Edoardo Ghignone

According to our database, Edoardo Ghignone authored at least 17 papers between 2022 and 2025.

Collaborative distances:

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

2025

Residual Koopman Model Predictive Control for Enhanced Vehicle Dynamics with Small On-Track Data Input.

Yonghao Fu, Cheng Hu, Haokun Xiong, Zhangpeng Bao, Wenyuan Du, Edoardo Ghignone, Michele Magno, Lei Xie, Hongye Su

CoRR, July, 2025

M-Predictive Spliner: Enabling Spatiotemporal Multi-Opponent Overtaking for Autonomous Racing.

Nadine Imholz, Maurice Brunner, Nicolas Baumann, Edoardo Ghignone, Michele Magno

CoRR, June, 2025

R-CARLA: High-Fidelity Sensor Simulations with Interchangeable Dynamics for Autonomous Racing.

Maurice Brunner, Edoardo Ghignone, Nicolas Baumann, Michele Magno

CoRR, June, 2025

Drive Fast, Learn Faster: On-Board RL for High Performance Autonomous Racing.

Benedict Hildisch, Edoardo Ghignone, Nicolas Baumann, Cheng Hu, Andrea Carron, Michele Magno

CoRR, May, 2025

TinyCenterSpeed: Efficient Center-Based Object Detection for Autonomous Racing.

Neil Reichlin, Nicolas Baumann, Edoardo Ghignone, Michele Magno

CoRR, April, 2025

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

Onur Dikici, Edoardo Ghignone, Cheng Hu, Nicolas Baumann, Lei Xie, Andrea Carron, Michele Magno, Matteo Corno

IEEE Robotics Autom. Lett., February, 2025

Predictive Spliner: Data-Driven Overtaking in Autonomous Racing Using Opponent Trajectory Prediction.

Nicolas Baumann, Edoardo Ghignone, Cheng Hu, Benedict Hildisch, Tino Hämmerle, Alessandro Bettoni, Andrea Carron, Lei Xie, Michele Magno

IEEE Robotics Autom. Lett., February, 2025

RLPP: A Residual Method for Zero-Shot Real-World Autonomous Racing on Scaled Platforms.

Edoardo Ghignone, Nicolas Baumann, Cheng Hu, Jonathan Wang, Lei Xie, Andrea Carron, Michele Magno

CoRR, January, 2025

DTR: Delaunay Triangulation-based Racing for Scaled Autonomous Racing.

Luca Tognoni, Neil Reichlin, Edoardo Ghignone, Nicolas Baumann, Steven Marty, Liam Boyle, Michele Magno

Proceedings of the 10th International Workshop on Advances in Sensors and Interfaces, 2025

GP-enhanced Autonomous Drifting Framework using ADMM-based iLQR.

Yangyang Xie, Cheng Hu, Nicolas Baumann, Edoardo Ghignone, Michele Magno, Lei Xie

Proceedings of the 2025 American Control Conference, 2025

2024

ForzaETH Race Stack - Scaled Autonomous Head-to-Head Racing on Fully Commercial off-the-Shelf Hardware.

Nicolas Baumann, Edoardo Ghignone, Jonas Kühne, Niklas Bastuck, Jonathan Becker, Nadine Imholz, Tobias Kränzlin, Tian Yi Lim, Michael Lötscher, Luca Schwarzenbach, Luca Tognoni, Christian Vogt, Andrea Carron, Michele Magno

CoRR, 2024

CR3DT: Camera-RADAR Fusion for 3D Detection and Tracking.

Nicolas Baumann, Michael Baumgartner, Edoardo Ghignone, Jonas Kühne, Tobias Fischer, Yung-Hsu Yang, Marc Pollefeys, Michele Magno

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

Robustness Evaluation of Localization Techniques for Autonomous Racing.

Tian Yi Lim, Edoardo Ghignone, Nicolas Baumann, Michele Magno

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

2023

TC-Driver: A Trajectory Conditioned Reinforcement Learning Approach to Zero-Shot Autonomous Racing.

Edoardo Ghignone, Nicolas Baumann, Michele Magno

Field Robotics, January, 2023

Assessing the Robustness of LiDAR, Radar and Depth Cameras Against Ill-Reflecting Surfaces in Autonomous Vehicles: An Experimental Study.

Michael Lötscher, Nicolas Baumann, Edoardo Ghignone, Andrea Ronco, Michele Magno

Proceedings of the 9th IEEE World Forum on Internet of Things, 2023

Model- and Acceleration-based Pursuit Controller for High-Performance Autonomous Racing.

Jonathan Becker, Nadine Imholz, Luca Schwarzenbach, Edoardo Ghignone, Nicolas Baumann, Michele Magno

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

TC-Driver: Trajectory Conditioned Driving for Robust Autonomous Racing - A Reinforcement Learning Approach.

Edoardo Ghignone, Nicolas Baumann, Mike Boss, Michele Magno

CoRR, 2022