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ANYmal - a highly mobile and dynamic quadrupedal robot
Open accessAbstract
This paper introduces ANYmal, a quadrupedal robot that features outstanding mobility and dynamic motion capability. Thanks to novel, compliant joint modules with integrated electronics, the 30 kg, 0.5 m tall robotic dog is torque controllable and very robust against impulsive loads during running or jumping. The presented machine was designed with a focus on outdoor suitability, simple maintenance, and user-friendly handling to enable future operation in real world scenarios. Performance tests with the joint actuators indicated a torque control bandwidth of more than 70 Hz, high disturbance rejection capability, as well as impact robustness when moving with maximal velocity. It is demonstrated in a series of experiments that ANYmal can execute walking gaits, dynamically trot at moderate speed, and is able to perform special maneuvers to stand up or crawl very steep stairs. Detailed measurements unveil that even full-speed running requires less than 280 W, resulting in an autonomy of more than 2 h.
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“The controller was used to drive two generations of ANYmal quadrupeds [20] in a variety of conditions that are beyond the reach of prior published work in legged robotics.”
From Learning quadrupedal locomotion over challenging terrain (2020) · cites this paper as [20]
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Cites
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Design of HyQ – a hydraulically and electrically actuated quadruped robot
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Design principles for highly efficient quadrupeds and implementation on the MIT Cheetah robot
Seok, S., Wang, A. Z., Chuah, M. Y., Otten, D. M., Lang, J. H., & Kim, S. (2013) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2013.6631038 · Cited by 457
Design and Control Considerations for High-Performance Series Elastic Actuators
Paine, N., Oh, S., & Sentis, L. (2013) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2013.2270435 · Cited by 411
Valkyrie: NASA's First Bipedal Humanoid Robot
Radford, N. A., Strawser, P., Hambuchen, K., Mehling, J. S., Verdeyen, W. K., Donnan, A. S., Holley, J., Sanchez, J., Nguyen, V., Bridgwater, L., et al. (2015) · Journal of Field Robotics · doi:10.1002/rob.21560 · Cited by 300
State Estimation for Legged Robots: Consistent Fusion of Leg Kinematics and IMU
Bloesch, M., Hutter, M., Hoepflinger, M. A., Leutenegger, S., Gehring, C., Remy, C. D., & Siegwart, R. (2013) · The MIT Press eBooks · doi:10.7551/mitpress/9816.003.0008 · Cited by 277
Self-citationPaine, N., Mehling, J. S., Holley, J., Radford, N. A., Johnson, G., Fok, C., & Sentis, L. (2015) · Journal of Field Robotics · doi:10.1002/rob.21556 · Cited by 263
STARLETH: A COMPLIANT QUADRUPEDAL ROBOT FOR FAST, EFFICIENT, AND VERSATILE LOCOMOTION
Hutter, M., Gehring, C., Bloesch, M., Hoepflinger, M. A., Remy, C. D., & Siegwart, R. (2012) · WORLD SCIENTIFIC eBooks · doi:10.1142/9789814415958_0062 · Cited by 245
Self-citation
Research works printed but not linked: 2
- boaventura, 2013, Hydraulic Compliance Control of the Quadruped Robot HyQ
- 0, ATLAS Robot, Boston Dynamics
Cited by
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Learning agile and dynamic motor skills for legged robots
Hwangbo, J., Lee, J., Dosovitskiy, A., Bellicoso, D., Tsounis, V., Koltun, V., & Hutter, M. (2019) · Science Robotics · doi:10.1126/scirobotics.aau5872 · Cited by 1,482
“Most legged systems are driven by hydraulic actuators [51] or electric motors with gears [3], and some even include dedicated mechanical compliance [5, 52].”
BackgroundMethodInfluentialSelf-citationLearning quadrupedal locomotion over challenging terrain
Lee, J., Hwangbo, J., Wellhausen, L., Koltun, V., & Hutter, M. (2020) · Science Robotics · doi:10.1126/scirobotics.abc5986 · Cited by 1,156
“The controller was used to drive two generations of ANYmal quadrupeds [20] in a variety of conditions that are beyond the reach of prior published work in legged robotics.”
MethodSelf-citationLearning quadrupedal locomotion over challenging terrain
Lee, J., Hwangbo, J., Wellhausen, L., Koltun, V., & Hutter, M. (2020) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-b-000448343 · Cited by 752
Self-citationMIT Cheetah 3: Design and Control of a Robust, Dynamic Quadruped Robot
Bledt, G., Powell, M. J., Katz, B., Carlo, J. D., Wensing, P. M., & Kim, S. (2018) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2018.8593885 · Cited by 739
“By comparison, the series elastic actuators used in ANYmal, which measure the deflection of a series spring to control output torque, have far greater torque accuracy, but much lower peak torque, speed, and torque bandwidth, especially at high torques [2].”
BackgroundInfluentialMini Cheetah: A Platform for Pushing the Limits of Dynamic Quadruped Control
Katz, B., Carlo, J. D., & Kim, S. (2019) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2019.8793865 · Cited by 559
“A similar approach was used in the quadruped ANYmal, with the series-elastic ANYdrive actuator [6].”
BackgroundMethodWinkler, A. W., Bellicoso, C. D., Hutter, M., & Buchli, J. (2018) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2018.2798285 · Cited by 451
“Secondly, we demonstrate a subset of motions in the realistic physics simulator Gazebo as well as on the quadruped robot ANYmal [34].”
BackgroundMethodSelf-citationLearning to Walk Via Deep Reinforcement Learning
Haarnoja, T., Ha, S., Zhou, A., Tan, J., Tucker, G., & Levine, S. (2019) · Robotics: Science and Systems XV · doi:10.15607/rss.2019.xv.011 · Cited by 430
Multi-environment robotic transitions through adaptive morphogenesis
Baines, R. L., Patiballa, S. K., Booth, J., Ramirez, L., Sipple, T., Garcia, A., Fish, F. E., & Kramer-Bottiglio, R. K. (2022) · Nature · doi:10.1038/s41586-022-05188-w · Cited by 346
Whole-Body Nonlinear Model Predictive Control Through Contacts for Quadrupeds
Neunert, M., Stäuble, M., Giftthaler, M., Bellicoso, C. D., Carius, J., Gehring, C., Hutter, M., & Buchli, J. (2018) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2018.2800124 · Cited by 289
“We show that the approach transfers between platforms, and apply the same framework to the two quadrupeds HyQ and ANYmal (Figure 1).”
MethodInfluentialSelf-citationPerceptive Locomotion Through Nonlinear Model-Predictive Control
Grandia, R., Jenelten, F., Yang, S., Farshidian, F., & Hutter, M. (2023) · IEEE Transactions on Robotics · doi:10.1109/tro.2023.3275384 · Cited by 281
“The resulting method is evaluated on the quadrupedal robot ANYmal [25] (see Fig.1)inSectionVII.”
MethodSelf-citationGraph‐based subterranean exploration path planning using aerial and legged robots
Dang, T., Tranzatto, M., Khattak, S., Mascarich, F., Alexis, K., & Hutter, M. (2020) · Journal of Field Robotics · doi:10.1002/rob.21993 · Cited by 253
“, 2020b) were utilized, alongside the ANYmal quadrupedal legged platform (Hutter et al., 2016).”
MethodSelf-citationData-Driven Model Predictive Control for Trajectory Tracking With a Robotic Arm
Carron, A., Arcari, E., Wermelinger, M., Hewing, L., Hutter, M., & Zeilinger, M. N. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2929987 · Cited by 245
“These actuators, called ANYdrives [44], are composed of a brushless motor, harmonic drive gear, a torsional spring, and integrated control electronics and sensors.”
BackgroundSelf-citationPer-Contact Iteration Method for Solving Contact Dynamics
Hwangbo, J., Lee, J., & Hutter, M. (2018) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2018.2792536 · Cited by 243
“We test the following four scenarios: • Trotting: The model of ANYmal runs forward at 1.5 m/s with its legs moving in diagonal pairs.”
MethodInfluentialSelf-citationDeepGait: Planning and Control of Quadrupedal Gaits Using Deep Reinforcement Learning
Tsounis, V., Alge, M., Lee, J., Farshidian, F., & Hutter, M. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.2979660 · Cited by 238
“This work was supported in part by Intel Labs, in part by the Swiss National Science Foundation (SNSF) through Projects 166232 and 188596, in part by the National Centre of Competence in Research Robotics (NCCR Robotics), in part by the European Union’s Horizon 2020 research and innovation program under Grant Agreemen…”
BackgroundInfluentialSelf-citationAn Open Torque-Controlled Modular Robot Architecture for Legged Locomotion Research
Grimminger, F., Meduri, A., Khadiv, M., Viereck, J., Wuthrich, M., Naveau, M., Berenz, V., Heim, S. W., Widmaier, F., Flayols, T., et al. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.2976639 · Cited by 221
“Complex machining is typical in quadruped robots exhibiting high performance force control such as HyQ [27], Anymal [12] or the MIT Cheetah [33].”
BackgroundKeep Rollin’—Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots
Bjelonic, M., Bellicoso, C. D., de Viragh, Y., Sako, D., Tresoldi, F. D., Jenelten, F., & Hutter, M. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2899750 · Cited by 248
“In addition, with 4 m/s we broke ANYmal’s maximum speed record of 1.5 m/s given in [38].”
BackgroundMethodInfluentialSelf-citationAdvances in real‐world applications for legged robots
Bellicoso, C. D., Bjelonic, M., Wellhausen, L., Holtmann, K., Günther, F., Tranzatto, M., Fankhauser, P., & Hutter, M. (2018) · Journal of Field Robotics · doi:10.1002/rob.21839 · Cited by 223
“This enables the generation of motion plans which keep the torso of the robot always parallel to the local estimation of the terrain, that is, this approach allows to blindly and robustly (Gehring et al., 2016) overcome challenging environments, for example, sloped terrain.”
BackgroundMethodSelf-citationRobust Rough-Terrain Locomotion with a Quadrupedal Robot
Fankhauser, P., Bjelonic, M., Bellicoso, C. D., Miki, T., & Hutter, M. (2018) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2018.8460731 · Cited by 210
Self-citationDynamic Locomotion Through Online Nonlinear Motion Optimization for Quadrupedal Robots
Bellicoso, C. D., Jenelten, F., Gehring, C., & Hutter, M. (2018) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2018.2794620 · Cited by 206
“Over the past few years, ANYmal [8] (see Fig.”
BackgroundMethodSelf-citationJi, G., Mun, J., Kim, H., & Hwangbo, J. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3151396 · Cited by 229
“[1] trained control policies for the ANYmal robot [2] for robust and high-speed locomotion while keeping the balance under large disturbances.”
BackgroundSelf-citationMulti-expert learning of adaptive legged locomotion
Yang, C., Yuan, K., Zhu, Q., Yu, W., & Li, Z. (2020) · Science Robotics · doi:10.1126/scirobotics.abb2174 · Cited by 227
Where Should I Walk? Predicting Terrain Properties From Images Via Self-Supervised Learning
Wellhausen, L., Dosovitskiy, A., Ranftl, R., Walas, K., Cadena, C., & Hutter, M. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2895390 · Cited by 195
“We deploy and test the proposed system on the ANYmal quadruped [6].”
MethodSelf-citationRepresentation-Free Model Predictive Control for Dynamic Motions in Quadrupeds
Ding, Y., Pandala, A., Li, C., Shin, Y.-H., & Park, H.-W. (2021) · IEEE Transactions on Robotics · doi:10.1109/tro.2020.3046415 · Cited by 205
VILENS: Visual, Inertial, Lidar, and Leg Odometry for All-Terrain Legged Robots
Wisth, D., Camurri, M., & Fallon, M. F. (2022) · IEEE Transactions on Robotics · doi:10.1109/tro.2022.3193788 · Cited by 183
“2 shows this effect on the ANYmal B300 robot traveling over various terrains.”
MethodInfluentialCENTAURO: A Hybrid Locomotion and High Power Resilient Manipulation Platform
Kashiri, N., Cordasco, S., Guria, P., Margan, A., Tsagarakis, N. G., Baccelliere, L., Muratore, L., Laurenzi, A., Ren, Z., Hoffman, E. M., et al. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2896758 · Cited by 179
“Despite the development of a number of hexapods, the major developments in multi-legged robots was focused on quadrupeds, including BigDog [10], LittleDog [11], MIT Cheetah [12], TITAN [13], HyQ [14], Cheetah-cub [15] and Anymal [16].”
BackgroundExtreme Parkour with Legged Robots
Cheng, X., Shi, K., Agarwal, A., & Pathak, D. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10610200 · Cited by 183
“…design principle for general robot base motion acquisition, together with an automatic terrain curriculum for overcoming exploration burden in RL. • Our results set a new landmark in learning-driven park-our with high jumps that are 2x the height of the robot, long jumps that are 2x the…”
Nahrendra, I. M. A., Yu, B., & Myung, H. (2023) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48891.2023.10161144 · Cited by 203
“In recent years, quadrupedal robots have played an important role in various applications, such as industrial inspection and exploration [1]–[6].”
BackgroundPerception-less terrain adaptation through whole body control and hierarchical optimization
Bellicoso, C. D., Gehring, C., Hwangbo, J., Fankhauser, P., & Hutter, M. (2016) · IEEE-RAS International Conference on Humanoid Robots (Humanoids) · doi:10.1109/humanoids.2016.7803330 · Cited by 169
“Our experiments 1 were conducted on ANYmal [9], an accurately torque-controllable quadrupedal robot.”
MethodSelf-citationKeep Rollin’ - Whole-Body Motion Control and Planning for Wheeled Quadrupedal Robots
Bjelonic, M., Bellicoso, C. D., de Viragh, Y., Sako, D., Tresoldi, F., Jenelten, F., & Hutter, M. (2019) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-b-000323519 · Cited by 165
Self-citationDynamic locomotion and whole-body control for quadrupedal robots
Bellicoso, C. D., Jenelten, F., Fankhauser, P., Gehring, C., Hwangbo, J., & Hutter, M. (2017) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2017.8206174 · Cited by 162
“Recent results have shown ANYmal [9] walking [1], trotting [5], and climbing over stairs [3] by employing whole-body control and motion optimization algorithms.”
BackgroundMethodInfluentialSelf-citationStanford Doggo: An Open-Source, Quasi-Direct-Drive Quadruped
Kau, N., Schultz, A., Ferrante, N., & Slade, P. (2019) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2019.8794436 · Cited by 157
“Many state-of-theart legged robots have achieved remarkable feats including high speed locomotion [1], [2], agile maneuvers [3], [4], [5], and traversing difficult terrain [6], [7], [8], [9].”
BackgroundUnified Multi-Modal Landmark Tracking for Tightly Coupled Lidar-Visual-Inertial Odometry
Wisth, D., Camurri, M., Das, S., & Fallon, M. F. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3056380 · Cited by 146
“…consists of two of the most significant runs of the SubT competition (Alpha-2 and Beta-2) collected on two copies of the ANYmal B300 quadruped robot [28] equipped with a Flir BFS-U3-16S2C-CS monocular camera and a industrial-grade Xsens MTi-100 IMU, which were hardware synchronized by a dedicated…”
RLOC: Terrain-Aware Legged Locomotion Using Reinforcement Learning and Optimal Control
Gangapurwala, S., Geisert, M., Orsolino, R., Fallon, M. F., & Havoutis, I. (2022) · IEEE Transactions on Robotics · doi:10.1109/tro.2022.3172469 · Cited by 164
“In this work, we design, train, and evaluate a control framework for legged locomotion over uneven terrain using the ANYbotics ANYmal B [1] and ANYmal C [2] quadrupedal robots.”
MethodOptimized Jumping on the MIT Cheetah 3 Robot
Nguyen, Q., Powell, M. J., Katz, B., Carlo, J. D., & Kim, S. (2019) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2019.8794449 · Cited by 138
“ANYmal at ETH [2] features an extensive range of motion for completing autonomous tasks in real-world situations with the use of Series Elastic Actuators (SEAs).”
BackgroundLearning robust autonomous navigation and locomotion for wheeled-legged robots
Lee, J., Bjelonic, M., Reske, A., Wellhausen, L., Miki, T., & Hutter, M. (2024) · Science Robotics · doi:10.1126/scirobotics.adi9641 · Cited by 163
“For instance, the ANYmal robot [1] can only operate for a maximum of 1hour[2, 3] at half the speed of an average human walking (2.2km/h on average [4]).”
BackgroundSelf-citationVision-controlled jetting for composite systems and robots
Buchner, T. J. K., Rogler, S., Weirich, S., Armati, Y., Cangan, B. G., Ramos, J., Twiddy, S. T., Marini, D. M., Weber, A., Chen, D., et al. (2023) · Nature · doi:10.1038/s41586-023-06684-3 · Cited by 151
“2 and Supplementary Video 3), every created cavity must have a connection to the outside of the printed part for drainage.”
InfluentialMulti-Layered Safety for Legged Robots via Control Barrier Functions and Model Predictive Control
Grandia, R., Taylor, A. J., Ames, A. D., & Hutter, M. (2021) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48506.2021.9561510 · Cited by 135
“@ethz.ch. A. Taylor and A. Ames are with the Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA 91125, USA {ajtaylor,ames}@caltech.edu. Fig. 1. ANYmal [6] performing a trotting gait on stepping-stones. and sparsely available. We propose to combine the safety guarantees…”
BackgroundSelf-citationALMA - Articulated Locomotion and Manipulation for a Torque-Controllable Robot
Bellicoso, C. D., Krämer, K., Stäuble, M., Sako, D., Jenelten, F., Bjelonic, M., & Hutter, M. (2019) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2019.8794273 · Cited by 133
“This work has been conducted as part of ANYmal Research, a community to advance legged robotics.”
MethodInfluentialSelf-citationANYexo: A Versatile and Dynamic Upper-Limb Rehabilitation Robot
Zimmermann, Y., Forino, A., Riener, R., & Hutter, M. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2926958 · Cited by 128
“[23], [24], covers the minimum requirements on torque for all joints while not exceeding the target for strength assessment.”
BackgroundSelf-citationElevation Mapping for Locomotion and Navigation using GPU
Miki, T., Wellhausen, L., Grandia, R., Jenelten, F., Homberger, T., & Hutter, M. (2022) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros47612.2022.9981507 · Cited by 126
“We validate the usability of our mapping framework through legged locomotion and navigation experiments using the ANYmal platform [32].”
BackgroundMethodInfluentialSelf-citationAgile and versatile climbing on ferromagnetic surfaces with a quadrupedal robot
Hong, S., Um, Y., Park, J.-J., & Park, H.-W. (2022) · Science Robotics · doi:10.1126/scirobotics.add1017 · Cited by 124
Go Fetch! - Dynamic Grasps using Boston Dynamics Spot with External Robotic Arm
Zimmermann, S., Poranne, R., & Coros, S. (2021) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48506.2021.9561835 · Cited by 123
“Beside that, the academic community has invested vast amounts of resources into developing mobile platforms such as quadrupeds [1], [2], [3].”
BackgroundControl strategy of stable walking for a hexapod wheel-legged robot
Chen, Z., Wang, S., Wang, J., Xu, K., Lei, T., Zhang, H., Wang, X., Liu, D., & Si, J. (2020) · ISA Transactions · doi:10.1016/j.isatra.2020.08.033 · Cited by 120
Jenelten, F., He, J., Farshidian, F., & Hutter, M. (2024) · Science Robotics · doi:10.1126/scirobotics.adh5401 · Cited by 142
Self-citationPerceptive Locomotion in Rough Terrain – Online Foothold Optimization
Jenelten, F., Miki, T., Vijayan, A. E., Bjelonic, M., & Hutter, M. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.3007427 · Cited by 115
“We have tested the perceptive locomotion pipeline on ANYmal [16], a fully torque controllable quadruped robot, designed for harsh in-and outdoor environments.”
MethodSelf-citationA Review of Quadruped Robots: Structure, Control, and Autonomous Motion
Fan, Y., Pei, Z., Wang, C., Li, M., Tang, Z., & Liu, Q. (2024) · Advanced Intelligent Systems · doi:10.1002/aisy.202300783 · Cited by 115
Mechanism, Actuation, Perception, and Control of Highly Dynamic Multilegged Robots: A Review
He, J., & Gao, F. (2020) · Chinese Journal of Mechanical Engineering · doi:10.1186/s10033-020-00485-9 · Cited by 122
“Recently, StarlETH [20, 102–104] and ANYmal [10, 87], two fully torque-controllable quadruped robots, achieved impressive loco-motion performance using the WBC method.”
BackgroundMethodInfluentialTrajectory Optimization for Wheeled-Legged Quadrupedal Robots Driving in Challenging Terrain
Medeiros, V. S., Jelavić, E., Bjelonic, M., Siegwart, R., Meggiolaro, M. A., & Hutter, M. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.2990720 · Cited by 113
“Furthermore, we evaluated the proposed approach on ANYmal equipped with actuated non-steerable wheels in both simulations and real-world experiments.”
BackgroundInfluentialSelf-citationTranzatto, M., Mascarich, F., Bernreiter, L., Godinho, C., Camurri, M., Khattak, S., Dang, T., Reijgwart, V., Loeje, J., Wisth, D., et al. (2022) · Field Robotics · doi:10.55417/fr.2022011 · Cited by 118
Self-citationBirdBot achieves energy-efficient gait with minimal control using avian-inspired leg clutching
Badri–Spröwitz, A., Sarvestani, A. A., Sitti, M., & Daley, M. A. (2022) · Science Robotics · doi:10.1126/scirobotics.abg4055 · Cited by 116
Learning to Walk in the Real World with Minimal Human EffortPreprint
Ha, S., Xu, P., Tan, Z., Levine, S., & Tan, J. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2002.08550 · Cited by 165
Pronto: A Multi-Sensor State Estimator for Legged Robots in Real-World Scenarios
Camurri, M., Ramezani, M., Nobili, S., & Fallon, M. F. (2020) · Frontiers in Robotics and AI · doi:10.3389/frobt.2020.00068 · Cited by 106
“ANYmal (version B, Figure 1D ) is a 12-DoF electrically actuated quadruped robot initially designed by Hutter et al. (2016) at ETH Zurich and now manufactured by ANYbotics.”
MethodBiConMP: A Nonlinear Model Predictive Control Framework for Whole Body Motion Planning
Meduri, A., Shah, P., Viereck, J., Khadiv, M., Havoutis, I., & Righetti, L. (2023) · IEEE Transactions on Robotics · doi:10.1109/tro.2022.3228390 · Cited by 107
“The solve times of AnYmal trot are slightly higher as compared to Solo12 since we use more collocation points in the trajectory.”
BackgroundInfluentialFlexible Motion Framework of the Six Wheel-Legged Robot: Experimental Results
Wang, S., Chen, Z., Li, J., Wang, J., Li, J., & Zhao, J. (2021) · IEEE/ASME Transactions on Mechatronics · doi:10.1109/tmech.2021.3100879 · Cited by 98
Legged Robots that Keep on Learning: Fine-Tuning Locomotion Policies in the Real World
Smith, L., Kew, J. C., Peng, X. B., Ha, S., Tan, J., & Levine, S. (2022) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra46639.2022.9812166 · Cited by 118
TAMOLS: Terrain-Aware Motion Optimization for Legged Systems
Jenelten, F., Grandia, R., Farshidian, F., & Hutter, M. (2022) · IEEE Transactions on Robotics · doi:10.1109/tro.2022.3186804 · Cited by 95
“Most recently, this approach was shown in combination with online mapping, enabling ANYmal to walk over 20 cm high steps [28].”
MethodInfluentialSelf-citationLearning a State Representation and Navigation in Cluttered and Dynamic Environments
Hoeller, D., Wellhausen, L., Farshidian, F., & Hutter, M. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3068639 · Cited by 96
“We deploy the policy to the quadrupedal robot ANYmal [14] sim-to-real and show that it can navigate in a cluttered scene and avoid people moving across its path in a very reactive manner.”
MethodInfluentialSelf-citationModel predictive control of legged and humanoid robots: models and algorithms
Katayama, S., Murooka, M., & Tazaki, Y. (2023) · Advanced Robotics · doi:10.1080/01691864.2023.2168134 · Cited by 91
“Recently, more advanced robots, such as HyQ [2], ANYmal [3], MIT Cheetah [4], and Mini Cheetah [5], have been developed by different research institutes.”
BackgroundA Family of Iterative Gauss-Newton Shooting Methods for Nonlinear Optimal Control
Giftthaler, M., Neunert, M., Stäuble, M., Buchli, J., & Diehl, M. (2018) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2018.8593840 · Cited by 89
Robust Legged Robot State Estimation Using Factor Graph Optimization
Wisth, D., Camurri, M., & Fallon, M. F. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2933768 · Cited by 87
“Experiments were conducted using an ANYbotics ANYmal quadruped [5] in outdoor environments, including the Oil Rig training facility shown above.”
Safe Robot Navigation Via Multi-Modal Anomaly Detection
Wellhausen, L., Ranftl, R., & Hutter, M. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.2967706 · Cited by 86
“The quadrupedal robot ANYmal is teleoperated over various terrain while we record the image streams of an onboard camera, as well as the foothold contact locations in a robot-centered frame.”
MethodInfluentialSelf-citationMa, Y., Farshidian, F., Miki, T., Lee, J., & Hutter, M. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3143567 · Cited by 94
“In this work, we deployed our controller on ALMA platform [5], which consists of the Dynaarm manipulator mounted on ANYmal base [17] and we use Raisim physics engine [18] to simulate the robot during locomotion training.”
MethodSelf-citationDynamic Locomotion on Slippery Ground
Jenelten, F., Hwangbo, J., Tresoldi, F., Bellicoso, C. D., & Hutter, M. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2931284 · Cited by 84
“To verify our approach, we have conducted several experiments on ANYmal [19], a fully torque-controllable quadrupedal robot.”
MethodInfluentialSelf-citationRoBoa: Construction and Evaluation of a Steerable Vine Robot for Search and Rescue Applications
der Maur, P. A., Djambazi, B., Haberthur, Y., Hormann, P., Kübler, A. M., Lustenberger, M., Sigrist, S., Vigen, O., Förster, J., Achermann, F., et al. (2021) · IEEE International Conference on Soft Robotics (RoboSoft) · doi:10.1109/robosoft51838.2021.9479192 · Cited by 85
“The same issue occurs with wheel-based [7], or legged robots [8], [9].”
Design of Dynamic Legged Robots
Kim, S., & Wensing, P. M. (2017) · Foundations and Trends in Robotics · doi:10.1561/2300000044 · Cited by 81
“Marco Hutter, one of the original designers of StarlETH, recently introduced a more modular version of StarlETH, ANYmal (Hutter et al., 2016), which is able to climb steep stairs (50◦ inclination) and trot dynamically at 0.”
BackgroundJumping over obstacles with MIT Cheetah 2
Park, H.-W., Wensing, P. M., & Kim, S. (2020) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2020.103703 · Cited by 83
A study on quadruped mobile robots
Taheri, H., & Mozayani, N. (2023) · Mechanism and Machine Theory · doi:10.1016/j.mechmachtheory.2023.105448 · Cited by 82
Weaver: Hexapod robot for autonomous navigation on unstructured terrain
Bjelonic, M., Kottege, N., Homberger, T., Borges, P., Beckerle, P., & Chli, M. (2018) · Journal of Field Robotics · doi:10.1002/rob.21795 · Cited by 78
“, 2014a), ANYmal (Hutter et al., 2016), HyQ2Max (Semini et al.”
BackgroundHighly-Integrated Hydraulic Smart Actuators and Smart Manifolds for High-Bandwidth Force Control
Barasuol, V., Villarreal, O., Sangiah, D., Frigerio, M., Baker, M., Morgan, R., Medrano‐Cerda, G. A., Caldwell, D. G., & Semini, C. (2018) · Frontiers in Robotics and AI · doi:10.3389/frobt.2018.00051 · Cited by 76
“Considering the control bandwidth found in state-of-theart papers for related applications (Paine et al., 2014; Boaventura et al., 2015; Hutter et al., 2016), that ranges from 30 Hz to 60 Hz for small signals around 10%, the control performance obtained with the smart actuarors is relevant, promissing and are part of…”
BackgroundVersatile multicontact planning and control for legged loco-manipulation
Sleiman, J.-P., Farshidian, F., & Hutter, M. (2023) · Science Robotics · doi:10.1126/scirobotics.adg5014 · Cited by 80
Self-citationNot Only Rewards but Also Constraints: Applications on Legged Robot Locomotion
KIM, Y. H., Oh, H., Lee, J., Choi, J., Ji, G., Jung, M., Youm, D., & Hwangbo, J. (2024) · IEEE Transactions on Robotics · doi:10.1109/tro.2024.3400935 · Cited by 93
Self-citationSantina, C. D., Catalano, M. G., & Bicchi, A. (2020) · Springer eBooks · doi:10.1007/978-3-642-41610-1_146-1 · Cited by 73
Guided Constrained Policy Optimization for Dynamic Quadrupedal Robot Locomotion
Gangapurwala, S., Mitchell, A., & Havoutis, I. (2020) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2020.2979656 · Cited by 75
“The desired joint positions are forwarded as an input to the approximated actuator network which outputs the torques for each of the joints for the ANYmal quadruped.”
MethodInfluentialA survey on modularity and distributivity in series-parallel hybrid robots
Kumar, S., Wöhrle, H., Fernández, J. D. G., Müller, A., & Kirchner, F. (2020) · Mechatronics · doi:10.1016/j.mechatronics.2020.102367 · Cited by 74
Design and Dynamic Locomotion Control of Quadruped Robot with Perception-Less Terrain Adaptation
Wang, L., Meng, L., Kang, R., Liu, B., Gu, S., Zhang, Z., Meng, F., & Ming, A. (2022) · Cyborg and Bionic Systems · doi:10.34133/2022/9816495 · Cited by 71
“In recent years, many advanced quadruped robots have been achieved in terms of dynamic motion and stability, such as BigDog [2], StarIETH [3], HyQ [4], ANYmal [5], MIT Cheetah [6–8], Jueying [9], BQR [10], and Minitaur [11].”
BackgroundPerceptive whole‐body planning for multilegged robots in confined spaces
Buchanan, R., Wellhausen, L., Bjelonic, M., Bandyopadhyay, T., Kottege, N., & Hutter, M. (2020) · Journal of Field Robotics · doi:10.1002/rob.21974 · Cited by 69
“To perform experiments, we implemented our planner on the quadrupedal robot ANYmal (Hutter et al., 2016).”
MethodSelf-citationForceful manipulation with micro air vehicles
Estrada, M. A., Mintchev, S., Christensen, D. L., Cutkosky, M. R., & Floreano, D. (2018) · Science Robotics · doi:10.1126/scirobotics.aau6903 · Cited by 69
High-speed quadrupedal locomotion by imitation-relaxation reinforcement learning
Jin, Y., Liu, X., Shao, Y., Wang, H., & Yang, W. (2022) · Nature Machine Intelligence · doi:10.1038/s42256-022-00576-3 · Cited by 70
Electrohydraulic musculoskeletal robotic leg for agile, adaptive, yet energy-efficient locomotion
Buchner, T. J. K., Fukushima, T., Kazemipour, A., Gravert, S.-D., Prairie, M., Romanescu, P., Arm, P., Zhang, Y., Wang, X., Zhang, S. L., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-51568-3 · Cited by 72
Hwangbo, J., Bellicoso, C. D., Fankhauser, P., & Hutter, M. (2016) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2016.7759570 · Cited by 66
“In case of dynamic robots like StarlETH [1] and its decedent ANYmal [2], adding force sensors at the feet is undesirable due to the following three reasons.”
BackgroundMethodSelf-citationHeterogeneous Sensor Fusion for Accurate State Estimation of Dynamic Legged Robots
Nobili, S., Camurri, M., Barasuol, V., Focchi, M., Caldwell, D. G., Semini, C., & Fallon, M. F. (2017) · Robotics: Science and Systems · doi:10.15607/rss.2017.xiii.007 · Cited by 63
“Despite the improvements demonstrated by bipedal systems in the DARPA Robotics Challenge, for example [12], quadruped robots (Boston Dynamics LS3 [14], MIT Cheetah 2 [18], ANYmal [11]) present a more immediate solution to explore the parts of the world that are inaccessible to traditional robots.”
MethodChitikena, H., Sanfilippo, F., & Ma, S. (2023) · Applied Sciences · doi:10.3390/app13031800 · Cited by 78
Adaptive Force-based Control for Legged Robots
Sombolestan, M., Chen, Y., & Nguyen, Q. (2021) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9636393 · Cited by 63
Walking Posture Adaptation for Legged Robot Navigation in Confined Spaces
Buchanan, R., Bandyopadhyay, T., Bjelonic, M., Wellhausen, L., Hutter, M., & Kottege, N. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2899664 · Cited by 63
Self-citationRough Terrain Navigation for Legged Robots using Reachability Planning and Template Learning
Wellhausen, L., & Hutter, M. (2021) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9636358 · Cited by 59
“The abstraction used for the ANYmal [4] robot is shown in Figure 1.”
BackgroundMethodSelf-citationOnline LiDAR-SLAM for Legged Robots with Robust Registration and Deep-Learned Loop Closure
Ramezani, M., Tinchev, G., Egor, I., & Fallon, M. F. (2020) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra40945.2020.9196769 · Cited by 57
Virtual Model Control for Quadruped Robots
Chen, G., Guo, S. L., Hou, B., & Wang, J. (2020) · IEEE Access · doi:10.1109/access.2020.3013434 · Cited by 58
Learning-based legged locomotion: State of the art and future perspectives
Ha, S., Lee, J., van de Panne, M., Xie, Z., Yu, W., & Khadiv, M. (2025) · The International Journal of Robotics Research · doi:10.1177/02783649241312698 · Cited by 76
Benchmarking Classic and Learned Navigation in Complex 3D EnvironmentsPreprint
Mishkin, D., Dosovitskiy, A., & Koltun, V. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1901.10915 · Cited by 57
“Methods of this type have been successfully deployed on a variety of mobile robotic platforms [41, 4, 20].”
BackgroundBayer, J., & Faigl, J. (2019) · European Conference on Mobile Robots · doi:10.1109/ecmr.2019.8870968 · Cited by 56
“Generally, sufficiently large robots such [11], but also LAURON V [12] and ANYmal [13], have paid load capacity to be equipped with relatively large and heavy equipment (powerful computers, laser range finders, and appropriate power source).”
BackgroundDevelopment of a Quadruped Robot System With Torque-Controllable Modular Actuator Unit
Lee, Y. H., Lee, Y. H., Lee, H., Kang, H., Lee, J., Phan, L. T., Jin, S., Kim, Y. B., Seok, D.-Y., Lee, S. Y., et al. (2020) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2020.3007084 · Cited by 52
“The application of this superior technology to legged robots, such as StarlETH [21], ANYmal [22], AiDIN-IV [23], and Atrias [24], has demonstrated promising”
InfluentialDesign and Control of a Miniature Bipedal Robot with Proprioceptive Actuation for Dynamic Behaviors
Liu, Y., Shen, J., Zhang, J., Zhang, X., Zhu, T., & Hong, D. W. (2022) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra46639.2022.9811790 · Cited by 52
A Survey of Traversability Estimation for Mobile Robots
Sevastopoulos, C., & Konstantopoulos, S. (2022) · IEEE Access · doi:10.1109/access.2022.3202545 · Cited by 55
Design and Control for WLR-3P: A Hydraulic Wheel-Legged Robot
Li, X., Yu, H., Feng, H., Zhang, S., & Fu, Y. (2023) · Cyborg and Bionic Systems · doi:10.34133/cbsystems.0025 · Cited by 52
“Several state-ofthe-art robots like the humanoid Valkyrie [16] or the quadruped Anymal [17] showed how to use SEA not only for precise output force regulation but also for storing energy temporarily during locomotion.”
BackgroundInertial Measurement Units (IMUs) in Mobile Robots over the Last Five Years: A Review
Samatas, G. G., & Pachidis, T. P. (2022) · Designs · doi:10.3390/designs6010017 · Cited by 51
Coupling Vision and Proprioception for Navigation of Legged Robots
Fu, Z., Kumar, A., Agarwal, A., Qi, H., Malik, J., & Pathak, D. (2022) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52688.2022.01676 · Cited by 53
“Legged Locomotion: This has conventionally been accomplished using control theory [2, 5, 6, 22, 28, 31, 33, 39, 55, 63, 72, 88] over handcrafted dynamics models.”
MethodSmith, L., Kostrikov, I., & Levine, S. (2023) · Robotics: Science and Systems · doi:10.15607/rss.2023.xix.056 · Cited by 61
“RL with more complex quadrupedal robots [31] often used large amounts of simulation data.”
BackgroundMethodFrequency-Aware Model Predictive Control
Grandia, R., Farshidian, F., Dosovitskiy, A., Ranftl, R., & Hutter, M. (2019) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2019.2895882 · Cited by 51
“The quadruped robot ANYmal [1] trotting in place on non-rigid terrain.”
BackgroundSelf-citationFast and flexible multilegged locomotion using learned centroidal dynamics
Kwon, T., Lee, Y., & van de Panne, M. (2020) · ACM Transactions on Graphics · doi:10.1145/3386569.3392432 · Cited by 51
Adaptive Feet for Quadrupedal Walkers
Catalano, M. G., Pollayil, M. J., Grioli, G., Valsecchi, G., Kolvenbach, H., Hutter, M., Bicchi, A., & Garabini, M. (2021) · IEEE Transactions on Robotics · doi:10.1109/tro.2021.3088060 · Cited by 51
Self-citation
Metadata
- Authors
- Hutter, M., Gehring, C., Jud, D., Lauber, A., Bellicoso, C. D., Tsounis, V., Hwangbo, J., Bodie, K., Fankhauser, P., Bloesch, M., Diethelm, R., Bachmann, S., Melzer, A., & Hoepflinger, M.
- Affiliations
- ETH Zurich (CH)
- ORCID
- Venue
- 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Publisher
- IEEE
- Published
- 2016-10
- Pages
- 38-44
- ISSN
- 2153-0858 (ISSN-L)
- OpenAlex
- W4250058668
- Cited by
- 969
- References
- 28
- Citations by year
- 2026: 65 · 2025: 147 · 2024: 148 · 2023: 128 · 2022: 130 · 2021: 109 · 2020: 101 · 2019: 69 · 2018: 44 · 2017: 22 · 2016: 6
- FWCI
- 94.15
- Type
- conference paper
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- other-oa
- Locations
- IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (publishedVersion)
- Repository for Publications and Research Data (ETH Zurich) (submittedVersion, other-oa)
- ETH Zürich Research Collection
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Robotic Locomotion and Control
- Physical Sciences › Engineering › Control and Systems Engineering › Robotic Mechanisms and Dynamics
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Keywords
- ANYmal, quadrupedal robots, legged robots, torque control, gait, trotting, stair climbing, outdoor robots, dynamic locomotion
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