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In this work, we show how to learn a visual walking policy that only uses a monocular RGB camera and proprioception.
H. Von Helmholtz, Helmholtz’s treatise on physiological optics . Optical Society of America, 1925, vol. 3
1925
Earlier work this paper cites.
J. M. Loomis, J. A. Da Silva, N. Fujita, and S. S. Fukusima, “Visual space perception and visually directed action.” Journal of experimental psychology: Human Perception and Performance , vol. 18, no. 4, p. 906, 1992
1992
Earlier work this paper cites.
J. Templer, The Staircase: Studies of Hazards, Falls, and Safer Design . The MIT PressNational Endowment for the Humanities/Andrew W. Mellon Foundation Humanities Open Book Program., 03 1995. [Online]. Available: https://doi.org/10.7551/mitpress/6434.001.0001
1995
Earlier work this paper cites.
A. E. Patla, “Understanding the roles of vision in the control of human locomotion,” Gait & posture , vol. 5, no. 1, pp. 54–69, 1997
1997
Earlier work this paper cites.
A. Patla, “Strategies for dynamic stability during adaptive human locomotion,” IEEE Engineering in Medicine and Biology Magazine , vol. 22, no. 2, pp. 48–52, 2003
2003
Earlier work this paper cites.
R. Hartley and A. Zisserman, Multiple view geometry in computer vision . Cambridge university press, 2003
2003
Earlier work this paper cites.
J. Buchli, M. Kalakrishnan, M. Mistry, P. Pastor, and S. Schaal, “Compliant quadruped locomotion over rough terrain,” in 2009 IEEE/RSJ international conference on Intelligent robots and systems . IEEE, 2009, pp. 814–820
2009
Earlier work this paper cites.
K. Byl and R. Tedrake, “Dynamically diverse legged locomotion for rough terrain,” in 2009 IEEE International Conference on Robotics and Automation , 2009, pp. 1607–1608
2009
Earlier work this paper cites.
M. A. Hoepflinger, C. D. Remy, M. Hutter, L. Spinello, and R. Siegwart, “Haptic terrain classification for legged robots,” in 2010 IEEE International Conference on Robotics and Automation . IEEE, 2010, pp. 2828–2833
2010
Earlier work this paper cites.
M. Kalakrishnan, J. Buchli, P. Pastor, M. Mistry, and S. Schaal, “Learning, planning, and control for quadruped locomotion over challenging terrain,” The International Journal of Robotics Research , vol. 30, no. 2, pp. 236–258, 2011
2011
Earlier work this paper cites.
J. Z. Kolter and A. Y. Ng, “The stanford LittleDog: A learning and rapid replanning approach to quadruped locomotion,” The International Journal of Robotics Research , vol. 30, no. 2, pp. 150–174, jan 2011
2011
Earlier work this paper cites.
M. Zucker, N. Ratliff, M. Stolle, J. Chestnutt, J. A. Bagnell, C. G. Atkeson, and J. Kuffner, “Optimization and learning for rough terrain legged locomotion,” The International Journal of Robotics Research , vol. 30, no. 2, pp. 175–191, 2011
2011
Earlier work this paper cites.
A. Barrett, K. M. Goedert, and J. C. Basso, “Prism adaptation for spatial neglect after stroke: translational practice gaps,” Nature Reviews Neurology , vol. 8, no. 10, p. 567, 2012
2012
Earlier work this paper cites.
K. S. Kretch, J. M. Franchak, and K. E. Adolph, “Crawling and walking infants see the world differently,” Child Development , vol. 85, no. 4, pp. 1503–1518, dec 2013
2013
Earlier work this paper cites.
M. Khoramshahi, H. J. Bidgoly, S. Shafiee, A. Asaei, A. J. Ijspeert, and M. N. Ahmadabadi, “Piecewise linear spine for speed–energy efficiency trade-off in quadruped robots,” Robotics and Autonomous Systems , vol. 61, no. 12, pp. 1350–1359, dec 2013
2013
Earlier work this paper cites.
A. D. Ames, K. Galloway, K. Sreenath, and J. W. Grizzle, “Rapidly exponentially stabilizing control lyapunov functions and hybrid zero dynamics,” IEEE Transactions on Automatic Control , vol. 59, no. 4, pp. 876–891, apr 2014
2014
Earlier work this paper cites.
M. Hoffmann, K. Štěpánová, and M. Reinstein, “The effect of motor action and different sensory modalities on terrain classification in a quadruped robot running with multiple gaits,” Robotics and Autonomous Systems , vol. 62, no. 12, pp. 1790–1798, 2014
2014
Earlier work this paper cites.
R. Calandra, A. Seyfarth, J. Peters, and M. P. Deisenroth, “Bayesian optimization for learning gaits under uncertainty,” Annals of Mathematics and Artificial Intelligence , vol. 76, no. 1-2, pp. 5–23, jun 2015
2015
Cited alongside, same era.
H.-W. Park, P. M. Wensing, S. Kim et al. , “Online planning for autonomous running jumps over obstacles in high-speed quadrupeds,” Robotics: Science and Systems , 2015
2015
Cited alongside, same era.
K. Walas, “Terrain classification and negotiation with a walking robot,” Journal of Intelligent & Robotic Systems , vol. 78, no. 3, pp. 401–423, 2015
2015
Cited alongside, same era.
D. J. Hyun, J. Lee, S. Park, and S. Kim, “Implementation of trot-to-gallop transition and subsequent gallop on the MIT cheetah i,” The International Journal of Robotics Research , vol. 35, no. 13, pp. 1627–1650, jul 2016
2016
Cited alongside, same era.
A. Kumar, Z. Fu, D. Pathak, and J. Malik, “Rma: Rapid motor adaptation for legged robots,” in Robotics: Science and Systems , 2021
2021
Later among the works it cites.
K. Bonnen, J. S. Matthis, A. Gibaldi, M. S. Banks, D. M. Levi, and M. Hayhoe, “Binocular vision and the control of foot placement during walking in natural terrain,” Scientific reports , vol. 11, no. 1, pp. 1–12, 2021
2021
Later among the works it cites.
A. Loquercio, E. Kaufmann, R. Ranftl, M. Müller, V. Koltun, and D. Scaramuzza, “Learning high-speed flight in the wild,” Science Robotics , vol. 6, no. 59, p. eabg5810, 2021
2021
Later among the works it cites.
Z. Fu, A. Kumar, J. Malik, and D. Pathak, “Minimizing energy consumption leads to the emergence of gaits in legged robots,” 2021
2021
Later among the works it cites.
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C. Gehring, S. Coros, M. Hutter, C. Dario Bellicoso, H. Heijnen, R. Diethelm, M. Bloesch, P. Fankhauser, J. Hwangbo, M. Hoepflinger, and R. Siegwart, “Practice makes perfect: An optimization-based approach to controlling agile motions for a quadruped robot,” IEEE Robotics Automation Magazine , vol. 23, no. 1, pp. 34–43, 2016
2016
Cited alongside, same era.
X. A. Wu, T. M. Huh, R. Mukherjee, and M. Cutkosky, “Integrated ground reaction force sensing and terrain classification for small legged robots,” IEEE Robotics and Automation Letters , vol. 1, no. 2, pp. 1125–1132, 2016
2016
Cited alongside, same era.
C. D. Bellicoso, F. Jenelten, P. Fankhauser, C. Gehring, J. Hwangbo, and M. Hutter, “Dynamic locomotion and whole-body control for quadrupedal robots,” in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2017, pp. 3359–3365
2017
Cited alongside, same era.
A. Valada and W. Burgard, “Deep spatiotemporal models for robust proprioceptive terrain classification,” The International Journal of Robotics Research , vol. 36, no. 13-14, pp. 1521–1539, 2017
2017
Cited alongside, same era.
J. Hwangbo, J. Lee, and M. Hutter, “Per-contact iteration method for solving contact dynamics,” IEEE Robotics and Automation Letters , vol. 3, no. 2, pp. 895–902, 2018. [Online]. Available: www.raisim.com
2018
Cited alongside, same era.
N. Ma, X. Zhang, H.-T. Zheng, and J. Sun, “Shufflenet v2: Practical guidelines for efficient cnn architecture design,” in Proceedings of the European conference on computer vision (ECCV) , 2018, pp. 116–131
2018
Cited alongside, same era.
R. O. Chavez-Garcia, J. Guzzi, L. M. Gambardella, and A. Giusti, “Learning ground traversability from simulations,” IEEE Robotics and Automation letters , vol. 3, no. 3, pp. 1695–1702, 2018
2018
Cited alongside, same era.
J. Hwangbo, J. Lee, A. Dosovitskiy, D. Bellicoso, V. Tsounis, V. Koltun, and M. Hutter, “Learning agile and dynamic motor skills for legged robots,” Science Robotics , vol. 4, no. 26, p. eaau5872, 2019
2019
Cited alongside, same era.
2021
Later among the works it cites.
M. Gaertner, M. Bjelonic, F. Farshidian, and M. Hutter, “Collision-free mpc for legged robots in static and dynamic scenes,” in 2021 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2021, pp. 8266–8272
2021
Later among the works it cites.
2021
Later among the works it cites.
G. B. Margolis, T. Chen, K. Paigwar, X. Fu, D. Kim, S. bae Kim, and P. Agrawal, “Learning to jump from pixels,” in 5th Annual Conference on Robot Learning , 2021. [Online]. Available: https://openreview.net/forum?id=R4E8wTUtxdl
2021
Later among the works it cites.
W. Yu, D. Jain, A. Escontrela, A. Iscen, P. Xu, E. Coumans, S. Ha, J. Tan, and T. Zhang, “Visual-locomotion: Learning to walk on complex terrains with vision,” in 5th Annual Conference on Robot Learning , 2021. [Online]. Available: https://openreview.net/forum?id=NDYbXf-DvwZ
2021
Later among the works it cites.
B. Yang, L. Wellhausen, T. Miki, M. Liu, and M. Hutter, “Real-time optimal navigation planning using learned motion costs,” in 2021 IEEE International Conference on Robotics and Automation (ICRA) . IEEE, 2021, pp. 9283–9289
2021
Later among the works it cites.
G. Kahn, P. Abbeel, and S. Levine, “Badgr: An autonomous self-supervised learning-based navigation system,” IEEE Robotics and Automation Letters , vol. 6, no. 2, pp. 1312–1319, 2021
2021
Later among the works it cites.
R. Ranftl, K. Lasinger, D. Hafner, K. Schindler, and V. Koltun, “Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 44, no. 3, 2022
2022
Closest in time.
A. Agarwal, A. Kumar, J. Malik, and D. Pathak, “Legged locomotion in challenging terrains using egocentric vision,” 2022. [Online]. Available: https://openreview.net/pdf?id=Re3NjSwf0WF
2022
Closest in time.
T. Miki, J. Lee, J. Hwangbo, L. Wellhausen, V. Koltun, and M. Hutter, “Learning robust perceptive locomotion for quadrupedal robots in the wild,” Science Robotics , vol. 7, no. 62, p. eabk2822, 2022
2022
Closest in time.
N. Rudin, D. Hoeller, P. Reist, and M. Hutter, “Learning to walk in minutes using massively parallel deep reinforcement learning,” in Conference on Robot Learning . PMLR, 2022, pp. 91–100
2022
Closest in time.
R. Yang, M. Zhang, N. Hansen, H. Xu, and X. Wang, “Learning vision-guided quadrupedal locomotion end-to-end with cross-modal transformers,” in International Conference on Learning Representations , 2022. [Online]. Available: https://openreview.net/forum?id=nhnJ3oo6AB
2022
Closest in time.