Abstract
In this article, we use a recurrent neural network including four-cell core architecture to model the walking gait and implement it with the simulated and physical NAO robot. Meanwhile, inspired by the biological CPG models, we propose a simplified CPG model which comprises motorneurons, interneurons, sensor neurons and the simplified spinal cord. Within this model, the CPGs do not directly output trajectories to the servo motors. Instead, they only work to maintain the phase relation among ipsilateral and contralateral limbs. The final output is dependent on the integration of CPG signals, outputs of interneurons, motor neurons and sensor neurons (sensory feedback).
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Amrollah, E., Henaff, P.: On the role of sensory feedbacks in rowat–selverston cpg to improve robot legged locomotion. Frontiers in Neuroscience 4 (2010)
Geng, T., Porr, B., Worgotter, F.: Fast biped walking with a sensor-driven neuronal controller and real-time online learning. Journal of Robotics Research 25, 243–259 (2006)
Ijspeert, A.J.: Central pattern generators for locomotion control in animals and robots: a review. Neural Networks 21(4), 642–653 (2008)
Latash, M.L.: Neurophysiological Basis of Movement. Human Kinetics Publishers (1998)
Lee, G., Lowe, R., Ziemke, T.: Modelling early infant walking: Testing a generic cpg architecture on the nao humanoid. In: Proceedings of Development and Learning (ICDL) 2011 IEEE International Conference, Frankfurt, Germany (October 2011)
Li, C., Lowe, R., Duran, B., Ziemke, T.: Humanoids that crawl: Comparing gait performance of icub and nao using a cpg architecture. In: Computer Science and Automation Engineering (CSAE), Shanghai, China (May 2011)
Liu, C., Chen, Q., Wang, D.: Biped robot walking using central pattern generator and genetic algorithm. In: Proceeding of International Conference on Robotics (2010)
Nakamura, Y., Mori, T., Sato, M., Ishii, S.: Reinforcement learning for a biped robot based on a cpg-actor-critic method. Neural Netw. 20(6), 723–735 (2007)
Nassour, J., Hénaff, P., Ben Ouezdou, F., Cheng, G.: A Study of Adaptive Locomotive Behaviors of a Biped Robot: Patterns Generation and Classification. In: Doncieux, S., Girard, B., Guillot, A., Hallam, J., Meyer, J.-A., Mouret, J.-B. (eds.) SAB 2010. LNCS, vol. 6226, pp. 313–324. Springer, Heidelberg (2010)
Orlovskii, G.N., Deliagina, T.G., Grillner, S.: Neuronal control of locomotion: from mollusc to man. Oxford University Press (1999)
Righetti, L., Ijspeert, A.: Design methodologies for central pattern generators: an application to crawling humanoids. In: Proceedings of Robotics: Science and Systems, Philadelphia, USA (August 2006)
Rutishauser, S., Spröwitz, A., Righetti, L., Ijspeert, A.J.: Passive compliant quadruped robot using central pattern generators for locomotion control. Physica 577.2, 617–639 (2006)
Rybak, I.A., Shevtsova, N.A., Lafreniere-Roula, M., McCrea, D.A.: Modelling spinal circuitry involved in locomotor pattern generation: insights from deletions during fictive locomotion. The Journal of Physiology Online 577, 617–639 (2006)
Thelen, E., Smith, L.B.: A dynamic systems approach to the development of cognition and action. MIT Press, Boston (1994)
Vaal, J., Van Soest, A.J., Hopkins, B.: Modelling the early development of bipedal locomotion: A multidisciplinary approach. Human Movement Science 14(4-5), 609–636 (1995)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Li, C., Lowe, R., Ziemke, T. (2012). Modelling Walking Behaviors Based on CPGs: A Simplified Bio-inspired Architecture. In: Ziemke, T., Balkenius, C., Hallam, J. (eds) From Animals to Animats 12. SAB 2012. Lecture Notes in Computer Science(), vol 7426. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33093-3_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-33093-3_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33092-6
Online ISBN: 978-3-642-33093-3
eBook Packages: Computer ScienceComputer Science (R0)