Coordination of many oscillators and generation of locomotory patterns

Abstract

This paper considers a synthesis approach to a decentralized autonomous system in which the functional order of the entire system is generated by cooperative interaction among its subsystems, each of which has the autonomy to control a part of the state of the system, and its application to pattern generators of animal locomotion. First, biological locomotory rhythms and their generators, swimming patterns of aquatic animals and gait patterns of quadrupeds, are reviewed briefly. Then, a design principle for autonomous coordination of many oscillators is proposed. Using these results, we synthesize a swimming pattern generator and a gait pattern generator. Finally, it is shown using computer simulations that the proposed systems generate desirable patterns.

Simple robot suggests physical interlimb communication is essential for quadruped walking

“…There is currently no systematic methodology for designing a CPG controller; each individual CPG model has been designed on a completely ad hoc basis by focusing, in particular, on the interlimb neural connections in the CPG [11][12][13][14][15][16][17][18][19][20][21][22]. To establish a design methodology, we have reworked the design principle of CPG-based control [28,29].…”

Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment

“…Furthermore, rhythmic motor patterns are coordinated by neural circuits referred to as central pattern generators (Grillner 1975(Grillner , 1985Selverston 1985 for review). This has inspired theoretical studies of motor pattern generation in isolated neural networks in the absence of sensory feedback (Miller and Scott 1977;Friesen and Stent 1977;Kawahara and Mori 1982;Matsuoka 1985Matsuoka , 1987Kleinfeld and Sompolinsky 1988;Yuasa and Ito 1990). On the other hand, neurophysiological studies of insect locomotion suggest that sensory feedback is involved in patterning motor activity and that it is more than the modulation of the centrally generated pattern (B/issler 1986;Pearson 1987).…”

Biologically Inspired Approaches to Advanced Information Technology

“…The choice of the subsystem in form of simple oscillators [1,3,19], and more specifically phase oscillators [20,21] has been presented before. However, we motivate our choice with concepts from physics of complex systems rather then base the model on simplified cell models.…”

“…Models of different complexity and based on different assumptions have been devised that can produce the abstract gait patterns [1,3,[19][20][21]. One important approach is -motivated by the oscillatory limb movements -to use the most simple mathematical model that produces stable oscillatory behavior as gait pattern generator for one limb.…”

“…Except [20,21] most previous models use nonlinear oscillators that are motivated by neuronal circuits and that have therefore limit cycles with irregular shapes. In this contribution, the point is made to use the simplest oscillators possible as canonical subsystems, in order to have systems that are well understood and are simpler to treat analytically.…”