Data driven models of legged locomotion
| dc.contributor.author | Revzen, Shai | |
| dc.contributor.author | Kvalheim, Matthew D. | |
| dc.date.accessioned | 2024-12-11T17:02:19Z | |
| dc.date.available | 2024-12-11T17:02:19Z | |
| dc.date.issued | 2015-05-22 | |
| dc.description | SPIE Defense + Security, 2015, Baltimore, MD, United States | |
| dc.description.abstract | Legged locomotion is a challenging regime both for experimental analysis and for robot design. From biology, we know that legged animals can perform spectacular feats which our machines can only surpass on some specially controlled surfaces such as roads. We present a concise review of the theoretical underpinnings of Data Driven Floquet Analysis (DDFA), an approach for empirical modeling of rhythmic dynamical systems. We provide a review of recent and classical results which justify its use in the analysis of legged systems. | |
| dc.description.sponsorship | We wish to thank John Guckenheimer, Sam Burden, and Moritz Maus for their contributions to the work presented herein. This research was supported in part by ARO Young Investigator Award #61770 to S. Revzen, Army Research Laboratory Cooperative Agreements W911NF–08–2–0004 and W911NF–10–2–0016; and National Science Foundation Award #1028237. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute for Government purposes notwithstanding any copyright notation herein. | |
| dc.description.uri | https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9467/94671V/Data-driven-models-of-legged-locomotion/10.1117/12.2178007.full | |
| dc.format.extent | 8 pages | |
| dc.genre | conference papers and proceedings | |
| dc.identifier | doi:10.13016/m2tcdx-1dqm | |
| dc.identifier.citation | Revzen, Shai, and Matthew Kvalheim. “Data Driven Models of Legged Locomotion.” In Micro- and Nanotechnology Sensors, Systems, and Applications VII, 9467:315–22. SPIE, 2015. https://doi.org/10.1117/12.2178007. | |
| dc.identifier.uri | https://doi.org/10.1117/12.2178007 | |
| dc.identifier.uri | http://hdl.handle.net/11603/37052 | |
| dc.language.iso | en_US | |
| dc.publisher | SPIE | |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Mathematics and Statistics Department | |
| dc.rights | ©(2015) Society of Photo-Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. | |
| dc.title | Data driven models of legged locomotion | |
| dc.type | Text | |
| dcterms.creator | https://orcid.org/0000-0002-2662-6760 |
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