papers

Publications (14)

cs.RO2025

Target Tracking via LiDAR-RADAR Sensor Fusion for Autonomous Racing

Marcello Cellina, Matteo Corno, Sergio Matteo Savaresi

High Speed multi-vehicle Autonomous Racing will increase the safety and performance of road-going Autonomous Vehicles. Precise vehicle detection and dynamics estimation from a movi…

cs.CV2025

A Multimodal Hybrid Late-Cascade Fusion Network for Enhanced 3D Object Detection

Carlo Sgaravatti, Roberto Basla, Riccardo Pieroni +4

We present a new way to detect 3D objects from multimodal inputs, leveraging both LiDAR and RGB cameras in a hybrid late-cascade scheme, that combines an RGB detection network and…

cs.RO2024

Mobile Robot Localization: a Modular, Odometry-Improving Approach

Luca Mozzarelli, Luca Cattaneo, Matteo Corno +1

Despite the number of works published in recent years, vehicle localization remains an open, challenging problem. While map-based localization and SLAM algorithms are getting bette…

eess.SY2023

Non-Invasive Experimental Identification of a Single Particle Model for LiFePO4 Cells

Andrea Trivella, Matteo Corno, Stefano Radrizzani +1

The rapid spread of Lithium-ions batteries (LiBs) for electric vehicles calls for the development of accurate physical models for Battery Management Systems (BMSs). In this work, t…

cs.RO2024

Learning-Based On-Track System Identification for Scaled Autonomous Racing in Under a Minute

Onur Dikici, Edoardo Ghignone, Cheng Hu +5

Accurate tire modeling is crucial for optimizing autonomous racing vehicles, as state-of-the-art (SotA) model-based techniques rely on precise knowledge of the vehicle's parameters…

cs.RO2025

Hybrid Imitation-Learning Motion Planner for Urban Driving

Cristian Gariboldi, Matteo Corno, Beng Jin

With the release of open source datasets such as nuPlan and Argoverse, the research around learning-based planners has spread a lot in the last years. Existing systems have shown e…

cs.RO2024

Multi-Object Tracking with Camera-LiDAR Fusion for Autonomous Driving

Riccardo Pieroni, Simone Specchia, Matteo Corno +1

This paper presents a novel multi-modal Multi-Object Tracking (MOT) algorithm for self-driving cars that combines camera and LiDAR data. Camera frames are processed with a state-of…

cs.CV2026

LCF3D: A Robust and Real-Time Late-Cascade Fusion Framework for 3D Object Detection in Autonomous Driving

Carlo Sgaravatti, Riccardo Pieroni, Matteo Corno +3

Accurately localizing 3D objects like pedestrians, cyclists, and other vehicles is essential in Autonomous Driving. To ensure high detection performance, Autonomous Vehicles comple…

cs.RO2025

BUDD-e: an autonomous robotic guide for visually impaired users

Jinyang Li, Marcello Farina, Luca Mozzarelli +7

This paper describes the design and the realization of a prototype of the novel guide robot BUDD-e for visually impaired users. The robot has been tested in a real scenario with th…

cs.RO2025

LiDAR-Based Vehicle Detection and Tracking for Autonomous Racing

Marcello Cellina, Matteo Corno, Sergio Matteo Savaresi

Autonomous racing provides a controlled environment for testing the software and hardware of autonomous vehicles operating at their performance limits. Competitive interactions bet…

cs.RO2024

Automatic Navigation Map Generation for Mobile Robots in Urban Environments

Luca Mozzarelli, Simone Specchia, Matteo Corno +1

A fundamental prerequisite for safe and efficient navigation of mobile robots is the availability of reliable navigation maps upon which trajectories can be planned. With the incre…

eess.SY2023

Handling-Oriented Stiffness Control of a Multichamber Suspension

Gabriele Marini, Giulio Panzani, Matteo Corno +2

This paper deals with the development of a handling-oriented stiffness control strategy using multichamber suspensions. Indeed, being this technology capable of stiffness variabili…

eess.SY2023

Twin-in-the-loop state estimation for vehicle dynamics control: theory and experiments

Giorgio Riva, Simone Formentin, Matteo Corno +1

In vehicle dynamics control, many variables of interest cannot be directly measured, as sensors might be costly, fragile, or even not available. Therefore, real-time estimation tec…

eess.SY2020

Experimental Automatic Calibration of a Semi-Active Suspension Controller via Bayesian Optimization

Gianluca Savaia, Youngil Sohn, Simone Formentin +3

The End-of-Line (EoL) calibration of semi-active suspension systems for road vehicles is usually a critical and expensive task, needing a team of vehicle and control experts as wel…