{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T17:57:38Z","timestamp":1755799058031,"version":"3.44.0"},"publisher-location":"Cham","reference-count":28,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783032014856"},{"type":"electronic","value":"9783032014863"}],"license":[{"start":{"date-parts":[[2025,8,13]],"date-time":"2025-08-13T00:00:00Z","timestamp":1755043200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,13]],"date-time":"2025-08-13T00:00:00Z","timestamp":1755043200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-01486-3_11","type":"book-chapter","created":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T15:47:07Z","timestamp":1755618427000},"page":"124-137","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Acrobotics: A Generalist Approach to\u00a0Quadrupedal Robots\u2019 Parkour"],"prefix":"10.1007","author":[{"given":"Guillaume","family":"Gagn\u00e9-Labelle","sequence":"first","affiliation":[]},{"given":"Vassil","family":"Atanassov","sequence":"additional","affiliation":[]},{"given":"Ioannis","family":"Havoutis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,13]]},"reference":[{"key":"11_CR1","doi-asserted-by":"publisher","unstructured":"Atanassov, V., Ding, J., Kober, J., Havoutis, I., Santina, C.D.: Curriculum-based reinforcement learning for quadrupedal jumping: a reference-free design. IEEE Robot. Autom. Mag. 2\u201315 (2024). https:\/\/doi.org\/10.1109\/MRA.2024.3487325","DOI":"10.1109\/MRA.2024.3487325"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Bouman, A., et al.: Autonomous spot: long-range autonomous exploration of extreme environments with legged locomotion (2020). https:\/\/arxiv.org\/abs\/2010.09259","DOI":"10.1109\/IROS45743.2020.9341361"},{"key":"11_CR3","unstructured":"Caluwaerts, K., et\u00a0al.: Barkour: benchmarking animal-level agility with quadruped robots. arXiv preprint arXiv:2305.14654 (2023)"},{"key":"11_CR4","unstructured":"Campanaro, L., De\u00a0Martini, D., Gangapurwala, S., Merkt, W., Havoutis, I.: Roll-drop: accounting for observation noise with a single parameter. In: Proceedings of Machine Learning Research, pp. 718\u2013730. Proceedings of Machine Learning Research (2023)"},{"key":"11_CR5","unstructured":"Campanaro, L., Gangapurwala, S., Merkt, W., Havoutis, I.: Learning and deploying robust locomotion policies with minimal dynamics randomization. In: Proceedings of Machine Learning Research, pp. 578\u2013590. Proceedings of Machine Learning Research (2024)"},{"key":"11_CR6","unstructured":"Chen, D., Zhou, B., Koltun, V., Kr\u00e4henb\u00fchl, P.: Learning by cheating. In: Proceedings of the Conference on Robot Learning, pp. 66\u201375. PMLR (2020). https:\/\/proceedings.mlr.press\/v100\/chen20a.html"},{"key":"11_CR7","doi-asserted-by":"crossref","unstructured":"Cheng, X., Shi, K., Agarwal, A., Pathak, D.: Extreme parkour with legged robots. arXiv preprint arXiv:2309.14341 (2023)","DOI":"10.1109\/ICRA57147.2024.10610200"},{"key":"11_CR8","doi-asserted-by":"publisher","unstructured":"Gangapurwala, S., Campanaro, L., Havoutis, I.: Learning low-frequency motion control for robust and dynamic robot locomotion. In: 2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 5085\u20135091. IEEE, London (2023). https:\/\/doi.org\/10.1109\/ICRA48891.2023.10160357. https:\/\/ieeexplore.ieee.org\/document\/10160357\/","DOI":"10.1109\/ICRA48891.2023.10160357"},{"key":"11_CR9","doi-asserted-by":"publisher","unstructured":"Gangapurwala, S., Geisert, M., Orsolino, R., Fallon, M., Havoutis, I.: RLOC: terrain-aware legged locomotion using reinforcement learning and optimal control. IEEE Trans. Rob. 38(5), 2908\u20132927 (2022). https:\/\/doi.org\/10.1109\/TRO.2022.3172469. Conference Name: IEEE Transactions on Robotics","DOI":"10.1109\/TRO.2022.3172469"},{"key":"11_CR10","series-title":"Springer Proceedings in Advanced Robotics","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/978-981-15-9460-1_18","volume-title":"Field and Service Robotics","author":"C Gehring","year":"2021","unstructured":"Gehring, C., Fankhauser, P., Isler, L., Diethelm, R., Bachmann, S., Potz, M., Gerstenberg, L., Hutter, M.: ANYmal in the field: solving industrial inspection of an offshore HVDC platform with a quadrupedal robot. In: Ishigami, G., Yoshida, K. (eds.) Field and Service Robotics. SPAR, vol. 16, pp. 247\u2013260. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-15-9460-1_18"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Henderson, P., Islam, R., Bachman, P., Pineau, J., Precup, D., Meger, D.: Deep reinforcement learning that matters. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a032 (2018)","DOI":"10.1609\/aaai.v32i1.11694"},{"key":"11_CR12","doi-asserted-by":"crossref","unstructured":"Hoeller, D., Rudin, N., Sako, D., Hutter, M.: Anymal parkour: learning agile navigation for quadrupedal robots (2023). https:\/\/arxiv.org\/abs\/2306.14874","DOI":"10.1126\/scirobotics.adi7566"},{"key":"11_CR13","doi-asserted-by":"publisher","unstructured":"Hwangbo, J., et al.: Learning agile and dynamic motor skills for legged robots. Science Robotics 4(26), eaau5872 (2019). https:\/\/doi.org\/10.1126\/scirobotics.aau5872. https:\/\/www.science.org\/doi\/full\/10.1126\/scirobotics.aau5872. publisher: American Association for the Advancement of Science","DOI":"10.1126\/scirobotics.aau5872"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"Hwangbo, J., et al.: Learning agile and dynamic motor skills for legged robots. Sci. Robot. 4(26), eaau5872 (2019)","DOI":"10.1126\/scirobotics.aau5872"},{"key":"11_CR15","doi-asserted-by":"publisher","unstructured":"Kumar, A., Fu, Z., Pathak, D., Malik, J.: RMA: rapid motor adaptation for legged robots. In: Robotics: Science and Systems XVII. Robotics: Science and Systems Foundation (2021). https:\/\/doi.org\/10.15607\/RSS.2021.XVII.011. http:\/\/www.roboticsproceedings.org\/rss17\/p011.pdf","DOI":"10.15607\/RSS.2021.XVII.011"},{"key":"11_CR16","doi-asserted-by":"publisher","unstructured":"Lee, J., Hwangbo, J., Wellhausen, L., Koltun, V., Hutter, M.: Learning quadrupedal locomotion over challenging terrain. Sci. Robot. 5(47), eabc5986 (2020). https:\/\/doi.org\/10.1126\/scirobotics.abc5986. https:\/\/www.science.org\/doi\/10.1126\/scirobotics.abc5986. Publisher: American Association for the Advancement of Science","DOI":"10.1126\/scirobotics.abc5986"},{"key":"11_CR17","unstructured":"Makoviychuk, V., et al.: Isaac gym: high performance GPU-based physics simulation for robot learning (2021). https:\/\/arxiv.org\/abs\/2108.10470"},{"key":"11_CR18","unstructured":"Margolis, G.B., Agrawal, P.: Walk these ways: tuning robot control for generalization with multiplicity of behavior. In: Proceedings of The 6th Conference on Robot Learning, pp. 22\u201331. PMLR (2023). https:\/\/proceedings.mlr.press\/v205\/margolis23a.html"},{"key":"11_CR19","unstructured":"Merel, J., et al.: Hierarchical visuomotor control of humanoids. arXiv preprint arXiv:1811.09656 (2018)"},{"key":"11_CR20","doi-asserted-by":"publisher","unstructured":"Miki, T., Lee, J., Hwangbo, J., Wellhausen, L., Koltun, V., Hutter, M.: Learning robust perceptive locomotion for quadrupedal robots in the wild. Sci. Robot. 7(62), eabk2822 (2022).https:\/\/doi.org\/10.1126\/scirobotics.abk2822. https:\/\/www.science.org\/doi\/full\/10.1126\/scirobotics.abk2822. publisher: American Association for the Advancement of Science","DOI":"10.1126\/scirobotics.abk2822"},{"key":"11_CR21","doi-asserted-by":"crossref","unstructured":"Miki, T., Lee, J., Wellhausen, L., Hutter, M.: Learning to walk in confined spaces using 3D representation (2024). https:\/\/arxiv.org\/abs\/2403.00187","DOI":"10.1109\/ICRA57147.2024.10610271"},{"key":"11_CR22","doi-asserted-by":"crossref","unstructured":"Rudin, N., Hoeller, D., Bjelonic, M., Hutter, M.: Advanced skills by learning locomotion and local navigation end-to-end. In: 2022 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 2497\u20132503. IEEE (2022)","DOI":"10.1109\/IROS47612.2022.9981198"},{"key":"11_CR23","unstructured":"Rudin, N., Hoeller, D., Reist, P., Hutter, M.: Learning to walk in minutes using massively parallel deep reinforcement learning. In: Conference on Robot Learning, pp. 91\u2013100. PMLR (2022)"},{"key":"11_CR24","unstructured":"Schulman, J., Wolski, F., Dhariwal, P., Radford, A., Klimov, O.: Proximal policy optimization algorithms (2017). https:\/\/arxiv.org\/abs\/1707.06347"},{"key":"11_CR25","unstructured":"Sutton, R.: The bitter lesson (2019). http:\/\/www.incompleteideas.net\/IncIdeas\/BitterLesson.html"},{"key":"11_CR26","unstructured":"Sutton, R.S., Barto, A.G.: Reinforcement Learning: An Introduction. 2nd edn. The MIT Press, Cambridge (2018). http:\/\/incompleteideas.net\/book\/the-book-2nd.html"},{"key":"11_CR27","unstructured":"Wang, Z., Yang, E., Shen, L., Huang, H.: A comprehensive survey of forgetting in deep learning beyond continual learning (2023). https:\/\/arxiv.org\/abs\/2307.09218"},{"key":"11_CR28","unstructured":"Zhuang, Z., et al.: Robot parkour learning. arXiv preprint arXiv:2309.05665 (2023)"}],"container-title":["Lecture Notes in Computer Science","Towards Autonomous Robotic Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-01486-3_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,19]],"date-time":"2025-08-19T15:47:15Z","timestamp":1755618435000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-01486-3_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,13]]},"ISBN":["9783032014856","9783032014863"],"references-count":28,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-01486-3_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,8,13]]},"assertion":[{"value":"13 August 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"TAROS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Annual Conference Towards Autonomous Robotic Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"York","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"taros2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/taros-conference.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}