Performance benchmarking of quadrotor systems using time-optimal control

Frequently hailed for their dynamical capabilities, quadrotor vehicles are often employed as experimental platforms. However, questions surrounding achievable performance, influence of design parameters, and performance assessment of control strategies have remained largely unanswered. This paper presents an algorithm that allows the computation of quadrotor maneuvers that satisfy Pontryagin's minimum principle with respect to time-optimality. Such maneuvers provide a useful lower bound on the duration of maneuvers, which can be used to assess performance of controllers and vehicle design parameters. Computations are based on a two-dimensional first-principles quadrotor model. The minimum principle is applied to this model to find that time-optimal trajectories are bang-bang in the thrust command, and bang-singular in the rotational rate control. This paper presents a procedure allowing the computation of time-optimal maneuvers for arbitrary initial and final states by solving the boundary value problem induced by the minimum principle. The usage of the computed maneuvers as a benchmark is demonstrated by evaluating quadrotor design parameters, and a linear feedback control law as an example of a control strategy. Computed maneuvers are verified experimentally by applying them to quadrocopters in the ETH Zurich Flying Machine Arena testbe

Schalldämpfung durch Wald (Teil 1): Vegetationsabhängige Abschirmwirkung von Wäldern – Messtechnische Verifizierung eines akustisch-meteorologischen Modells

Die meteorologischen und akustischen Messergebnisse dieser Studie ergeben zusammen mit dem akustisch-meteorologischen Modell der Vorgängerstudie (Schriftenreihe des LfULG, Heft 33/2014) eine umfangreiche Datenbank zur Abschirmwirkung von Waldgebieten. Die Messungen in verschiedenen Jahreszeiten quantifizieren außerdem den meteorologischen Einfluss auf die schalldämpfende Wirkung von Wald und auf die Schalldämpfung in unterschiedlichen Entfernungen vom Waldgebiet. Damit wurden der Wertebereich und weitere statistische Kenngrößen der akustischen Abschirmwirkung in Abhängigkeit von den Umgebungsbedingungen bestimmt

Schalldämpfung durch Wald (Teil 2): Vegetationsabhängige Abschirmwirkung von Wäldern – Messtechnische Verifizierung eines akustisch-meteorologischen Modells: Ergänzende Datenaufbereitung

Der Bericht dokumentiert eine ergänzende Studie zu den in Teil 1 der Schriftenreihe des LfULG (Heft 16/2016) veröffentlichten Ergebnissen. Damit ist eine Vergrößerung, Absicherung und erhöhte Verallgemeinerbarkeit der erhobenen Datenbasis gegeben. Die bereits vorhandenen akustischen Messwerte eines 5-Kanal-Systems wurden ausgewertet und mit den Daten von parallelen empfangsseitigen 5-Kanal-Messungen verglichen. Außerdem wurden Messdaten einer akustischen Kamera in die Auswertungen der vorliegenden Datenbasis einbezogen

Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe's terrestrial ecosystems : a review

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.Peer reviewe

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.Peer reviewe

Traces of trauma – a multivariate pattern analysis of childhood trauma, brain structure and clinical phenotypes

Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research