DYNAMICAL INVARIANTS FOR CPG CONTROL IN AUTONOMOUS ROBOTS
Fernando Herrero-Carrón, Francisco de Borja Rodríguez, Pablo Varona
2010
Abstract
Several studies have shown the usefulness of central pattern generator circuits to control autonomous rhythmic motion in robots. The traditional approach is building CPGs from nonlinear oscillators, adjusting a connectivity matrix and its weights to achieve the desired function. Compared to existing living CPGs, this approach seems still somewhat limited in resources. Living CPGs have a large number of available mechanisms to accomplish their task. The main function of a CPG is ensuring that some constraints regarding rhythmic activity are always kept, surmounting any disturbances from the external environment. We call this constraints the “dynamical invariant” of a CPG. Understanding the underlying biological mechanisms would take the design of robotic CPGs a step further. It would allow us to begin the design with a set of invariants to be preserved. The presence of these invariants will guarantee that, in response to unexpected conditions, an effective motor program will emerge that will perform the expected function, without the need of anticipating every possible scenario. In this paper we discuss how some bio-inspired elements contribute to building up these invariants.
References
- Aguirre, C., Campos, D., Pascual, P., and Serrano, E. (2005). A model of spiking-bursting neuronal behavior using a piecewise linear two-dimensional map. Computational Intelligence and Bioinspired Systems, pages 130-135.
- Arshavsky, Y. I., Deliagina, T. G., Orlovsky, G. N., Panchin, Y. V., Popova, L. B., and Sadreyev, R. I. (1998). Analysis of the central pattern generator for swimming in the mollusk clione. Annals of the New York Academy of Sciences, 860(1):51-69.
- Brezina, V., Orekhova, I. V., and Weiss, K. R. (2000). The neuromuscular transform: The dynamic, nonlinear link between motor neuron firing patterns and muscle contraction in rhythmic behaviors. J Neurophysiol, 83(1):207-231.
- Bucher, D., Prinz, A. A., and Marder, E. (2005). Animalto-animal variability in motor pattern production in adults and during growth. J. Neurosci., 25(7):1611- 1619.
- Elson, R. C., Selverston, A. I., Abarbanel, H. D., and Rabinovich, M. I. (2002). Inhibitory synchronization of bursting in biological neurons: Dependence on synaptic time constant. J Neurophysiol, 88(3):1166-1176.
- Grillner, S. (2006). Biological pattern generation: The cellular and computational logic of networks in motion. Neuron, 52(5).
- Grillner, S., Hellgren, J., Ménard, A., Saitoh, K., and Wikström, M. A. (2005). Mechanisms for selection of basic motor programs-roles for the striatum and pallidum. Trends Neurosci, 28(7):364-370.
- Herrero-Carrón, F., Rodríguez, F. d. B., and Varona, P. (2010). Bio-inspired design strategies for cpg control in modular robotics. Submitted.
- Hindmarsh, J. L. and Rose, R. M. (1984). A model of neuronal bursting using three coupled first order differential equations. Proceedings Of The Royal Society Of London. Series B, Containing Papers Of a Biological Character. Royal Society (Great Britain), 221(1222):87-102.
- Hodgkin, A. L. and Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation in nerve. The Journal of physiology, 117(4):500-544.
- Huerta, R., Varona, P., Rabinovich, M. I., and Abarbanel, H. D. (2001). Topology selection by chaotic neurons of a pyloric central pattern generator. Biological Cybernetics, 84(1):L1-L8.
- Ijspeert, A. (2008). Central pattern generators for locomotion control in animals and robots: A review. Neural Networks, 21(4):642-653.
- Kopell, N. and Ermentrout, G. (2000). Mechanisms of phase-locking and frequency control in pairs of coupled neural oscillators.
- Kopell, N. and Somers, D. (1995). Anti-phase solutions in relaxation oscillators coupled through excitatory interactions. Journal of Mathematical Biology, 33(3):261- 280.
- Latorre, R., Rodríguez, F., and Varona, P. (2006). Neural signatures: Multiple coding in spiking-bursting cells. Biological Cybernetics, 95(2):169-183.
- Marder, E. and Goaillard, J.-M. (2006). Variability, compensation and homeostasis in neuron and network function. Nature Reviews Neuroscience, 7(7):563- 574.
- Marder, E. and Prinz, A. A. (2002). Modeling stability in neuron and network function: the role of activity in homeostasis. BioEssays : news and reviews in molecular, cellular and developmental biology., 24(12):1145-1154.
- Oprisan, S. A., Prinz, A. A., and Canavier, C. C. (2004). Phase resetting and phase locking in hybrid circuits of one model and one biological neuron. Biophys J, 87(4):2283-2298.
- Prinz, A. A., Bucher, D., and Marder, E. (2004). Similar network activity from disparate circuit parameters. Nature Neuroscience, 7(12):1345-1352.
- Reyes, M., Huerta, R., Rabinovich, M., and Selverston, A. (2008). Artificial synaptic modification reveals a dynamical invariant in the pyloric cpg. European Journal of Applied Physiology, 102(6):667-675.
- Rowat, P. F. and Selverston, A. I. (1997). Oscillatory mechanisms in pairs of neurons connected with fast inhibitory synapses. Journal of Computational Neuroscience, 4(2):103-127.
- Rulkov, N. F. (2002). Modeling of spiking-bursting neural behavior using two-dimensional map. Physical Review E, 65(4):041922+.
- Selverston, A. B., Szücs, A., Huerta, R., Pinto, R. D., and Reyes, M. (2009). Neural mechanisms underlying the generation of the lobster gastric mill motor pattern. Frontiers in Neural Circuits.
- Stiesberg, G. R., Reyes, M. B., Varona, P., Pinto, R. D., and Huerta, R. (2007). Connection topology selection in central pattern generators by maximizing the gain of information. Neural Computation, 19(4):974-993.
- Szucs, A., Pinto, R. D., Rabinovich, M. I., Abarbanel, H. D., and Selverston, A. I. (2003). Synaptic modulation of the interspike interval signatures of bursting pyloric neurons. Journal of neurophysiology, 89(3):1363-1377.
- Thoby-Brisson, M. and Simmers, J. (1998). Neuromodulatory inputs maintain expression of a lobster motor pattern-generating network in a modulationdependent state: Evidence from long-term decentralization in vitro. J. Neurosci., 18(6):2212-2225.
- Wang, X.-J. and Rinzel, J. (1992). Alternating and synchronous rhythms in reciprocally inhibitory model neurons. Neural Comput., 4(1):84-97.
Paper Citation
in Harvard Style
Herrero-Carrón F., de Borja Rodríguez F. and Varona P. (2010). DYNAMICAL INVARIANTS FOR CPG CONTROL IN AUTONOMOUS ROBOTS . In Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-8425-01-0, pages 441-445. DOI: 10.5220/0003004304410445
in Bibtex Style
@conference{icinco10,
author={Fernando Herrero-Carrón and Francisco de Borja Rodríguez and Pablo Varona},
title={DYNAMICAL INVARIANTS FOR CPG CONTROL IN AUTONOMOUS ROBOTS},
booktitle={Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2010},
pages={441-445},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003004304410445},
isbn={978-989-8425-01-0},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 7th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - DYNAMICAL INVARIANTS FOR CPG CONTROL IN AUTONOMOUS ROBOTS
SN - 978-989-8425-01-0
AU - Herrero-Carrón F.
AU - de Borja Rodríguez F.
AU - Varona P.
PY - 2010
SP - 441
EP - 445
DO - 10.5220/0003004304410445