Piepser: A Smart Wrist-Worn Variometer To Maximize The Paragliders Flytime. - Tim Fischer 001; Michael Ganz; Nicolas Baumann; Michele Magno (SAS, 2019)

Piepser 2.0: A Self-Sustaining Smartwatch to Maximize the Paragliders Flytime. - Nicolas Baumann; Michael Ganz; Michele Magno (IEEE Trans. Instrum. Meas., 2020)

TC-Driver: Trajectory Conditioned Driving for Robust Autonomous Racing - A Reinforcement Learning Approach. - Edoardo Ghignone; Nicolas Baumann; Mike Boss; Michele Magno (CoRR, 2022)

Design and Performance Evaluation of an Ultralow-Power Smart IoT Device With Embedded TinyML for Asset Activity Monitoring. - Marco Giordano; Nicolas Baumann; Michele Crabolu; Raphael Fischer 002; Giovanni Bellusci; Michele Magno (IEEE Trans. Instrum. Meas., 2022)

Low-cost Smart Raven Deterrent System with Tiny Machine Learning for Smart Agriculture. - Seonyeong Heo; Nicolas Baumann; Carla Margelisch; Marco Giordano; Michele Magno (I2MTC, 2023)

Model- and Acceleration-based Pursuit Controller for High-Performance Autonomous Racing. - Jonathan Becker; Nadine Imholz; Luca Schwarzenbach; Edoardo Ghignone; Nicolas Baumann; Michele Magno (ICRA, 2023)

Enhancing Lightweight Neural Networks for Small Object Detection in IoT Applications. - Liam Boyle; Nicolas Baumann; Seonyeong Heo; Michele Magno (SENSORS, 2023)

Towards Robust Velocity and Position Estimation of Opponents for Autonomous Racing Using Low-Power Radar. - Andrea Ronco; Nicolas Baumann; Marco Giordano; Michele Magno (IWASI, 2023)

A Robust and Real-Time Hyper-Spectral Sensor-Fusion Model for Concrete Crack Segmentation. - Matthias Steiner; Nicolas Baumann; Luzian Lebovitz; Michele Magno (SAS, 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 (WF-IoT, 2023)

TC-Driver: A Trajectory Conditioned Reinforcement Learning Approach to Zero-Shot Autonomous Racing. - Edoardo Ghignone; Nicolas Baumann; Michele Magno (Field Robotics, 2023)

Robustness Evaluation of Localization Techniques for Autonomous Racing. - Tian Yi Lim; Edoardo Ghignone; Nicolas Baumann; Michele Magno (DATE, 2024)

CR3DT: Camera-RADAR Fusion for 3D Detection and Tracking. - Nicolas Baumann; Michael Baumgartner; Edoardo Ghignone; Jonas Kühne; Tobias Fischer 004; Yung-Hsu Yang; Marc Pollefeys; Michele Magno (IROS, 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 002; et al. (CoRR, 2024)

DSORT-MCU: Detecting Small Objects in Real-Time on Microcontroller Units. - Liam Boyle; Julian Moosmann; Nicolas Baumann; Seonyeong Heo; Michele Magno (CoRR, 2024)

RLPP: A Residual Method for Zero-Shot Real-World Autonomous Racing on Scaled Platforms. - Edoardo Ghignone; Nicolas Baumann; Cheng Hu; Jonathan Wang; Lei Xie 007; Andrea Carron; Michele Magno (CoRR, 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 007; Michele Magno (IEEE Robotics Autom. Lett., 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 007; Andrea Carron; Michele Magno; Matteo Corno (IEEE Robotics Autom. Lett., 2025)

FSDP: Fast and Safe Data-Driven Overtaking Trajectory Planning for Head-to-Head Autonomous Racing Competitions. - Cheng Hu; Jihao Huang; Wule Mao; Yonghao Fu; Xuemin Chi; Haotong Qin; Nicolas Baumann; Zhitao Liu; Michele Magno; Lei Xie 007 (CoRR, 2025)

GP-enhanced Autonomous Drifting Framework using ADMM-based iLQR. - Yangyang Xie; Cheng Hu; Nicolas Baumann; Edoardo Ghignone; Michele Magno; Lei Xie 007 (CoRR, 2025)

TinyCenterSpeed: Efficient Center-Based Object Detection for Autonomous Racing. - Neil Reichlin; Nicolas Baumann; Edoardo Ghignone; Michele Magno (CoRR, 2025)

Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models. - Nicolas Baumann; Cheng Hu; Paviththiren Sivasothilingam; Haotong Qin; Lei Xie 007; Michele Magno; Luca Benini (CoRR, 2025)

RobotxR1: Enabling Embodied Robotic Intelligence on Large Language Models through Closed-Loop Reinforcement Learning. - Liam Boyle; Nicolas Baumann; Paviththiren Sivasothilingam; Michele Magno; Luca Benini (CoRR, 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, 2025)

DTR: Delaunay Triangulation-based Racing for Scaled Autonomous Racing. - Luca Tognoni; Neil Reichlin; Edoardo Ghignone; Nicolas Baumann; Steven Marty; Liam Boyle; Michele Magno (CoRR, 2025)

R-CARLA: High-Fidelity Sensor Simulations with Interchangeable Dynamics for Autonomous Racing. - Maurice Brunner; Edoardo Ghignone; Nicolas Baumann; Michele Magno (CoRR, 2025)

M-Predictive Spliner: Enabling Spatiotemporal Multi-Opponent Overtaking for Autonomous Racing. - Nadine Imholz; Maurice Brunner; Nicolas Baumann; Edoardo Ghignone; Michele Magno (CoRR, 2025)

Planar Velocity Estimation for Fast-Moving Mobile Robots Using Event-Based Optical Flow. - Liam Boyle; Jonas Kühne; Nicolas Baumann; Niklas Bastuck; Michele Magno (IEEE Robotics Autom. Lett., 2025)