Marco Hutter
Marco Hutter
Professor of Robotics, ETH Zurich
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
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
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
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
Learning quadrupedal locomotion over challenging terrain
J Lee, J Hwangbo, L Wellhausen, V Koltun, M Hutter
Science robotics 5 (47), eabc5986, 2020
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
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
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
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
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
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
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
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
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
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
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
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
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
Control of dynamic gaits for a quadrupedal robot
C Gehring, S Coros, M Hutter, M Bloesch, MA Hoepflinger, R Siegwart
2013 IEEE international conference on Robotics and automation, 3287-3292, 2013
Per-contact iteration method for solving contact dynamics
J Hwangbo, J Lee, M Hutter
IEEE Robotics and Automation Letters 3 (2), 895-902, 2018
Robot-centric elevation mapping with uncertainty estimates
P Fankhauser, M Bloesch, C Gehring, M Hutter, R Siegwart
Mobile Service Robotics, 433-440, 2014
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