78 citations · 279 across the 20 of their papers we have counts for
20 papers
Active Illumination for Visual Ego-Motion Estimation in the Dark
Francesco Crocetti, Alberto Dionigi, Raffaele Brilli +2
Visual Odometry (VO) and Visual SLAM (V-SLAM) systems often struggle in low-light and dark environments due to the lack of robust visual features. In this paper, we propose a novel…
The Power of Input: Benchmarking Zero-Shot Sim-To-Real Transfer of Reinforcement Learning Control Policies for Quadrotor Control
Alberto Dionigi, Gabriele Costante, Giuseppe Loianno
In the last decade, data-driven approaches have become popular choices for quadrotor control, thanks to their ability to facilitate the adaptation to unknown or uncertain flight co…
Infrastructure-less UWB-based Active Relative Localization
Valerio Brunacci, Alberto Dionigi, Alessio De Angelis +1
In multi-robot systems, relative localization between platforms plays a crucial role in many tasks, such as leader following, target tracking, or cooperative maneuvering. State of…
Almost Global Trajectory Tracking for Quadrotors Using Thrust Direction Control on
Mirko Leomanni, Alberto Dionigi, Francesco Ferrante +2
Many of the existing works on quadrotor control address the trajectory tracking problem by employing a cascade design in which the translational and rotational dynamics are stabili…
Exploring Deep Reinforcement Learning for Robust Target Tracking using Micro Aerial Vehicles
Alberto Dionigi, Mirko Leomanni, Alessandro Saviolo +2
The capability to autonomously track a non-cooperative target is a key technological requirement for micro aerial vehicles. In this paper, we propose an output feedback control sch…
D-VAT: End-to-End Visual Active Tracking for Micro Aerial Vehicles
Alberto Dionigi, Simone Felicioni, Mirko Leomanni +1
Visual active tracking is a growing research topic in robotics due to its key role in applications such as human assistance, disaster recovery, and surveillance. In contrast to pas…
GaPT: Gaussian Process Toolkit for Online Regression with Application to Learning Quadrotor Dynamics
Francesco Crocetti, Jeffrey Mao, Alessandro Saviolo +2
Gaussian Processes (GPs) are expressive models for capturing signal statistics and expressing prediction uncertainty. As a result, the robotics community has gathered interest in l…
A Robust Data-Driven Fault Diagnosis scheme based on Recursive Dempster-Shafer Combination Rule *
Cartocci N., M. R. Napolitano, G. Costante +3
In-flight sensor fault diagnosis and recursive combination of residual signals via the Dempster-Shafer (DS) theory have been considered in this study. In particular, a novel eviden…
PCA Methods and Evidence Based Filtering for Robust Aircraft Sensor Fault Diagnosis
N. Cartocci, G. Costante, M. R. Napolitano +3
In this paper PCA and D-PCA techniques are applied for the design of a Data Driven diagnostic Fault Isolation (FI) and Fault Estimation (FE) scheme for 18 primary sensors of a semi…
Development of a Cooperative Localization System using a UWB Network and BLE Technology
Valerio Brunacci, Alessio De Angelis, Gabriele Costante
This paper presents the development of a system able to estimate the 2D relative position of nodes in a wireless network, based on distance measurements between the nodes. The syst…
Tire-road friction estimation and uncertainty assessment to improve electric aircraft braking system
Francesco Crocetti, G. Costante, M. L. Fravolini +1
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 Ne…
A Data-Driven Slip Estimation Approach for Effective Braking Control under Varying Road Conditions
F. Crocetti, G. Costante, M. L. Fravolini +1
The performances of braking control systems for robotic platforms, e.g., assisted and autonomous vehicles, airplanes and drones, are deeply influenced by the road-tire friction exp…
Forecasting consumer confidence through semantic network analysis of online news
A. Fronzetti Colladon, F. Grippa, B. Guardabascio +2
This research studies the impact of online news on social and economic consumer perceptions through semantic network analysis. Using over 1.8 million online articles on Italian med…
The Role of the Input in Natural Language Video Description
Silvia Cascianelli, Gabriele Costante, Alessandro Devo +3
Natural Language Video Description (NLVD) has recently received strong interest in the Computer Vision, Natural Language Processing (NLP), Multimedia, and Autonomous Robotics commu…
Enhancing Continuous Control of Mobile Robots for End-to-End Visual Active Tracking
Alessandro Devo, Alberto Dionigi, Gabriele Costante
In the last decades, visual target tracking has been one of the primary research interests of the Robotics research community. The recent advances in Deep Learning technologies hav…
Towards Monocular Digital Elevation Model (DEM) Estimation by Convolutional Neural Networks - Application on Synthetic Aperture Radar Images
Gabriele Costante, Thomas A. Ciarfuglia, Filippo Biondi
Synthetic aperture radar (SAR) interferometry (InSAR) is performed using repeat-pass geometry. InSAR technique is used to estimate the topographic reconstruction of the earth surfa…
J-MOD: Joint Monocular Obstacle Detection and Depth Estimation
Michele Mancini, Gabriele Costante, Paolo Valigi +1
In this work, we propose an end-to-end deep architecture that jointly learns to detect obstacles and estimate their depth for MAV flight applications. Most of the existing approach…
LS-VO: Learning Dense Optical Subspace for Robust Visual Odometry Estimation
Gabriele Costante, Thomas A. Ciarfuglia
This work proposes a novel deep network architecture to solve the camera Ego-Motion estimation problem. A motion estimation network generally learns features similar to Optical Flo…
Fast Robust Monocular Depth Estimation for Obstacle Detection with Fully Convolutional Networks
Michele Mancini, Gabriele Costante, Paolo Valigi +1
Obstacle Detection is a central problem for any robotic system, and critical for autonomous systems that travel at high speeds in unpredictable environment. This is often achieved…
Perception-aware Path Planning
Gabriele Costante, Christian Forster, Jeffrey Delmerico +2
In this paper, we give a double twist to the problem of planning under uncertainty. State-of-the-art planners seek to minimize the localization uncertainty by only considering the…