Vision and Learning for Deliberative Monocular Cluttered Flight

Cameras provide a rich source of information while being passive, cheap and lightweight for small and medium Unmanned Aerial Vehicles (UAVs). In this work we present the first implementation of receding horizon control, which is widely used in ground vehicles, with monocular vision as the only sensing mode for autonomous UAV flight in dense clutter. We make it feasible on UAVs via a number of contributions: novel coupling of perception and control via relevant and diverse, multiple interpretations of the scene around the robot, leveraging recent advances in machine learning to showcase anytime budgeted cost-sensitive feature selection, and fast non-linear regression for monocular depth prediction. We empirically demonstrate the efficacy of our novel pipeline via real world experiments of more than 2 kms through dense trees with a quadrotor built from off-the-shelf parts. Moreover our pipeline is designed to combine information from other modalities like stereo and lidar as well if available

Robust Cardiac Motion Estimation using Ultrafast Ultrasound Data: A Low-Rank-Topology-Preserving Approach

Cardiac motion estimation is an important diagnostic tool to detect heart diseases and it has been explored with modalities such as MRI and conventional ultrasound (US) sequences. US cardiac motion estimation still presents challenges because of the complex motion patterns and the presence of noise. In this work, we propose a novel approach to estimate the cardiac motion using ultrafast ultrasound data. -- Our solution is based on a variational formulation characterized by the L2-regularized class. The displacement is represented by a lattice of b-splines and we ensure robustness by applying a maximum likelihood type estimator. While this is an important part of our solution, the main highlight of this paper is to combine a low-rank data representation with topology preservation. Low-rank data representation (achieved by finding the k-dominant singular values of a Casorati Matrix arranged from the data sequence) speeds up the global solution and achieves noise reduction. On the other hand, topology preservation (achieved by monitoring the Jacobian determinant) allows to radically rule out distortions while carefully controlling the size of allowed expansions and contractions. Our variational approach is carried out on a realistic dataset as well as on a simulated one. We demonstrate how our proposed variational solution deals with complex deformations through careful numerical experiments. While maintaining the accuracy of the solution, the low-rank preprocessing is shown to speed up the convergence of the variational problem. Beyond cardiac motion estimation, our approach is promising for the analysis of other organs that experience motion.Comment: 15 pages, 10 figures, Physics in Medicine and Biology, 201

Fluid flow queue models for fixed-mobile network evaluation

A methodology for fast and accurate end-to-end KPI, like throughput and delay, estimation is proposed based on the service-centric traffic flow analysis and the fluid flow queuing model named CURSA-SQ. Mobile network features, like shared medium and mobility, are considered defining the models to be taken into account such as the propagation models and the fluid flow scheduling model. The developed methodology provides accurate computation of these KPIs, while performing orders of magnitude faster than discrete event simulators like ns-3. Finally, this methodology combined to its capacity for performance estimation in MPLS networks enables its application for near real-time converged fixed-mobile networks operation as it is proven in three use case scenarios

Dark-Ages Reionisation & Galaxy Formation Simulation XVI: The Thermal Memory of Reionisation

Intergalactic medium temperature is a powerful probe of the epoch of reionisation, as information is retained long after reionisation itself. However, mean temperatures are highly degenerate with the timing of reionisation, with the amount heat injected during the epoch, and with the subsequent cooling rates. We post-process a suite of semi-analytic galaxy formation models to characterise how different thermal statistics of the intergalactic medium can be used to constrain reionisation. Temperature is highly correlated with redshift of reionisation for a period of time after the gas is heated. However as the gas cools, thermal memory of reionisation is lost, and a power-law temperature-density relation is formed, $T = T_0(1+\delta)^{1-\gamma}$ with $\gamma \approx 1.5$. Constraining our model against observations of electron optical depth and temperature at mean density, we find that reionisation likely finished at $z_{\rm{reion}} = 6.8 ^{+ 0.5} _{-0.8}$ with a soft spectral slope of $\alpha = 2.8 ^{+ 1.2} _{-1.0}$. By restricting spectral slope to the range $[0.5,2.5]$ motivated by population II synthesis models, reionisation timing is further constrained to $z_{\rm{reion}} = 6.9 ^{+ 0.4} _{-0.5}$. We find that, in the future, the degeneracies between reionisation timing and background spectrum can be broken using the scatter in temperatures and integrated thermal history.Comment: 17 pages, 17 figures, Accepted for publication in MNRA

Reducing Drift in Parametric Motion Tracking

We develop a class of differential motion trackers that automatically stabilize when in finite domains. Most differ-ential trackers compute motion only relative to one previous frame, accumulating errors indefinitely. We estimate pose changes between a set of past frames, and develop a probabilistic framework for integrating those estimates. We use an approximation to the posterior distribution of pose changes as an uncertainty model for parametric motion in order to help arbitrate the use of multiple base frames. We demonstrate this framework on a simple 2D translational tracker and a 3D, 6-degree of freedom tracker

Magnetic activity, differential rotation and dynamo action in the pulsating F9IV star KIC 5955122

We present photometric spot modeling of the nearly four-year long light-curve of the Kepler target KIC 5955122 in terms of persisting dark circular surface features. With a Bayesian technique, we produced a plausible surface map that shows dozens of small spots. After some artifacts are removed, the residuals are at $\pm 0.16$\,mmag. The shortest rotational period found is $P = 16.4 \pm 0.2$ days. The equator-to-pole extrapolated differential rotation is $0.25 \pm 0.02$ rad/d. The spots are roughly half as bright as the unperturbed stellar photosphere. Spot latitudes are restricted to the zone $\pm 60^\circ$ latitude. There is no indication for any near-pole spots. In addition, the p-mode pulsations enabled us to determine the evolutionary status of the star, the extension of the convective zone, and its radius and mass. We discuss the possibility that the clear signature of active regions in the light curve of the F9IV star KIC 5955122 is produced by a flux-transport dynamo action at the base of the convection zone. In particular, we argue that this star has evolved from an active to a quiet status during the Q0--Q16 period of observation, and we predict, according to our dynamo model, that the characteristic activity cycle is of the order of the solar one.Comment: 9 pages, 12 figures, to be published on A&