Learning high-speed flight in the wild A Loquercio, E Kaufmann, R Ranftl, M Müller, V Koltun, D Scaramuzza Science Robotics 6 (59), eabg5810, 2021 | 237 | 2021 |
Deep drone racing: From simulation to reality with domain randomization A Loquercio, E Kaufmann, R Ranftl, A Dosovitskiy, V Koltun, ... IEEE Transactions on Robotics 36 (1), 1-14, 2019 | 231 | 2019 |
Data-Driven MPC for Quadrotors G Torrente, E Kaufmann, P Föhn, D Scaramuzza IEEE Robotics and Automation Letters, 2021 | 207 | 2021 |
Rapid exploration with multi-rotors: A frontier selection method for high speed flight T Cieslewski, E Kaufmann, D Scaramuzza 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 206 | 2017 |
Champion-level drone racing using deep reinforcement learning E Kaufmann, L Bauersfeld, A Loquercio, M Müller, V Koltun, ... Nature 620 (7976), 982-987, 2023 | 193 | 2023 |
Flightmare: A Flexible Quadrotor Simulator Y Song, S Naji, E Kaufmann, A Loquercio, D Scaramuzza 2020 Conference on Robot Learning (CoRL), 2020 | 186 | 2020 |
Autonomous Drone Racing with Deep Reinforcement Learning Y Song, M Steinweg, E Kaufmann, D Scaramuzza 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021 | 176 | 2021 |
Deep drone racing: Learning agile flight in dynamic environments E Kaufmann, A Loquercio, R Ranftl, A Dosovitskiy, V Koltun, ... 2018 Conference on Robot Learning (CoRL), 2018 | 170 | 2018 |
Deep Drone Acrobatics E Kaufmann, A Loquercio, R Ranftl, M Müller, V Koltun, D Scaramuzza 2020 Robotics: Science and Systems (RSS), 2020 | 157 | 2020 |
AlphaPilot: Autonomous Drone Racing P Foehn, D Brescianini, E Kaufmann, T Cieslewski, M Gehrig, M Muglikar, ... 2020 Robotics: Science and Systems (RSS), 2020 | 156 | 2020 |
Beauty and the beast: Optimal methods meet learning for drone racing E Kaufmann, M Gehrig, P Foehn, R Ranftl, A Dosovitskiy, V Koltun, ... 2019 International Conference on Robotics and Automation (ICRA), 690-696, 2019 | 155 | 2019 |
Super-Human Performance in Gran Turismo Sport Using Deep Reinforcement Learning F Fuchs, Y Song, E Kaufmann, D Scaramuzza, P Duerr IEEE Robotics and Automation Letters, 2020 | 129 | 2020 |
A comparative study of nonlinear mpc and differential-flatness-based control for quadrotor agile flight S Sun, A Romero, P Foehn, E Kaufmann, D Scaramuzza IEEE Transactions on Robotics, 2021 | 121 | 2021 |
Performance, Precision, and Payloads: Adaptive Nonlinear MPC for Quadrotors D Hanover, P Foehn, S Sun, E Kaufmann, D Scaramuzza IEEE Robotics and Automation Letters, 2021 | 89 | 2021 |
Agilicious: Open-source and open-hardware agile quadrotor for vision-based flight P Foehn, E Kaufmann, A Romero, R Penicka, S Sun, L Bauersfeld, ... Science Robotics 7 (67), eabl6259, 2022 | 85 | 2022 |
NeuroBEM: Hybrid Aerodynamic Quadrotor Model L Bauersfeld, E Kaufmann, P Foehn, S Sun, D Scaramuzza 2021 Robotics: Science and Systems (RSS), 2021 | 76 | 2021 |
Autonomous Overtaking in Gran Turismo Sport Using Curriculum Reinforcement Learning Y Song, HC Lin, E Kaufmann, P Duerr, D Scaramuzza 2021 International Conference on Robotics and Automation (ICRA), 2021 | 70 | 2021 |
Real-Time Neural MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms T Salzmann, E Kaufmann, J Arrizabalaga, M Pavone, D Scaramuzza, ... IEEE Robotics and Automation Letters 8 (4), 2397-2404, 2023 | 60 | 2023 |
A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flight E Kaufmann, L Bauersfeld, D Scaramuzza 2022 International Conference on Robotics and Automation (ICRA), 2022 | 53 | 2022 |
Learning Minimum-Time Flight in Cluttered Environments R Penicka, Y Song, E Kaufmann, D Scaramuzza IEEE Robotics and Automation Letters 7 (3), 7209-7216, 2022 | 44 | 2022 |