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This article proposes a Novel Nonlinear Model Predictive Control (NMPC) for navigation and obstacle avoidance of an Unmanned Aerial Vehicle (UAV). The proposed NMPC formulation allows for a fully parametric obstacle trajectory, while in…

We present an iterative overlap estimation technique to augment existing point cloud registration algorithms that can achieve high performance in difficult real-world situations where large pose displacement and non-overlapping geometry…

Computer Vision and Pattern Recognition · Computer Science 2018-08-08 Ben Eckart , Kihwan Kim , Jan Kautz

This paper presents a stochastic model predictive control approach for nonlinear systems subject to time-invariant probabilistic uncertainties in model parameters and initial conditions. The stochastic optimal control problem entails a cost…

Optimization and Control · Mathematics 2014-10-17 Stefan Streif , Matthias Karl , Ali Mesbah

This work introduces a novel analytical model for estimating the airspeed of fixed-wing Unmanned Aerial Vehicles (UAVs) using solely propeller power and rotational speed measurements. The model can be used to replace Pitot-tube-based…

Systems and Control · Electrical Eng. & Systems 2025-07-08 Evangelos Ntouros , Pavel Kelley , Ewoud Smeur

Take-off and landing are the periods of a flight where aircraft are most vulnerable to a ground based rocket attack by terrorists. While aircraft approach and depart from airports on pre-defined flight paths, there is a degree of…

Applications · Statistics 2016-03-31 Willem J. Eerland , Simon Box

The Reduced-Basis Control-Variate Monte-Carlo method was introduced recently in [S. Boyaval and T. Leli\`evre, CMS, 8 2010] as an improved Monte-Carlo method, for the fast estimation of many parametrized expected values at many parameter…

Numerical Analysis · Mathematics 2015-06-04 Sébastien Boyaval

Models for predicting aircraft motion are an important component of modern aeronautical systems. These models help aircraft plan collision avoidance maneuvers and help conduct offline performance and safety analyses. In this article, we…

Machine Learning · Computer Science 2018-10-24 Shane Barratt , Mykel Kochenderfer , Stephen Boyd

Survival models are used in various fields, such as the development of cancer treatment protocols. Although many statistical and machine learning models have been proposed to achieve accurate survival predictions, little attention has been…

Machine Learning · Computer Science 2020-03-26 Hrushikesh Loya , Pranav Poduval , Deepak Anand , Neeraj Kumar , Amit Sethi

In this paper we present a sensitivity analysis for the so-called fully probabilistic control scheme. This scheme attempts to control a system modeled via a probability density function (pdf) and does so by computing a probabilistic control…

Optimization and Control · Mathematics 2019-03-25 Bernat Guillen Pegueroles , Giovanni Russo

The formation and accretion of ice on the leading edge of a wing can be detrimental to airplane performance. Complicating this reality is the fact that even a small amount of uncertainty in the shape of the accreted ice may result in a…

Data Analysis, Statistics and Probability · Physics 2014-11-14 Anthony M. DeGennaro , Clarence W. Rowley , Luigi Martinelli

Airfoil icing is a severe safety hazard in aviation and causes power losses on wind turbines. The precise shape of the ice formation is subject to large uncertainties, so uncertainty quantification (UQ) is needed for a reliable prediction…

Fluid Dynamics · Physics 2023-07-21 Jakob Dürrwächter , Andrea Beck , Claus-Dieter Munz

The accurate online estimation of the road-friction coefficient is an essential feature for any advanced brake control system. In this study, a data-driven scheme based on a MLP Neural Net is proposed to estimate the optimum friction…

Systems and Control · Electrical Eng. & Systems 2022-11-21 Francesco Crocetti , G. Costante , M. L. Fravolini , P. Valigi

In this article, we consider computing expectations w.r.t. probability measures which are subject to discretization error. Examples include partially observed diffusion processes or inverse problems, where one may have to discretize time…

Computation · Statistics 2021-02-25 Jeremy Heng , Ajay Jasra , Kody J. H. Law , Alexander Tarakanov

A common way to simulate the transport and spread of pollutants in the atmosphere is via stochastic Lagrangian dispersion models. Mathematically, these models describe turbulent transport processes with stochastic differential equations…

Data-driven forecasts of air quality have recently achieved more accurate short-term predictions. Despite their success, most of the current data-driven solutions lack proper quantifications of model uncertainty that communicate how much to…

Machine Learning · Computer Science 2021-12-07 Abdulmajid Murad , Frank Alexander Kraemer , Kerstin Bach , Gavin Taylor

Counting experiments often rely on Monte Carlo simulations for predictions of Poisson expectations. The accompanying uncertainty from the finite Monte Carlo sample size can be incorporated into parameter estimation by modifying the Poisson…

Instrumentation and Methods for Astrophysics · Physics 2020-04-22 Thorsten Glüsenkamp

This paper presents a flight control design for compound Vertical Takeoff and Landing (VTOL) vehicles. With their multitude of degrees of controllability as well as the significant variations in their flight characteristics, VTOL vehicles…

Systems and Control · Electrical Eng. & Systems 2024-05-28 Jean-Marie Kai

This work studies the design of safe control policies for large-scale non-linear systems operating in uncertain environments. In such a case, the robust control framework is a principled approach to safety that aims to maximize the…

Systems and Control · Computer Science 2019-03-04 Edouard Leurent , Yann Blanco , Denis Efimov , Odalric-Ambrym Maillard

Airfoil shape optimization plays a critical role in the design of high-performance aircraft. However, the high-dimensional nature of airfoil representation causes the challenging problem known as the "curse of dimensionality". To overcome…

Machine Learning · Computer Science 2023-11-21 Yu-Eop Kang , Dawoon Lee , Kwanjung Yee

For accomplishing a variety of missions in challenging environments, the capability of navigating with full autonomy while avoiding unexpected obstacles is the most crucial requirement for UAVs in real applications. In this paper, we…

Robotics · Computer Science 2020-12-29 Han Chen , Peng Lu
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