Mattia Piccinini

According to our database, Mattia Piccinini authored at least 19 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

SAVANT: Semantic Analysis with Vision-Augmented Anomaly deTection.

Roberto Brusnicki, David Pop, Yuan Gao, Mattia Piccinini, Johannes Betz

CoRR, October, 2025

Reinforcement Learning-based Dynamic Adaptation for Sampling-Based Motion Planning in Agile Autonomous Driving.

Alexander Langmann, Yevhenii Tokarev, Mattia Piccinini, Korbinian Möller, Johannes Betz

CoRR, October, 2025

Real-time Velocity Profile Optimization for Time-Optimal Maneuvering with Generic Acceleration Constraints.

Mattia Piazza, Mattia Piccinini, Sebastiano Taddei, Francesco Biral, Enrico Bertolazzi

CoRR, September, 2025

NuRisk: A Visual Question Answering Dataset for Agent-Level Risk Assessment in Autonomous Driving.

Yuan Gao, Mattia Piccinini, Roberto Brusnicki, Yuchen Zhang, Johannes Betz

CoRR, September, 2025

Learning to Sample: Reinforcement Learning-Guided Sampling for Autonomous Vehicle Motion Planning.

Korbinian Möller, Roland Stroop, Mattia Piccinini, Alexander Langmann, Johannes Betz

CoRR, September, 2025

Enhancing Physical Consistency in Lightweight World Models.

Dingrui Wang, Zhexiao Sun, Zhouheng Li, Cheng Wang, Youlun Peng, Hongyuan Ye, Baha Zarrouki, Wei Li, Mattia Piccinini, Lei Xie, Johannes Betz

CoRR, September, 2025

Model-Structured Neural Networks to Control the Steering Dynamics of Autonomous Race Cars.

Mattia Piccinini, Aniello Mungiello, Georg Jank, Gastone Pietro Rosati Papini, Francesco Biral, Johannes Betz

CoRR, July, 2025

MP-RBFN: Learning-based Vehicle Motion Primitives using Radial Basis Function Networks.

Marc Kaufeld, Mattia Piccinini, Johannes Betz

CoRR, July, 2025

Safe Reinforcement Learning with a Predictive Safety Filter for Motion Planning and Control: A Drifting Vehicle Example.

Bei Zhou, Baha Zarrouki, Mattia Piccinini, Cheng Hu, Lei Xie, Johannes Betz

CoRR, June, 2025

Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis.

Yuan Gao, Mattia Piccinini, Yuchen Zhang, Dingrui Wang, Korbinian Möller, Roberto Brusnicki, Baha Zarrouki, Alessio Gambi, Jan Frederik Totz, Kai Storms, Steven Peters, Andrea Stocco, Bassam Alrifaee, Marco Pavone, Johannes Betz

CoRR, June, 2025

Biasing the Driving Style of an Artificial Race Driver for Online Time-Optimal Maneuver Planning.

Sebastiano Taddei, Mattia Piccinini, Francesco Biral

CoRR, April, 2025

A Quasi-Steady-State Black Box Simulation Approach for the Generation of g-g-g-v Diagrams.

Frederik Werner, Simon Sagmeister, Mattia Piccinini, Johannes Betz

CoRR, April, 2025

Risk-Aware Driving Scenario Analysis with Large Language Models.

Yuan Gao, Mattia Piccinini, Johannes Betz

CoRR, February, 2025

Kineto-Dynamical Planning and Accurate Execution of Minimum-Time Maneuvers on Three-Dimensional Circuits.

Mattia Piccinini, Sebastiano Taddei, Johannes Betz, Francesco Biral

Proceedings of the IEEE International Conference on Robotics and Automation, 2025

2024

Reinforcement Learning and Optimal Control: A Hybrid Collision Avoidance Approach.

Simon Gottschalk, Matthias Gerdts, Mattia Piccinini

Proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems, 2024

2023

Robust and Sample-Efficient Estimation of Vehicle Lateral Velocity Using Neural Networks With Explainable Structure Informed by Kinematic Principles.

Mauro Da Lio, Mattia Piccinini, Francesco Biral

IEEE Trans. Intell. Transp. Syst., December, 2023

A Physics-Driven Artificial Agent for Online Time-Optimal Vehicle Motion Planning and Control.

Mattia Piccinini, Sebastiano Taddei, Matteo Larcher, Mattia Piazza, Francesco Biral

IEEE Access, 2023

Fast Planning and Tracking of Complex Autonomous Parking Maneuvers With Optimal Control and Pseudo-Neural Networks.

Edoardo Pagot, Mattia Piccinini, Enrico Bertolazzi, Francesco Biral

IEEE Access, 2023

2020

Real-time optimal control of an autonomous RC car with minimum-time maneuvers and a novel kineto-dynamical model.

Edoardo Pagot, Mattia Piccinini, Francesco Biral

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020