A legged central pattern generation model for autonomous gait transition
Conference paper
Yang, Z., Rocha, M., Lima, P., Karamanoglu, M. and Franca, F. 2014. A legged central pattern generation model for autonomous gait transition. 2014 IEEE International Joint Conference on Neural Networks (IJCNN). Beijing, China 06 - 11 Jul 2014 IEEE. pp. 1992-1995 https://doi.org/10.1109/IJCNN.2014.6889779
| Type | Conference paper |
|---|---|
| Title | A legged central pattern generation model for autonomous gait transition |
| Authors | Yang, Z., Rocha, M., Lima, P., Karamanoglu, M. and Franca, F. |
| Abstract | In this work, a generalized central pattern generator (CPG) model is formulated to generate a full range of gait patterns for a hexapod insect. To this end, a recurrent neural network module, as the building block for rhythmic patterns, is proposed to extend the concept of oscillatory building blocks (OBB) for constructing a CPG model. The model is able to make transitions between different gait patterns by simply adjusting one model parameter. Simulation results are further presented to show the effectiveness and performance |
| Keywords | Neurons; Mathematical model; Oscillators; Joints ; Biological system modeling; Legged locomotion; Generators |
| Conference | 2014 IEEE International Joint Conference on Neural Networks (IJCNN) |
| Page range | 1992-1995 |
| Proceedings Title | 2014 International Joint Conference on Neural Networks (IJCNN) |
| Series | IEEE International Joint Conference on Neural Networks (IJCNN) |
| ISSN | 2161-4393 |
| Electronic | 2161-4407 |
| ISBN | |
| Electronic | 9781479914845 |
| Publisher | IEEE |
| Publication dates | |
| 31 Jul 2014 | |
| Online | 04 Sep 2014 |
| Publication process dates | |
| Deposited | 28 May 2015 |
| Completed | Jul 2014 |
| Output status | Published |
| Publisher's version | File Access Level Restricted |
| Copyright Statement | Access to full text restricted pending copyright check. |
| Web address (URL) | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6889779 |
| Digital Object Identifier (DOI) | https://doi.org/10.1109/IJCNN.2014.6889779 |
| Web of Science identifier | WOS:000371465702013 |
| Language | English |
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