File:Adaptive-Fast-Walking-in-a-Biped-Robot-under-Neuronal-Control-and-Learning-pcbi.0030134.sv001.ogv
Adaptive-Fast-Walking-in-a-Biped-Robot-under-Neuronal-Control-and-Learning-pcbi.0030134.sv001.ogv (Ogg Theora video file, length 0.0 s, 312 × 240 pixels, 0 bps, file size: 4.93 MB)
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[edit]DescriptionAdaptive-Fast-Walking-in-a-Biped-Robot-under-Neuronal-Control-and-Learning-pcbi.0030134.sv001.ogv |
English: RunBot Can Perform Self-Stabilization When Changing Speed on the Fly In this situation, we immediately switch from a slower walking speed of 39 cm/s (≈1.7 leg-length/s) to a faster one of 73 cm/s (≈3.17 leg-length/s). This has been achieved by abruptly and strongly changing two parameters:
and gH. Self-stabilization reflects the cooperation between the mechanical properties and the neuronal control. Furthermore, it shows that RunBot's neuronal controller is robust to quite drastic and immediate parameter variations. Note that the real time data of the joint angles recorded during walking and changing speed on the fly is presented in Figure 5. (http://www.nld.ds.mpg.de/~poramate/RUNBOT/ManoonpongMovieS1.mpeg) (4.2 MPG). |
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Source | Video S1 from Manoonpong P, Geng T, Kulvicius T, Porr B, Wörgötter F (2007). "Adaptive, Fast Walking in a Biped Robot under Neuronal Control and Learning". PLOS Computational Biology. DOI:10.1371/journal.pcbi.0030134. PMID 17630828. PMC: 1914373. | ||
Author | Manoonpong P, Geng T, Kulvicius T, Porr B, Wörgötter F | ||
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Date/Time | Thumbnail | Dimensions | User | Comment | |
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current | 19:46, 30 October 2012 | 0.0 s, 312 × 240 (4.93 MB) | Open Access Media Importer Bot (talk | contribs) | Automatically uploaded media file from Open Access source. Please report problems or suggestions here. |
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Short title | RunBot Can Perform Self-Stabilization When Changing Speed on the Fly |
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Author | |
Usage terms | http://creativecommons.org/licenses/by/3.0/ |
Image title | In this situation, we immediately switch from a slower walking speed of 39 cm/s (?1.7 leg-length/s) to a faster one of 73 cm/s (?3.17 leg-length/s). This has been achieved by abruptly and strongly changing two parameters:
and gH. Self-stabilization reflects the cooperation between the mechanical properties and the neuronal control. Furthermore, it shows that RunBot's neuronal controller is robust to quite drastic and immediate parameter variations. Note that the real time data of the joint angles recorded during walking and changing speed on the fly is presented in Figure 5. (http://www.nld.ds.mpg.de/~poramate/RUNBOT/ManoonpongMovieS1.mpeg) (4.2 MPG). |
Software used | Xiph.Org libtheora 1.1 20090822 (Thusnelda) |
Date and time of digitizing | 2007-07 |