12 citations · 32 across the 10 of their papers we have counts for
8 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…
IMU-Centric Moving Horizon Estimation for Lateral Dynamics Estimation Across Vehicles and Grip Conditions
Seuffo Akouan ha Ngoune, Alessandro Toschi, Paolo Burgio +1
Accurate estimation of lateral vehicle dynamics near the adhesion limit is important for stability control and high-performance driving, but lateral velocity is rarely measured dir…
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…