Related papers: Nuclear Environments Inspection with Micro Aerial …
The role of a motion planner is pivotal in quadrotor applications, yet existing methods often struggle to adapt to complex environments, limiting their ability to achieve fast, safe, and robust flight. In this letter, we introduce a…
Autonomous navigation in unknown environments with obstacles remains challenging for micro aerial vehicles (MAVs) due to their limited onboard computing and sensing resources. Although various collision avoidance methods have been…
Unmanned Aerial Vehicles (UAVs) are getting closer to becoming ubiquitous in everyday life. Among them, Micro Aerial Vehicles (MAVs) have seen an outburst of attention recently, specifically in the area with a demand for autonomy. A key…
The decreased size and cost of Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) has enabled the use of swarms of unmanned autonomous vehicles to accomplish a variety of tasks. By utilizing swarming behaviors, it is…
Various studies on perception-aware planning have been proposed to enhance the state estimation accuracy of quadrotors in visually degraded environments. However, many existing methods heavily rely on prior environmental knowledge and face…
In this paper, we discuss the feasibility of measuring deeply virtual Compton scattering (DVCS) on nuclei in a collider setting, as for example, the planned high-luminosity Electron-Ion-Collider (EIC). We demonstrate that employing our…
Digital documentation of large interiors of historical buildings is an exhausting task since most of the areas of interest are beyond typical human reach. We advocate the use of autonomous teams of multi-rotor Unmanned Aerial Vehicles…
Unmanned Aerial Vehicles (UAVs) equipped with bioradars are a life-saving technology that can enable identification of survivors under collapsed buildings in the aftermath of natural disasters such as earthquakes or gas explosions. However,…
We consider a class of partially observable Markov decision processes (POMDPs) with uncertain transition and/or observation probabilities. The uncertainty takes the form of probability intervals. Such uncertain POMDPs can be used, for…
Neutral atom quantum computers require accurate single atom detection for the preparation and readout of their qubits. This is usually done using fluorescence imaging. The occupancy of an atom site in these images is often somewhat…
Photovoltaic (PV) panels are becoming increasingly widespread in the domain of renewable energy, and thus, small efficiency gains can have massive effects. Anti-reflective and self-cleaning coatings enhance panel performance but degrade…
This paper presents a study on the development of an obstacle-avoidance navigation system for autonomous navigation in home environments. The system utilizes vision-based techniques and advanced path-planning algorithms to enable the robot…
In the framework of risk assessment in nuclear accident analysis, best-estimatecomputer codes, associated to a probabilistic modeling of the uncertain input variables,are used to estimate safety margins. A first step in such uncertainty…
This paper describes how advanced deep learning based computer vision algorithms are applied to enable real-time on-board sensor processing for small UAVs. Four use cases are considered: target detection, classification and localization,…
This paper explores the application of vision-based system identification techniques in quadrotor modeling and control. Through experiments and analysis, we address the complexities and limitations of quadrotor modeling, particularly in…
Random cost simulations were introduced as a method to investigate optimization problems in systems with conflicting constraints. Here I study the approach in connection with the training of a feed-forward multilayer perceptron, as used in…
The Jiangmen Underground Neutrino Observatory (JUNO) is a multi-purpose experiment under construction in southern China. JUNO aims to determine the neutrino mass ordering and precisely measure the neutrino oscillation parameters by…
Autonomous Micro Aerial Vehicles (MAVs) such as quadrotors equipped with manipulation mechanisms have the potential to assist humans in tasks such as construction and package delivery. Cables are a promising option for manipulation…
Variational quantum algorithms (VQA) have emerged as a promising quantum alternative for solving optimization and machine learning problems using parameterized quantum circuits (PQCs). The design of these circuits influences the ability of…
An important open problem in robotic planning is the autonomous generation of 3D inspection paths -- that is, planning the best path to move a robot along in order to inspect a target structure. We recently suggested a new method for…