Francesco Crocetti
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View article: Comparison of DSO and ORB‐SLAM3 in Low‐Light Environments With Auxiliary Lighting and Deep Learning Based Image Enhancing
Comparison of DSO and ORB‐SLAM3 in Low‐Light Environments With Auxiliary Lighting and Deep Learning Based Image Enhancing Open
In the evolving landscape of robotic navigation, the demand for solutions capable of operating in challenging scenarios, such as low‐light environments, is increasing. This study investigates the performance of two state‐of‐the‐art (SOTA) …
View article: Active Illumination for Visual Ego-Motion Estimation in the Dark
Active Illumination for Visual Ego-Motion Estimation in the Dark Open
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 active illumination framework to enhance the performance o…
View article: AI-Driven Ground Robots: Mobile Edge Computing and mmWave Communications at Work
AI-Driven Ground Robots: Mobile Edge Computing and mmWave Communications at Work Open
The seamless integration of multiple radio access technologies (multi-RAT) and cloud/edge resources is pivotal for advancing future networks, which seek to unify distributed and heterogeneous computing and communication resources into a co…
View article: Data-driven and uncertainty-aware robust airstrip surface estimation
Data-driven and uncertainty-aware robust airstrip surface estimation Open
The performances of aircraft braking control systems are strongly influenced by the tire friction force experienced during the braking phase. The availability of an accurate estimate of the current airstrip characteristics is a recognized …
View article: Development and Validation of a Low-Cost Device for Real-Time Detection of Fatigue Damage of Structures Subjected to Vibrations
Development and Validation of a Low-Cost Device for Real-Time Detection of Fatigue Damage of Structures Subjected to Vibrations Open
This paper presents the development and validation of a low-cost device for real-time detection of fatigue damage of structures subjected to vibrations. The device consists of an hardware and signal processing algorithm to detect and monit…
View article: ARD‐VO: Agricultural robot data set of vineyards and olive groves
ARD‐VO: Agricultural robot data set of vineyards and olive groves Open
The availability of real‐world data in agricultural applications is of paramount importance to develop robust and effective robotic‐based solutions for farming operations. In this application context, however, very few data sets are availa…
View article: GaPT: Gaussian Process Toolkit for Online Regression with Application to Learning Quadrotor Dynamics
GaPT: Gaussian Process Toolkit for Online Regression with Application to Learning Quadrotor Dynamics Open
Gaussian Processes (GPs) are expressive models for capturing signal statistics and expressing prediction uncertainty. As a result, the robotics community has gathered interest in leveraging these methods for inference, planning, and contro…
View article: Data-Driven Fault Diagnosis Techniques: Non-Linear Directional Residual vs. Machine-Learning-Based Methods
Data-Driven Fault Diagnosis Techniques: Non-Linear Directional Residual vs. Machine-Learning-Based Methods Open
Linear dependence of variables is a commonly used assumption in most diagnostic systems for which many robust methodologies have been developed over the years. In case the system nonlinearities are relevant, fault diagnosis methods, relyin…
View article: A Robust Data-Driven Fault Diagnosis scheme based on Recursive Dempster–Shafer Combination Rule
A Robust Data-Driven Fault Diagnosis scheme based on Recursive Dempster–Shafer Combination Rule Open
In-flight sensor fault diagnosis and recursive combination of residual\nsignals via the Dempster-Shafer (DS) theory have been considered in this study.\nIn particular, a novel evidence-based combination rule of residual errors as a\nfuncti…
View article: Tire-road friction estimation and uncertainty assessment to improve electric aircraft braking system
Tire-road friction estimation and uncertainty assessment to improve electric aircraft braking system Open
The accurate online estimation of the road-friction coefficient is an\nessential feature for any advanced brake control system. In this study, a\ndata-driven scheme based on a MLP Neural Net is proposed to estimate the\noptimum friction co…
View article: Data‐based design of robust fault detection and isolation residuals via LASSO optimization and Bayesian filtering
Data‐based design of robust fault detection and isolation residuals via LASSO optimization and Bayesian filtering Open
In this paper, a data‐based approach for the design of structured residual subsets for the robust isolation of sensor faults is proposed. Linear regression models are employed to estimate faulty signals and to build a set of primary residu…
View article: A Data-Driven Slip Estimation Approach for Effective Braking Control under Varying Road Conditions
A Data-Driven Slip Estimation Approach for Effective Braking Control under Varying Road Conditions Open
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 experienced during the maneuver. Therefore, the availability o…
View article: PCA Methods and Evidence Based Filtering for Robust Aircraft Sensor Fault Diagnosis
PCA Methods and Evidence Based Filtering for Robust Aircraft Sensor Fault Diagnosis Open
In this paper PCA and D-PCA techniques are applied for the design of a Data\nDriven diagnostic Fault Isolation (FI) and Fault Estimation (FE) scheme for 18\nprimary sensors of a semi-autonomous aircraft. Specifically,\nContributions-based,…
View article: Data-Based Design of Robust Fault Isolation Residuals Using LASSO optimization
Data-Based Design of Robust Fault Isolation Residuals Using LASSO optimization Open
In this paper a data-based approach is proposed for the design of structured residual subsets for the robust isolation of sensor faults. Linear regression models are employed to estimate the faulty signals and to build a set of primary res…