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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 11/2017

16.03.2016 | Original Article

Prescription of rhythmic patterns for legged locomotion

verfasst von: Zhijun Yang, Daqiang Zhang, Marlon V. Rocha, Priscila M. V. Lima, Mehmet Karamanoglu, Felipe M. G. França

Erschienen in: Neural Computing and Applications | Ausgabe 11/2017

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Abstract

As the engine behind many life phenomena, motor information generated by the central nervous system plays a critical role in the activities of all animals. In this work, a novel, macroscopic and model-independent approach is presented for creating different patterns of coupled neural oscillations observed in biological central pattern generators (CPG) during the control of legged locomotion. Based on a simple distributed state machine, which consists of two nodes sharing pre-defined number of resources, the concept of oscillatory building blocks (OBBs) is summarised for the production of elaborated rhythmic patterns. Various types of OBBs can be designed to construct a motion joint of one degree of freedom with adjustable oscillatory frequencies and duty cycles. An OBB network can thus be potentially built to generate a full range of locomotion patterns of a legged animal with controlled transitions between different rhythmic patterns. It is shown that gait pattern transition can be achieved by simply changing a single parameter of an OBB module. Essentially, this simple mechanism allows for the consolidation of a methodology for the construction of artificial CPG architectures behaving as an asymmetric Hopfield neural network. Moreover, the proposed CPG model introduced here is amenable to analogue and/or digital circuit integration.
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Literatur
1.
Büschges A (2005) Sensory control and organization of neural networks mediating coordination of multisegmental organs for locomotion. J Neurophysiol 93(3):1127–1135CrossRef
2.
Grillner S (2006) Biological pattern generation: the cellular and computational logic of networks in motion. Neuron 52:751–766CrossRef
3.
Cruse H, Dürr V, Schilling M, Schmitz J (2009) Principles of insect locomotion. In: Arena P, Patanè L (eds) Spatial temporal patterns for action-oriented perception in roving robots, cognitive systems monographs. Springer, Berlin, pp 43–96CrossRef
4.
5.
Fuchs E, Holmes P, Kiemel T, Ayali A (2011) Inersegmental coordination of cockroach locomotion: adaptive control of centrally coupled pattern generator circuits. Front Neural Circuits 4:125. doi:10.​3389/​fncir.​2010.​00125
6.
Grillner S (1975) Locomotion in vertebrates: central mechanisms and reflex interaction. Physiol Rev 55:247–304
7.
Grillner S (1985) Neurobiological bases of rhythmic motor acts in vertebrates. Science 228:143–149CrossRef
8.
Stein PSG (1978) Motor systems with specific reference to the control of locomotion. Annu Rev Neurosci 1:61–81CrossRef
9.
Schöner G, Kelso JA (1988) Dynamic pattern generation in behavioural and neural systems. Science 239:1513–1520CrossRef
10.
Alexander RM (1989) Optimization and gaits in the locomotion of vertebrates. Physiol Rev 69:1199–1227
11.
Cohen AH (1992) The role of heterarchical control in the evolution of central pattern generators. Brain Behav Evol 40:112–124CrossRef
12.
Pearson KG (1993) Common principles of motor control in vertebrates and invertebrates. Annu Rev Neurosci 16:265–297CrossRef
13.
Latash ML (1993) Control of human movement. Human Kinetics Publishers, Champaign
14.
McGeer T (1993) Dynamics and control of bipedal locomotion. J Theor Biol 163:277–314CrossRef
15.
Ryckebusch S, Wehr M, Laurent G (1994) Distinct rhythmic locomotor patterns can be generated by a simple adaptive neural circuit: biology, simulation, and VLSI implementation. J Comput Neurosci 1(4):339–358CrossRef
16.
Kiehn O, Butt SJ (2003) Physiological, anatomical and genetic identification of CPG neurons in the developing mammalian spinal cord. Prog Neurobiol 70:347–361CrossRef
17.
Marder E, Calabrese RL (1996) Principles of rhythmic motor pattern generation. Physiol Rev 76:687–717
18.
Stein PSG, Grillner S, Selverston AI, Stuart DG (eds) (1997) Neurons, networks, and motor behavior. MIT Press, Cambridge
19.
Schmidt RA, Lee TD (1999) Motor control and learning: a behavioral emphasis. Human Kinetics Publishers, Champaign
20.
Pearson K, Gordon J (2000) Locomotion. In: Kandel E, Schwartz J, Jessel T (eds) Principles of neural science. McGraw-Hill Companies Inc, New York, pp 737–755
21.
Magill RA (2001) Motor learning: concepts and applications. McGraw-Hill Companies Inc, New York
22.
Grillner S (2003) The motor infrastructure: from ion channels to neuronal networks. Nat Rev Neurosci 4:573–586CrossRef
23.
Jing J, Cropper EC, Hurwitz I, Weiss KR (2004) The construction of movement with behavior-specific and behavior-independent modules. J Neurosci 24:6315–6325CrossRef
24.
Grillner S, Markram H, De Schutter E, Silberberg G, LeBeau FE (2005) Microcircuits in action—from CPGs to neocortex. Trends Neurosci 28:525–533CrossRef
25.
Norris BJ, Weaver AL, Morris LG, Wenning A, García PA, Calabrese RL (2006) A central pattern generator producing alternative outputs: temporal pattern of premotor activity. J Neurophysiol 96:309–326CrossRef
26.
Wang XJ, Rinzel J (1992) Alternating and synchronous rhythms in reciprocally inhibitory model neurons. Neural Comput 4:84–97CrossRef
27.
Hatsopoulos N (1996) Coupling the neural and physical dynamics in rhythmic movements. Neural Comput 8:567–581CrossRef
28.
Rinzel J, Terman D, Wang X, Ermentrout B (1998) Propagating activity patterns in large-scale inhibitory neuronal networks. Science 279:1351–1355CrossRef
29.
Ermentrout GB, Chow CC (2002) Modeling neural oscillations. Physiol Behav 77:629–633CrossRef
30.
Ghigliazza RM, Holmes P (2004) A minimal model of a central pattern generator and motoneurons for insect locomotion. SIAM J Appl Dyn Syst 3(4):671–700MathSciNetCrossRefMATH
31.
Katz PS, Sakurai A, Clemens S, Davis D (2004) Cycle period of a network oscillator is independent of membrane potential and spiking activity in individual central pattern generator neurons. J Neurophysiol 92:1904–1917CrossRef
32.
Marder E, Bucher D, Schulz DJ, Taylor AL (2005) Invertebrate central pattern generation moves along. Curr Biol 15:R685–R699CrossRef
33.
Jones SR, Kopell N (2006) Local network parameters can affect inter-network phase lags in central pattern generators. J Math Biol 52(1):115–140MathSciNetCrossRefMATH
34.
Daun-Gruhn S, Büschges A (2011) From neuron to behavior: dynamic equation-based prediction of biological processes in motor control. Biol Cybern 105:71–88CrossRef
35.
Olree KS, Vaughan CL (1995) Fundamental patterns of bilateral muscle activity in human locomotion. Biol Cybern 73(5):409–414CrossRef
36.
Prentice SD, Patla AE, Stacey DA (1998) Simple artificial neural network models can generate basic muscle activity patterns for human locomotion at different speeds. Exp Brain Res 123(4):474–480CrossRef
37.
Delcomyn F (1999) Walking robots and the central and peripheral control of locomotion in insects. Auton Robots 7(3):259–270CrossRef
38.
Ijspeert AJ, Kodjabachian J (1999) Evolution and development of a central pattern generator for the swimming of a Lamprey. Artif Life 5(3):247–269CrossRef
39.
Ijspeert AJ (2001) A connectionist central pattern generator for the aquatic and terrestrial gaits of a simulated salamander. Biol Cybern 84(5):331–348MathSciNetCrossRef
40.
McCrea DA (2001) Spinal circuitry of sensorimotor control of locomotion. J Physiol 533(1):41–50CrossRef
41.
Butt SJ, Kiehn O (2003) Functional identification of interneurons responsible for left-right coordination of hindlimbs in mammals. Neuron 38:953–963CrossRef
42.
Cangiano L, Grillner S (2005) Mechanisms of rhythm generation in a spinal locomotor network deprived of crossed connections: the lamprey hemicord. J Neurosci 25:923–935CrossRef
43.
Stein PSG (2005) Neuronal control of turtle hindlimb motor rhythms. J Comp Physiol A 191(3):213–229CrossRef
44.
Bucher D, Prinz AA, Marder E (2005) Animal-to-animal variability in motor pattern production in adults and during growth. J Neurosci 25:1611–1619CrossRef
45.
46.
Raibert MH (1986) Legged robots that balance. MIT Press, CambridgeMATH
47.
Arena P (2000) The central pattern generator: a paradigm for artificial locomotion. Soft Comput 4(4):251–266CrossRefMATH
48.
49.
Webb B (2002) Robots in invertebrate neuroscience. Nature 417:359–363CrossRef
50.
51.
Nusbaum MP, Beenhakker MP (2002) A small-systems approach to motor pattern generation. Nature 417:343–350CrossRef
52.
Lewis MA, Etienne-Cummings R, Hartmann MJ, Xu ZR, Cohen AH (2003) An in silico central pattern generator: silicon oscillator, coupling, entrainment, and physical computation. Biol Cybern 88(2):137–151CrossRefMATH
53.
Nakada K, Asai T, Amemiya Y (2003) An analog CMOS central pattern generator for interlimb coordination in quadruped. IEEE Trans Neural Netw 14(5):1356–1365CrossRef
54.
Still S, Hepp K, Douglas RJ (2006) Neuromorphic walking gait control. IEEE Trans Neural Netw 17(2):496–508CrossRef
55.
Vogelstein RJ, Tenore F, Etienne-Cummings R, Lewis MA, Cohen AH (2006) Dynamic control of the central pattern generator for locomotion. Biol Cybern 95(6):555–566CrossRefMATH
56.
Zhang X, Zheng H, Chen L (2006) Gait transition for a quadrupedal robot by replacing the gait matrix of a central pattern generator model. Adv Robot 20(7):849–866CrossRef
57.
Yang Z, Huo J, Monteiro H, Murray A (2009). Sensor-driven neuromorphic walking leg control. In: IEEE international symposium on circuits and systems (ISCAS), pp 2137–2140
58.
Yang Z, Cameron K, Lewinger W, Webb B, Murray AF (2012) Neuromorphic control of stepping pattern generation: a dynamic model with analog circuit implementation. IEEE Trans Neural Net Learn Syst 23(3):373–384CrossRef
59.
Twickel AV, Hild M, Siedel T, Patel V, Pasemann F (2012) Neural control of a modular multi-legged walking machine: simulation and hardware. Robotics Auton Syst 60(2):227–241CrossRef
60.
Barron-Zambrano JH, Torres-Huitzil C (2013) FPGA implementation of a configurable neuromorphic CPG-based locomotion controller. Neural Netw 45:50–61CrossRef
61.
Harris-Warrick RM (2011) Neuromodulation and flexibility in central pattern generator networks. Curr Opin Neurobiol 21:1–8CrossRef
62.
Bay JS, Hemami H (1987) Modeling of a neural pattern generator with coupled nonlinear oscillators. IEEE Trans Biomed Eng 34:297–306CrossRef
63.
Linkens DA, Taylor Y, Duthie HL (1976) Mathematical modeling of the colorectal myoelectrical activity in humans. IEEE Trans Biomed Eng 23:101–110CrossRef
64.
Tsutsumi K, Matsumoto H (1984) A synaptic modification algorithm in consideration of the generation of rhythmic oscillation in a ring neural network. Biol Cybern 50:419–430CrossRef
65.
Taga G, Yamaguchi Y, Shimizu H (1991) Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment. Biol Cybern 65:147–159CrossRefMATH
66.
Taga G (1995) A model of the neuro-musculo-skeletal system for human locomotion—I. Emergence of basic gait. Biol Cybern 73:97–111CrossRefMATH
67.
68.
Schöner G, Jiang WY, Kelso JAS (1990) A synergetic theory of quadrupedal gaits and gait transitions. J Theor Biol 142:359–391CrossRef
69.
Collins JJ, Richmond SA (1994) Hard-wired central pattern generators for quadrupedal locomotion. Biol Cybern 71:375–385CrossRefMATH
70.
71.
Kimura H, Fukuoka Y, Cohen AH (2007) Adaptive dynamic walking of a quadruped robot on natural ground based on biological concepts. Int J Robot Res 26:475–490CrossRef
72.
Collins JJ (1995) Gait transitions. In: Arbib MA (ed) The handbook of brain theory and neural networks. The MIT Press, New York, pp 420–423
73.
Yang Z, França FMG (1998) Generating arbitrary rhythmic patterns with purely inhibitory neural networks. In: Proceedings of European symposium on artificial neural networks (ESANN), pp 53–58
74.
França FMG, Yang Z (2000) Building artificial CPGs with asymmetric Hopfield networks. In: Proceedings of international joint conference on neural networks, Como, Italy, vol IV, pp 290–295
75.
Yang Z, França FMG (2003) A generalized locomotion CPG architecture based on oscillatory building blocks. Biol Cybern 89(1):34–42MATH
76.
Barbosa VC, Gafni E (1989) Concurrency in heavily loaded neighbourhood-constrained systems. ACM Trans Program Lang Syst 11(4):562–584CrossRef
77.
Barbosa VC (1996) An introduction to distributed algorithms. The MIT Press, Cambridge
78.
França FMG (1994) Neural networks as neighbourhood-constrained systems, unpublished doctoral dissertation. Imperial College, London
79.
80.
Kuffler SW, Eyzaguirre C (1955) Synaptic inhibition in an isolated nerve cell. J Gen Physiol 39:155–184CrossRef
81.
Perkel DH (1976) A computer program for simulating a network of interacting neurons: I. Organization and physiological assumptions. Comput Biomed Res 9:31–43CrossRef
82.
Roberts A, Tunstall MJ (1990) Mutual re-excitation with post-inhibitory rebound: a simulation study on the mechanisms for locomotor rhythm generation in the spinal cord of Xenopus embryos. Eur J Neurosci 2:11–23CrossRef
83.
Hopfield JJ (1982) Neural networks and physical systems with emergent collective properties. Proc Natl Acad Sci USA 79:2554–2558MathSciNetCrossRefMATH
84.
Hopfield JJ, Tank DW (1986) Computing with neural circuits: a model. Science 233:625–632CrossRefMATH
85.
Hopfield JJ, Tank DW (1985) Neural computation of decisions in optimization problems. Biol Cybern 52:141–152MATH
86.
Chen W, Ren G, Zhang J, Wang J (2012) Smooth transition between different gaits of a hexapod robot via a central pattern generators algorithm. J Intell Robot Syst 67:255–270CrossRefMATH
87.
Getting PA (1989) Emerging principles governing the operation of neural networks. Annu Rev Neurosci 12:185–204CrossRef
88.
Soffe SR, Roberts A, Li WC (2009) Defining the excitatory neurons that drive the locomotor rhythm in a simple vertebrate: insights into the origin of reticulospinal control. J Physiol 587(20):4829–4844CrossRef
89.
90.
91.
92.
Patrick SK, Noah JA, Yang JF (2009) Interlimb coordination in human crawling reveals similarities in development and neural control with quadrupeds. J Neurophysiol 101(2):603–613CrossRef
93.
Ivanenko YP, Labini FS, Cappellini G et al (2011) Gait transition in simulated reduced gravity. J Appl Physiol 110:781–788CrossRef
94.
Hückesfeld S, Schoofs A, Schlegel P, Miroschnikow A, Pankratz MJ (2015) Localization of motor neurons and central pattern generators for motor patterns underlying feeding behavior in Drosophila Larvae. PLoS One 10(8):e0135011. doi:10.​1371/​journal.​pone.​0135011 CrossRef
95.
Yu J, Tan M, Chen J, Zhang J (2014) A survey on CPG-Inspired control models and system implementation. IEEE Trans Neural Netw Learn Syst 25(3):441–456CrossRef
96.
Wang T, Guo W, Li M et al (2012) CPG control for biped hopping robot in unpredictable environment. J Bionic Eng 9(1):29–38CrossRef
97.
Liu C, Chen Q, Wang D (2011) CPG-inspired workspace trajectory generation and adaptive locomotion control for quadruped robots. IEEE Trans Syst Man Cybern B Cybern 41(3):867–880CrossRef
98.
Aoi S, Egi Y, Sugimoto R, Yamashita T et al (2012) Functional roles of phase resetting in the gait transition of a biped robot from quadrupedal to bipedal locomotion. IEEE Trans Robot 28(6):1244–1259CrossRef
99.
Ajallooeian M, Kieboom JVD, Mukovskiy A et al (2013) A general family of morphed nonlinear phase oscillators with arbitrary limit cycle shape. Phys D 263(15):41–56MathSciNetCrossRefMATH
100.
101.
Li F, Basu A, Chang C-H, Cohen AH (2012) Dynamical systems guided design and analysis of silicon oscillators for central pattern generators. IEEE Trans Circuits Syst I Reg Pap 59(12):3046–3059MathSciNetCrossRef
102.
Zhao L, Nogaret A (2014) Stimulus-dependent polyrhythms of central pattern generator hardware. Int J Math Comput Phys Quantum Eng 8(5):721–724
Metadaten
Titel
Prescription of rhythmic patterns for legged locomotion
verfasst von
Zhijun Yang
Daqiang Zhang
Marlon V. Rocha
Priscila M. V. Lima
Mehmet Karamanoglu
Felipe M. G. França
Publikationsdatum
16.03.2016
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 11/2017
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-016-2237-4

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