12 citations · 32 across the 10 of their papers we have counts for
12 papers · 1 filter
High-Fidelity Multi-Body Simulator for Autonomous Racing
Nicola Musiu, Francesco Iacovacci, Fausto Lupo +11
We present a custom high-fidelity vehicle dynamics simulation environment for testing and validation of Autonomous Racing software. The digital twin of the autonomous vehicle is de…
Driving Context-guided Model Predictive Planning and Control for Autonomous Car Racing at the Limit and Beyond
Ayoub Raji, Federico Sacco, Nicola Musiu +1
This paper presents a Model Predictive Control-based motion planning and control pipeline for autonomous car racing capable of adapting to different driving contexts, such as overt…
Mission Performance: Automatic and Adaptive Race Pace Progression for Autonomous Racing
Giovanni Lambertini, Matteo Pini, Nicola Musiu +3
In this paper, we describe the Mission Performance module implemented for a fully autonomous racing car to automatically manage the longitudinal, lateral, and combined performances…
A Multi-Modal Perception Pipeline for Object Detection and Tracking in Autonomous Racing
Davide Malvezzi, Michele Pestarino, Vittoria Cavicchioli +9
Object detection and tracking are fundamental components of perception systems for autonomous driving. Achieving robust performance under adverse conditions such as limited visibil…
A2RL V\textsubscript{max}: The A2RL autonomous racing dataset for long-range, high-speed perception and multi-vehicle interaction
Marvin Klemp, Dominic Ebner, Cornelius Schröder +15
In autonomous driving development, a perception dataset is crucial, as it provides fundamental data for training, testing, and validating algorithms for an autonomous vehicle's mul…
RAGE-XY: RADAR-Aided Longitudinal and Lateral Forces Estimation For Autonomous Race Cars
Davide Malvezzi, Nicola Musiu, Eugenio Mascaro +2
In this work, we present RAGE-XY, an extended version of RAGE, a real-time estimation framework that simultaneously infers vehicle velocity, tire slip angles, and the forces acting…
RAGE: A Tightly Coupled Radar-Aided Grip Estimator For Autonomous Race Cars
Davide Malvezzi, Nicola Musiu, Eugenio Mascaro +2
Real-time estimation of vehicle-tire-road friction is critical for allowing autonomous race cars to safely and effectively operate at their physical limits. Traditional approaches…
Fast and Realistic Automated Scenario Simulations and Reporting for an Autonomous Racing Stack
Giovanni Lambertini, Matteo Pini, Eugenio Mascaro +3
In this paper, we describe the automated simulation and reporting pipeline implemented for our autonomous racing stack, ur.autopilot. The backbone of the simulation is based on a h…
BETTY Dataset: A Multi-modal Dataset for Full-Stack Autonomy
Micah Nye, Ayoub Raji, Andrew Saba +9
We present the BETTY dataset, a large-scale, multi-modal dataset collected on several autonomous racing vehicles, targeting supervised and self-supervised state estimation, dynamic…
A Simulation Benchmark for Autonomous Racing with Large-Scale Human Data
Adrian Remonda, Nicklas Hansen, Ayoub Raji +4
Despite the availability of international prize-money competitions, scaled vehicles, and simulation environments, research on autonomous racing and the control of sports cars opera…
Guess the Drift with LOP-UKF: LiDAR Odometry and Pacejka Model for Real-Time Racecar Sideslip Estimation
Alessandro Toschi, Nicola Musiu, Francesco Gatti +4
The sideslip angle, crucial for vehicle safety and stability, is determined using both longitudinal and lateral velocities. However, measuring the lateral component often necessita…
er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds
Ayoub Raji, Danilo Caporale, Francesco Gatti +15
The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at unprecedented speed and in head-to-head scenario, using…