z., Schaal, S., Meier, F.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018 (inproceedings)

am

pdf video [BibTex]

pdf video [BibTex]


Thumb xl graphene silver hybrid
Graphene-silver hybrid devices for sensitive photodetection in the ultraviolet

Paria, D., Jeong, H. H., Vadakkumbatt, V., Deshpande, P., Fischer, P., Ghosh, A., Ghosh, A.

Nanoscale, 10, pages: 7685-7693, April 2018 (article)

Abstract
The weak light-matter interaction in graphene can be enhanced with a number of strategies, among which sensitization with plasmonic nanostructures is particularly attractive. This has resulted in the development of graphene-plasmonic hybrid systems with strongly enhanced photodetection efficiencies in the visible and the IR, but none in the UV. Here, we describe a silver nanoparticle-graphene stacked optoelectronic device that shows strong enhancement of its photoresponse across the entire UV spectrum. The device fabrication strategy is scalable and modular. Self-assembly techniques are combined with physical shadow growth techniques to fabricate a regular large-area array of 50 nm silver nanoparticles onto which CVD graphene is transferred. The presence of the silver nanoparticles resulted in a plasmonically enhanced photoresponse as high as 3.2 A W-1 in the wavelength range from 330 nm to 450 nm. At lower wavelengths, close to the Van Hove singularity of the density of states in graphene, we measured an even higher responsivity of 14.5 A W-1 at 280 nm, which corresponds to a more than 10 000-fold enhancement over the photoresponse of native graphene.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Nanoparticles on the move for medicine

Fischer, P.

Physics World Focus on Nanotechnology, pages: 26028, (Editors: Margaret Harris), IOP Publishing Ltd and individual contributors, April 2018 (article)

Abstract
Peer Fischer outlines the prospects for creating “nanoswimmers” that can be steered through the body to deliver drugs directly to their targets Molecules don’t move very fast on their own. If they had to rely solely on diffusion – a slow and inefficient process linked to the Brownian motion of small particles and molecules in solution – then a protein mole­cule, for instance, would take around three weeks to travel a single centimetre down a nerve fibre. This is why active transport mechanisms exist in cells and in the human body: without them, all the processes of life would happen at a pace that would make snails look speedy.

pf

link (url) [BibTex]

link (url) [BibTex]


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Photogravitactic Microswimmers

Singh, D. P., Uspal, W. E., Popescu, M. N., Wilson, L. G., Fischer, P.

Adv. Func. Mat., 28, pages: 1706660, Febuary 2018 (article)

Abstract
Abstract Phototactic microorganisms are commonly observed to respond to natural sunlight by swimming upward against gravity. This study demonstrates that synthetic photochemically active microswimmers can also swim against gravity. The particles initially sediment and, when illuminated at low light intensities exhibit wall‐bound states of motion near the bottom surface. Upon increasing the intensity of light, the artificial swimmers lift off from the wall and swim against gravity and away from the light source. This motion in the bulk has been further confirmed using holographic microscopy. A theoretical model is presented within the framework of self‐diffusiophoresis, which allows to unequivocally identify the photochemical activity and the phototactic response as key mechanisms in the observed phenomenology. Since the lift‐off threshold intensity depends on the particle size, it can be exploited to selectively address particles with the same density from a polydisperse mixture of active particles and move them in or out of the boundary region. This study provides a simple design strategy to fabricate artificial microswimmers whose two‐ or three‐dimensional swimming behavior can be controlled with light.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Chiral Plasmonic Hydrogen Sensors

Matuschek, M., Singh, D. P., Hyeon-Ho, J., Nesterov, M., Weiss, T., Fischer, P., Neubrech, F., Na Liu, L.

Small, 14(7):1702990, Febuary 2018 (article)

Abstract
In this article, a chiral plasmonic hydrogen‐sensing platform using palladium‐based nanohelices is demonstrated. Such 3D chiral nanostructures fabricated by nanoglancing angle deposition exhibit strong circular dichroism both experimentally and theoretically. The chiroptical properties of the palladium nanohelices are altered upon hydrogen uptake and sensitively depend on the hydrogen concentration. Such properties are well suited for remote and spark‐free hydrogen sensing in the flammable range. Hysteresis is reduced, when an increasing amount of gold is utilized in the palladium‐gold hybrid helices. As a result, the linearity of the circular dichroism in response to hydrogen is significantly improved. The chiral plasmonic sensor scheme is of potential interest for hydrogen‐sensing applications, where good linearity and high sensitivity are required.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Acoustic Fabrication via the Assembly and Fusion of Particles

Melde, K., Choi, E., Wu, Z., Palagi, S., Qiu, T., Fischer, P.

Advanced Materials, 30(3):1704507, January 2018 (article)

Abstract
Acoustic assembly promises a route toward rapid parallel fabrication of whole objects directly from solution. This study reports the contact-free and maskless assembly, and fixing of silicone particles into arbitrary 2D shapes using ultrasound fields. Ultrasound passes through an acoustic hologram to form a target image. The particles assemble from a suspension along lines of high pressure in the image due to acoustic radiation forces and are then fixed (crosslinked) in a UV-triggered reaction. For this, the particles are loaded with a photoinitiator by solvent-induced swelling. This localizes the reaction and allows the bulk suspension to be reused. The final fabricated parts are mechanically stable and self-supporting.

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link (url) DOI Project Page [BibTex]


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Distributed Event-Based State Estimation for Networked Systems: An LMI Approach

Muehlebach, M., Trimpe, S.

IEEE Transactions on Automatic Control, 63(1):269-276, January 2018 (article)

am ics

arXiv (extended version) DOI Project Page [BibTex]

arXiv (extended version) DOI Project Page [BibTex]


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On Time Optimization of Centroidal Momentum Dynamics

Ponton, B., Herzog, A., Del Prete, A., Schaal, S., Righetti, L.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 5776-5782, IEEE, Brisbane, Australia, 2018 (inproceedings)

Abstract
Recently, the centroidal momentum dynamics has received substantial attention to plan dynamically consistent motions for robots with arms and legs in multi-contact scenarios. However, it is also non convex which renders any optimization approach difficult and timing is usually kept fixed in most trajectory optimization techniques to not introduce additional non convexities to the problem. But this can limit the versatility of the algorithms. In our previous work, we proposed a convex relaxation of the problem that allowed to efficiently compute momentum trajectories and contact forces. However, our approach could not minimize a desired angular momentum objective which seriously limited its applicability. Noticing that the non-convexity introduced by the time variables is of similar nature as the centroidal dynamics one, we propose two convex relaxations to the problem based on trust regions and soft constraints. The resulting approaches can compute time-optimized dynamically consistent trajectories sufficiently fast to make the approach realtime capable. The performance of the algorithm is demonstrated in several multi-contact scenarios for a humanoid robot. In particular, we show that the proposed convex relaxation of the original problem finds solutions that are consistent with the original non-convex problem and illustrate how timing optimization allows to find motion plans that would be difficult to plan with fixed timing † †Implementation details and demos can be found in the source code available at https://git-amd.tuebingen.mpg.de/bponton/timeoptimization.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Combining learned and analytical models for predicting action effects

Kloss, A., Schaal, S., Bohg, J.

arXiv, 2018 (article) Submitted

Abstract
One of the most basic skills a robot should possess is predicting the effect of physical interactions with objects in the environment. This enables optimal action selection to reach a certain goal state. Traditionally, dynamics are approximated by physics-based analytical models. These models rely on specific state representations that may be hard to obtain from raw sensory data, especially if no knowledge of the object shape is assumed. More recently, we have seen learning approaches that can predict the effect of complex physical interactions directly from sensory input. It is however an open question how far these models generalize beyond their training data. In this work, we investigate the advantages and limitations of neural network based learning approaches for predicting the effects of actions based on sensory input and show how analytical and learned models can be combined to leverage the best of both worlds. As physical interaction task, we use planar pushing, for which there exists a well-known analytical model and a large real-world dataset. We propose to use a convolutional neural network to convert raw depth images or organized point clouds into a suitable representation for the analytical model and compare this approach to using neural networks for both, perception and prediction. A systematic evaluation of the proposed approach on a very large real-world dataset shows two main advantages of the hybrid architecture. Compared to a pure neural network, it significantly (i) reduces required training data and (ii) improves generalization to novel physical interaction.

am

arXiv pdf link (url) [BibTex]


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Nanorobots propel through the eye

Zhiguang Wu, J. T. H. J. Q. W. M. S. F. Z. Z. W. M. D. S. S. T. Q. P. F.

Max Planck Society, 2018 (mpi_year_book)

Abstract
Scientists at the Max Planck Institute for Intelligent Systems in Stuttgart developed specially coated nanometer-sized robots that could be moved actively through dense tissue like the vitreous of the eye. So far, the transport of such nano-vehicles has only been demonstrated in model systems or biological fluids, but not in real tissue. Our work constitutes one step further towards nanorobots becoming minimally-invasive tools for precisely delivering medicine to where it is needed.

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link (url) [BibTex]


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Unsupervised Contact Learning for Humanoid Estimation and Control

Rotella, N., Schaal, S., Righetti, L.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 411-417, IEEE, Brisbane, Australia, 2018 (inproceedings)

Abstract
This work presents a method for contact state estimation using fuzzy clustering to learn contact probability for full, six-dimensional humanoid contacts. The data required for training is solely from proprioceptive sensors - endeffector contact wrench sensors and inertial measurement units (IMUs) - and the method is completely unsupervised. The resulting cluster means are used to efficiently compute the probability of contact in each of the six endeffector degrees of freedom (DoFs) independently. This clustering-based contact probability estimator is validated in a kinematics-based base state estimator in a simulation environment with realistic added sensor noise for locomotion over rough, low-friction terrain on which the robot is subject to foot slip and rotation. The proposed base state estimator which utilizes these six DoF contact probability estimates is shown to perform considerably better than that which determines kinematic contact constraints purely based on measured normal force.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Learning Task-Specific Dynamics to Improve Whole-Body Control

Gams, A., Mason, S., Ude, A., Schaal, S., Righetti, L.

In Hua, IEEE, Beijing, China, November 2018 (inproceedings)

Abstract
In task-based inverse dynamics control, reference accelerations used to follow a desired plan can be broken down into feedforward and feedback trajectories. The feedback term accounts for tracking errors that are caused from inaccurate dynamic models or external disturbances. On underactuated, free-floating robots, such as humanoids, high feedback terms can be used to improve tracking accuracy; however, this can lead to very stiff behavior or poor tracking accuracy due to limited control bandwidth. In this paper, we show how to reduce the required contribution of the feedback controller by incorporating learned task-space reference accelerations. Thus, we i) improve the execution of the given specific task, and ii) offer the means to reduce feedback gains, providing for greater compliance of the system. With a systematic approach we also reduce heuristic tuning of the model parameters and feedback gains, often present in real-world experiments. In contrast to learning task-specific joint-torques, which might produce a similar effect but can lead to poor generalization, our approach directly learns the task-space dynamics of the center of mass of a humanoid robot. Simulated and real-world results on the lower part of the Sarcos Hermes humanoid robot demonstrate the applicability of the approach.

am mg

link (url) [BibTex]

link (url) [BibTex]


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An MPC Walking Framework With External Contact Forces

Mason, S., Rotella, N., Schaal, S., Righetti, L.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 1785-1790, IEEE, Brisbane, Australia, May 2018 (inproceedings)

Abstract
In this work, we present an extension to a linear Model Predictive Control (MPC) scheme that plans external contact forces for the robot when given multiple contact locations and their corresponding friction cone. To this end, we set up a two-step optimization problem. In the first optimization, we compute the Center of Mass (CoM) trajectory, foot step locations, and introduce slack variables to account for violating the imposed constraints on the Zero Moment Point (ZMP). We then use the slack variables to trigger the second optimization, in which we calculate the optimal external force that compensates for the ZMP tracking error. This optimization considers multiple contacts positions within the environment by formulating the problem as a Mixed Integer Quadratic Program (MIQP) that can be solved at a speed between 100-300 Hz. Once contact is created, the MIQP reduces to a single Quadratic Program (QP) that can be solved in real-time ({\textless}; 1kHz). Simulations show that the presented walking control scheme can withstand disturbances 2-3× larger with the additional force provided by a hand contact.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]

2002


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Forward models in visuomotor control

Mehta, B., Schaal, S.

J Neurophysiol, 88(2):942-53, August 2002, clmc (article)

Abstract
In recent years, an increasing number of research projects investigated whether the central nervous system employs internal models in motor control. While inverse models in the control loop can be identified more readily in both motor behavior and the firing of single neurons, providing direct evidence for the existence of forward models is more complicated. In this paper, we will discuss such an identification of forward models in the context of the visuomotor control of an unstable dynamic system, the balancing of a pole on a finger. Pole balancing imposes stringent constraints on the biological controller, as it needs to cope with the large delays of visual information processing while keeping the pole at an unstable equilibrium. We hypothesize various model-based and non-model-based control schemes of how visuomotor control can be accomplished in this task, including Smith Predictors, predictors with Kalman filters, tapped-delay line control, and delay-uncompensated control. Behavioral experiments with human participants allow exclusion of most of the hypothesized control schemes. In the end, our data support the existence of a forward model in the sensory preprocessing loop of control. As an important part of our research, we will provide a discussion of when and how forward models can be identified and also the possible pitfalls in the search for forward models in control.

am

link (url) [BibTex]

2002


link (url) [BibTex]


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Chirality-specific nonlinear spectroscopies in isotropic media

Fischer, P., Albrecht, A.

BULLETIN OF THE CHEMICAL SOCIETY OF JAPAN, 75(5):1119-1124, 2002, 10th International Conference on Time-Resolved Vibrational Spectroscopy (TRVS 2001), OKAZZAKI, JAPAN, MAY 21-25, 2001 (article)

Abstract
Sum or difference frequency generation (SFG or DFG) in isotropic media is in the electric-dipole approximation only symmetry allowed for optically active systems. The hyperpolarizability giving rise to these three-wave mixing processes features only one isotropic component. It factorizes into two terms, an energy (denominator) factor and a triple product of transition moments. These forbid degenerate SFG, i.e., second harmonic generation, as well as the existence of the linear electrooptic effect (Pockels effect) in isotropic media. This second order response also has no static limit, which leads to particularly strong resonance phenomena that are qualitatively different from those usually seen in the ubiquitous even-wave mixing spectroscopies. In particular, the participation of two (not the usual one) excited states is essential to achieve dramatic resonance enhancement, We report our first efforts to see such resonantly enhanced chirality specific SFG.

pf

DOI [BibTex]

DOI [BibTex]


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The chiral specificity of sum-frequency generation in solutions

Fischer, P., Beckwitt, K., Wise, F., Albrecht, A.

CHEMICAL PHYSICS LETTERS, 352(5-6):463-468, 2002 (article)

Abstract
Sum-frequency generation in isotropic media is in the electric-dipole approximation the only symmetry allowed for chiral systems. We demonstrate that the sum-frequency intensity from an optically active liquid depends quadratically on the difference in concentration of the two enantiomers. The dominant contribution to the signal is found to be due to the chirality specific electric-dipolar three-wave mixing nonlinearity. Selecting the polarization of all fields allows the chiral electric-dipolar contributions to the bulk sum-frequency signal to be discerned from any achiral magnetic-dipolar and electric-quadrupolar contributions. (C) 2002 Published by Elsevier Science B.V.

pf

DOI [BibTex]

DOI [BibTex]


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On optical rectification in isotropic media

Fischer, P., Albrecht, A.

LASER PHYSICS, 12(8):1177-1181, 2002 (article)

Abstract
Coherent nonlinear optical processes at second-order are only electric-dipole allowed in isotropic media that are optically active. Sum-frequency generation in chiral liquids has recently been observed, and difference-frequency and optical rectification have been predicted to exist in isotropic chiral media. Both Rayleigh-Schrodinger perturbation theory and the density matrix approach are used to discuss the quantum-chemical basis of optical rectification in optically active liquids. For pinene we compute the corresponding orientationally averaged hyperpolarizability, and estimate the light-induced dc electric polarization and the consequent voltage across a measuring capacitor it may give rise to near resonance.

pf

[BibTex]

[BibTex]


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Learning rhythmic movements by demonstration using nonlinear oscillators

Ijspeert, J. A., Nakanishi, J., Schaal, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS 2002), pages: 958-963, Piscataway, NJ: IEEE, Lausanne, Sept.30-Oct.4 2002, 2002, clmc (inproceedings)

Abstract
Locally weighted learning (LWL) is a class of statistical learning techniques that provides useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of robotic systems. This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks. We discuss two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly. In contrast to the traditional beliefs that LWL methods cannot work well in high-dimensional spaces, we provide new algorithms that have been tested in up to 50 dimensional learning problems. The applicability of our LWL algorithms is demonstrated in various robot learning examples, including the learning of devil-sticking, pole-balancing of a humanoid robot arm, and inverse-dynamics learning for a seven degree-of-freedom robot.

am

link (url) [BibTex]

link (url) [BibTex]


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Learning robot control

Schaal, S.

In The handbook of brain theory and neural networks, 2nd Edition, pages: 983-987, 2, (Editors: Arbib, M. A.), MIT Press, Cambridge, MA, 2002, clmc (inbook)

Abstract
This is a review article on learning control in robots.

am

link (url) [BibTex]

link (url) [BibTex]


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Arm and hand movement control

Schaal, S.

In The handbook of brain theory and neural networks, 2nd Edition, pages: 110-113, 2, (Editors: Arbib, M. A.), MIT Press, Cambridge, MA, 2002, clmc (inbook)

Abstract
This is a review article on computational and biological research on arm and hand control.

am

link (url) [BibTex]

link (url) [BibTex]


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Scalable techniques from nonparameteric statistics for real-time robot learning

Schaal, S., Atkeson, C. G., Vijayakumar, S.

Applied Intelligence, 17(1):49-60, 2002, clmc (article)

Abstract
Locally weighted learning (LWL) is a class of techniques from nonparametric statistics that provides useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of robotic systems. This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks. We discuss two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly. In contrast to the traditional belief that LWL methods cannot work well in high-dimensional spaces, we provide new algorithms that have been tested on up to 90 dimensional learning problems. The applicability of our LWL algorithms is demonstrated in various robot learning examples, including the learning of devil-sticking, pole-balancing by a humanoid robot arm, and inverse-dynamics learning for a seven and a 30 degree-of-freedom robot. In all these examples, the application of our statistical neural networks techniques allowed either faster or more accurate acquisition of motor control than classical control engineering.

am

link (url) [BibTex]

link (url) [BibTex]


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Movement imitation with nonlinear dynamical systems in humanoid robots

Ijspeert, J. A., Nakanishi, J., Schaal, S.

In International Conference on Robotics and Automation (ICRA2002), Washinton, May 11-15 2002, 2002, clmc (inproceedings)

Abstract
Locally weighted learning (LWL) is a class of statistical learning techniques that provides useful representations and training algorithms for learning about complex phenomena during autonomous adaptive control of robotic systems. This paper introduces several LWL algorithms that have been tested successfully in real-time learning of complex robot tasks. We discuss two major classes of LWL, memory-based LWL and purely incremental LWL that does not need to remember any data explicitly. In contrast to the traditional beliefs that LWL methods cannot work well in high-dimensional spaces, we provide new algorithms that have been tested in up to 50 dimensional learning problems. The applicability of our LWL algorithms is demonstrated in various robot learning examples, including the learning of devil-sticking, pole-balancing of a humanoid robot arm, and inverse-dynamics learning for a seven degree-of-freedom robot.

am

link (url) [BibTex]

link (url) [BibTex]


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A locally weighted learning composite adaptive controller with structure adaptation

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

In IEEE International Conference on Intelligent Robots and Systems (IROS 2002), Lausanne, Sept.30-Oct.4 2002, 2002, clmc (inproceedings)

Abstract
This paper introduces a provably stable adaptive learning controller which 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 pro-posed learning adaptive control algorithm uses both the tracking error and the estimation error to up-date the parameters. We provide Lyapunov analyses that demonstrate the stability properties of the learning controller. Numerical simulations illustrate rapid convergence of the tracking error and the automatic structure adaptation capability of the function approximator. This paper introduces a provably stable adaptive learning controller which 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 pro-posed learning adaptive control algorithm uses both the tracking error and the estimation error to up-date the parameters. We provide Lyapunov analyses that demonstrate the stability properties of the learning controller. Numerical simulations illustrate rapid convergence of the tracking error and the automatic structure adaptation capability of the function approximator

am

link (url) [BibTex]

link (url) [BibTex]