| Learning agile and dynamic motor skills for legged robots J Hwangbo, J Lee, A Dosovitskiy, D Bellicoso, V Tsounis, V Koltun, ... Science Robotics 4 (26), eaau5872, 2019 | 1495 | 2019 |
| Learning quadrupedal locomotion over challenging terrain J Lee, J Hwangbo, L Wellhausen, V Koltun, M Hutter Science robotics 5 (47), eabc5986, 2020 | 1289 | 2020 |
| Robust visual inertial odometry using a direct EKF-based approach M Bloesch, S Omari, M Hutter, R Siegwart 2015 IEEE/RSJ international conference on intelligent robots and systems …, 2015 | 1131 | 2015 |
| Anymal-a highly mobile and dynamic quadrupedal robot M Hutter, C Gehring, D Jud, A Lauber, CD Bellicoso, V Tsounis, ... 2016 IEEE/RSJ international conference on intelligent robots and systems …, 2016 | 1053 | 2016 |
| Learning robust perceptive locomotion for quadrupedal robots in the wild T Miki, J Lee, J Hwangbo, L Wellhausen, V Koltun, M Hutter Science robotics 7 (62), eabk2822, 2022 | 775 | 2022 |
| Control of a quadrotor with reinforcement learning J Hwangbo, I Sa, R Siegwart, M Hutter IEEE Robotics and Automation Letters 2 (4), 2096-2103, 2017 | 709 | 2017 |
| Learning to walk in minutes using massively parallel deep reinforcement learning N Rudin, D Hoeller, P Reist, M Hutter Conference on Robot Learning, 91-100, 2022 | 601 | 2022 |
| Iterated extended Kalman filter based visual-inertial odometry using direct photometric feedback M Bloesch, M Burri, S Omari, M Hutter, R Siegwart The International Journal of Robotics Research 36 (10), 1053-1072, 2017 | 553 | 2017 |
| Gait and trajectory optimization for legged systems through phase-based end-effector parameterization AW Winkler, CD Bellicoso, M Hutter, J Buchli IEEE Robotics and Automation Letters 3 (3), 1560-1567, 2018 | 533 | 2018 |
| State estimation for legged robots-consistent fusion of leg kinematics and IMU M Bloesch, M Hutter, MA Hoepflinger, S Leutenegger, C Gehring, ... Robotics 17, 17-24, 2013 | 415 | 2013 |
| Kinect v2 for mobile robot navigation: Evaluation and modeling P Fankhauser, M Bloesch, D Rodriguez, R Kaestner, M Hutter, R Siegwart 2015 international conference on advanced robotics (ICAR), 388-394, 2015 | 389 | 2015 |
| StarlETH: A compliant quadrupedal robot for fast, efficient, and versatile locomotion M Hutter, C Gehring, M Bloesch, MA Hoepflinger, CD Remy, R Siegwart Adaptive mobile robotics, 483-490, 2012 | 389 | 2012 |
| Anymal-toward legged robots for harsh environments M Hutter, C Gehring, A Lauber, F Gunther, CD Bellicoso, V Tsounis, ... Advanced Robotics 31 (17), 918-931, 2017 | 379 | 2017 |
| On stochastic optimal control and reinforcement learning by approximate inference K Rawlik, M Toussaint, S Vijayakumar Proceedings of Robotics: Science and Systems VIII, 2012 | 377 | 2012 |
| The current state and future outlook of rescue robotics J Delmerico, S Mintchev, A Giusti, B Gromov, K Melo, T Horvat, C Cadena, ... Journal of Field Robotics 36 (7), 1171-1191, 2019 | 347 | 2019 |
| Whole-body nonlinear model predictive control through contacts for quadrupeds M Neunert, M Stäuble, M Giftthaler, CD Bellicoso, J Carius, C Gehring, ... IEEE Robotics and Automation Letters 3 (3), 1458-1465, 2018 | 327 | 2018 |
| Probabilistic terrain mapping for mobile robots with uncertain localization P Fankhauser, M Bloesch, M Hutter IEEE Robotics and Automation Letters 3 (4), 3019-3026, 2018 | 303 | 2018 |
| A universal grid map library: Implementation and use case for rough terrain navigation P Fankhauser, M Hutter Robot Operating System (ROS) The Complete Reference (Volume 1), 99-120, 2016 | 303 | 2016 |
| Per-contact iteration method for solving contact dynamics J Hwangbo, J Lee, M Hutter IEEE Robotics and Automation Letters 3 (2), 895-902, 2018 | 273 | 2018 |
| Deepgait: Planning and control of quadrupedal gaits using deep reinforcement learning V Tsounis, M Alge, J Lee, F Farshidian, M Hutter IEEE Robotics and Automation Letters 5 (2), 3699-3706, 2020 | 251 | 2020 |
Roland SiegwartProfessor of Robotics, ETH Zurich, SwitzerlandE-mailová adresa ověřena na: ethz.ch
