A Survey of Offline and Online Learning-Based Algorithms for Multirotor UAVs

Multirotor UAVs are used for a wide spectrum of civilian and public domain applications. Navigation controllers endowed with different attributes and onboard sensor suites enable multirotor autonomous or semi-autonomous, safe flight, operation, and functionality under nominal and detrimental conditions and external disturbances, even when flying in uncertain and dynamically changing environments. During the last decade, given the faster-than-exponential increase of available computational power, different learning-based algorithms have been derived, implemented, and tested to navigate and control, among other systems, multirotor UAVs. Learning algorithms have been, and are used to derive data-driven based models, to identify parameters, to track objects, to develop navigation controllers, and to learn the environment in which multirotors operate. Learning algorithms combined with model-based control techniques have been proven beneficial when applied to multirotors. This survey summarizes published research since 2015, dividing algorithms, techniques, and methodologies into offline and online learning categories, and then, further classifying them into machine learning, deep learning, and reinforcement learning sub-categories. An integral part and focus of this survey are on online learning algorithms as applied to multirotors with the aim to register the type of learning techniques that are either hard or almost hard real-time implementable, as well as to understand what information is learned, why, and how, and how fast. The outcome of the survey offers a clear understanding of the recent state-of-the-art and of the type and kind of learning-based algorithms that may be implemented, tested, and executed in real-time.Comment: 26 pages, 6 figures, 4 tables, Survey Pape

Correction to the Euler Lagrange multirotor model with Euler angles generalized coordinates

This technical note proves analytically how the exact equivalence of the Newton-Euler and Euler-Lagrange modeling formulations as applied to multirotor UAVs is achieved. This is done by deriving a correct Euler-Lagrange multirotor attitude dynamics model. A review of the published literature reveals that the commonly adopted Euler-Lagrange multirotor dynamics model is equivalent to the Newton-Euler model only when it comes to the position dynamics, but not in the attitude dynamics. Step-by-step derivations and calculations are provided to show how modeling equivalence to the Newton-Euler formulation is proven. The modeling equivalence is then verified by obtaining identical results in numerical simulation studies. Simulation results also illustrate that when using the correct model for feedback linearization, controller stability at high gains is improved

A Taxonomy for Organizing the Core Concepts According to Their Underlying Principles

This article organizes and classifies the 18 core concepts. There are nine overarching principles into which the concepts fit: life, liberty, equality, dignity, family as foundation, community, capacity, individualization, and accountability. These in turn reflect three approaches to policy: the Constitutional approach, consisting of the principles of life, liberty, and equality; the Ethical approach, consisting of the principles of dignity, family as foundation, and community; and the administrative approach, consisting of the principles of capacity, individualization, and accountability. There is also a set of Professional principles, which the article illustrates with examples from the field of medicine/health care. Finally, the article demonstrates how the organization and classification of the core concepts create a wholistic, unified approach to policy

Motion corrected fetal body magnetic resonance imaging provides reliable 3D lung volumes in normal and abnormal fetuses

Objectives: To calculate 3D-segmented total lung volume (TLV) in fetuses with thoracic anomalies using deformable slice-to-volume registration (DSVR) with comparison to 2D-manual segmentation. To establish a normogram of TLV calculated by DSVR in healthy control fetuses. Methods: A pilot study at a single regional fetal medicine referral centre included 16 magnetic resonance imaging (MRI) datasets of fetuses (22–32 weeks gestational age). Diagnosis was CDH (n = 6), CPAM (n = 2), and healthy controls (n = 8). Deformable slice-to-volume registration was used for reconstruction of 3D isotropic (0.85 mm) volumes of the fetal body followed by semi-automated lung segmentation. 3D TLV were compared to traditional 2D-based volumetry. Abnormal cases referenced to a normogram produced from 100 normal fetuses whose TLV was calculated by DSVR only. Results: Deformable slice-to-volume registration-derived TLV values have high correlation with the 2D-based measurements but with a consistently lower volume; bias −1.44 cm3 [95% limits: −2.6 to −0.3] with improved resolution to exclude hilar structures even in cases of motion corruption or very low lung volumes. Conclusions: Deformable slice-to-volume registration for fetal lung MRI aids analysis of motion corrupted scans and does not suffer from the interpolation error inherent to 2D-segmentation. It increases information content of acquired data in terms of visualising organs in 3D space and quantification of volumes, which may improve counselling and surgical planning

2D-IR spectroscopy of proteins in H2O – a perspective

The form of the amide I infrared absorption band provides a sensitive probe of the secondary structure and dynamics of proteins in the solution phase. However, the frequency coincidence of the amide I band with the bending vibrational mode of H2O has necessitated the widespread use of deuterated solvents. Recently, it has been demonstrated that ultrafast 2D-IR spectroscopy allows the detection of the protein amide I band in H2O-based fluids, meaning that IR methods can now be applied to study proteins in physiologically relevant solvents. In this perspective, we describe the basis of the 2D-IR method for observing the protein amide I band in H2O and show how this development has the potential to impact on areas ranging from our fundamental appreciation of protein structural dynamics to new applications for 2D-IR spectroscopy in the analytical and biomedical sciences. In addition, we discuss how the spectral response of water, rather than being a hindrance, now provides a basis for new approaches to data pre-processing, standardisation of 2D-IR data collection and signal quantification. Ultimately, we visualise a direction of travel towards the creation of 2D-IR spectral libraries that can be linked to advanced computational methods for use in high-throughput protein screening and disease diagnosis

Fetal body MRI and its application to fetal and neonatal treatment: an illustrative review

This Review depicts the evolving role of MRI in the diagnosis and prognostication of anomalies of the fetal body, here including head and neck, thorax, abdomen and spine. A review of the current literature on the latest developments in antenatal imaging for diagnosis and prognostication of congenital anomalies is coupled with illustrative cases in true radiological planes with viewable three-dimensional video models that show the potential of post-acquisition reconstruction protocols. We discuss the benefits and limitations of fetal MRI, from anomaly detection, to classification and prognostication, and defines the role of imaging in the decision to proceed to fetal intervention, across the breadth of included conditions. We also consider the current capabilities of ultrasound and explore how MRI and ultrasound can complement each other in the future of fetal imaging

2D-infrared spectroscopy of proteins in water : using the solvent thermal response as an internal standard

Ultrafast two-dimensional infrared (2D-IR) spectra can now be obtained in a matter of seconds, opening up the possibility of high-throughput screening applications of relevance to the biomedical and pharmaceutical sectors. Determining quantitative information from 2D-IR spectra recorded on different samples and different instruments is however made difficult by variations in beam alignment, laser intensity, and sample conditions. Recently, we demonstrated that 2D-IR spectroscopy of the protein amide I band can be performed in aqueous (H2O) rather than deuterated (D2O) solvents, and we now report a method that uses the magnitude of the associated thermal response of H2O as an internal normalization standard for 2D-IR spectra. Using the water response, which is temporally separated from the protein signal, to normalize the spectra allows significant reduction of the impact of measurement-to-measurement fluctuations on the data. We demonstrate that this normalization method enables creation of calibration curves for measurement of absolute protein concentrations and facilitates reproducible difference spectroscopy methodologies. These advances make significant progress toward the robust data handling strategies that will be essential for the realization of automated spectral analysis tools for large scale 2D-IR screening studies of protein-containing solutions and biofluids