Bayesian Optimization Using Domain Knowledge on the ATRIAS Biped

Controllers in robotics often consist of expert-designed heuristics, which can be hard to tune in higher dimensions. It is typical to use simulation to learn these parameters, but controllers learned in simulation often don't transfer to hardware. This necessitates optimization directly on hardware. However, collecting data on hardware can be expensive. This has led to a recent interest in adapting data-efficient learning techniques to robotics. One popular method is Bayesian Optimization (BO), a sample-efficient black-box optimization scheme, but its performance typically degrades in higher dimensions. We aim to overcome this problem by incorporating domain knowledge to reduce dimensionality in a meaningful way, with a focus on bipedal locomotion. In previous work, we proposed a transformation based on knowledge of human walking that projected a 16-dimensional controller to a 1-dimensional space. In simulation, this showed enhanced sample efficiency when optimizing human-inspired neuromuscular walking controllers on a humanoid model. In this paper, we present a generalized feature transform applicable to non-humanoid robot morphologies and evaluate it on the ATRIAS bipedal robot -- in simulation and on hardware. We present three different walking controllers; two are evaluated on the real robot. Our results show that this feature transform captures important aspects of walking and accelerates learning on hardware and simulation, as compared to traditional BO.Comment: 8 pages, submitted to IEEE International Conference on Robotics and Automation 201

Möglichkeiten zur Qualitätssicherung ökologisch erzeugter Gartenbauprodukte durch Koordinierung der Wertschöpfungsketten

Die Untersuchungen konzentrieren sich auf den besonderen Aspekt der Qualitätserhaltung ökologischer Produkte in der Nacherntephase entlang der gesamten Wertschöpfungskette. Die hier geschätzten Verluste von über 1/3 der Erntemengen können zu einem beträchtlichen Teil auf unorganisiertes, unkoordiniertes und dadurch wenig produktangepasstes Handeln der beteiligten Akteure zurückgeführt werden. Mittels qualitativer Interviews wurden Akteure typischer Lieferketten in Deutschland und ergänzend dazu auch in der Schweiz und den Niederlanden zu ihren Aktivitäten zum Qualitätserhalt befragt. Als besondere Schwachstellen konnten die verschiedenen Qualitätsbilder der Akteure, mangelhafte technische Ressourcen, wenig aufeinander abgestimmte Arbeitsabläufe sowie ungenügende Nachfrage durch den Verbraucher identifiziert werden. Lösungsansätze ergeben sich aus einer verstärkter Kommunikation und Absprache aller Marktbeteiligten, qualifizierten Mitarbeiter auf allen Ebenen, einer gemeinsamen Orientierung der Arbeitsabläufe an den Bedürfnissen eines lebendigen und stoffwechselnden Produktes inklusive der Sicherung einer geschlossenen Kühlkette. Als notwendig erachtet werden verstärkt Anstrengungen zur Förderung der Nachfrage. Schweizerische Erfolgsfaktoren sind die eindeutige Positionierung und das Engagement des LEH sowie Strukturen, die ein weitgehend ausgeglichenes Kräfteverhältnis der Kettenakteure und damit einen konstruktiven Dialog ermöglichen. Als besonderer Vorteil der niederländischen Strukturen wird die traditionell professionelle Produktion sowie auch hier das allseitige Bemühen um Dialog und Austausch angesehen

Comparison of Neural Networks, Evolutionary Techniques and Thermodynamic Group Contribution Methods for the Prediction of Heats of Vaporization

In this paper we report results for the prediction of thermodynamic properties based on neural networks, evolutionary algorithms and a combination of them. We compare backpropagation trained networks and evolution strategy trained networks with two physical models. Experimental data for the enthalpy of vaporization were taken from the literature in our investigation. The input information for both neural network and physical models consists of parameters describing the molecular structure of the molecules and the temperature. The results show the good ability of the neural networks to correlate and to predict the thermodynamic property. We also conclude that backpropagation training outperforms evolutionary training as well as simple hybrid training

The critical behavior of 3D Ising glass models: universality and scaling corrections

We perform high-statistics Monte Carlo simulations of three three-dimensional Ising spin-glass models: the +-J Ising model for two values of the disorder parameter p, p=1/2 and p=0.7, and the bond-diluted +-J model for bond-occupation probability p_b = 0.45. A finite-size scaling analysis of the quartic cumulants at the critical point shows conclusively that these models belong to the same universality class and allows us to estimate the scaling-correction exponent omega related to the leading irrelevant operator, omega=1.0(1). We also determine the critical exponents nu and eta. Taking into account the scaling corrections, we obtain nu=2.53(8) and eta=-0.384(9).Comment: 9 pages, published versio

Computational statistics using the Bayesian Inference Engine

This paper introduces the Bayesian Inference Engine (BIE), a general parallel, optimised software package for parameter inference and model selection. This package is motivated by the analysis needs of modern astronomical surveys and the need to organise and reuse expensive derived data. The BIE is the first platform for computational statistics designed explicitly to enable Bayesian update and model comparison for astronomical problems. Bayesian update is based on the representation of high-dimensional posterior distributions using metric-ball-tree based kernel density estimation. Among its algorithmic offerings, the BIE emphasises hybrid tempered MCMC schemes that robustly sample multimodal posterior distributions in high-dimensional parameter spaces. Moreover, the BIE is implements a full persistence or serialisation system that stores the full byte-level image of the running inference and previously characterised posterior distributions for later use. Two new algorithms to compute the marginal likelihood from the posterior distribution, developed for and implemented in the BIE, enable model comparison for complex models and data sets. Finally, the BIE was designed to be a collaborative platform for applying Bayesian methodology to astronomy. It includes an extensible object-oriented and easily extended framework that implements every aspect of the Bayesian inference. By providing a variety of statistical algorithms for all phases of the inference problem, a scientist may explore a variety of approaches with a single model and data implementation. Additional technical details and download details are available from http://www.astro.umass.edu/bie. The BIE is distributed under the GNU GPL.Comment: Resubmitted version. Additional technical details and download details are available from http://www.astro.umass.edu/bie. The BIE is distributed under the GNU GP

Multicritical Nishimori point in the phase diagram of the +- J Ising model on a square lattice

We investigate the critical behavior of the random-bond +- J Ising model on a square lattice at the multicritical Nishimori point in the T-p phase diagram, where T is the temperature and p is the disorder parameter (p=1 corresponds to the pure Ising model). We perform a finite-size scaling analysis of high-statistics Monte Carlo simulations along the Nishimori line defined by $2p-1={\rm Tanh}(1/T)$, along which the multicritical point lies. The multicritical Nishimori point is located at p^*=0.89081(7), T^*=0.9528(4), and the renormalization-group dimensions of the operators that control the multicritical behavior are y_1=0.655(15) and y_2 = 0.250(2); they correspond to the thermal exponent \nu= 1/y_2=4.00(3) and to the crossover exponent \phi= y_1/y_2=2.62(6).Comment: 23 page

Geschichte der Erntetechnik von weißem Spargel

White asparagus is the most important vegetable crop in Germany. Harvesting white asparagus is time-consuming and costly. Additionally, the shortage of labor causes problems and has led to an intensive search for alternatives. This article describes the development of harvesting methods in the last 50 years. The most important step was the use of opaque black/white films to cover the asparagus ridges to reduce the harvesting frequency. Based on this, various harvesting methods were developed. Starting with hand harvesting with basket, push carriages and single- to multi-row motorized harvesting aids followed. At the same time, non-selective and selective mechanical harvesters were developed. The advantages and disadvantages of the individual methods are described.Weißer Spargel ist die wichtigste Gemüsekultur in Deutschland. Jedoch ist die Ernte von weißem Spargel arbeitsintensiv, zeitaufwendig und kostspielig. Auch der Mangel an Arbeitskräften bereitet Probleme und führt zu einer intensiven Suche nach Alternativen. Dieser Artikel beschreibt die Entwicklung der Erntemethoden in den letzten 50 Jahren. Der wichtigste Schritt war die Verwendung von undurchsichtigen schwarz/weißen Folien zum Abdecken der Spargeldämme, um seltener zu stechen. Auf dieser Grundlage wurden verschiedene Ernteverfahren entwickelt. Angefangen bei der Handernte mit Körben, folgten Schiebewagen und ein- bis mehrreihige motorisierte Erntehilfen. Parallel dazu wurden nicht-selektive und selektive mechanische Erntemaschinen entwickelt. Die Vor- und Nachteile der einzelnen Verfahren werden beschrieben

Generalized Parton Distributions -- theoretical review --

In this talk an introduction to generalized parton distributions is given. Recent developments are shortly reviewed, including non-perturbative calculations, phenomenological aspects and evaluation of higher order perturbative and power corrections.Comment: 11 pages, 5 figure