An analog CMOS central pattern generator for interlimb coordination in quadruped locomotion

This paper proposes a neuromorphic analog CMOS controller for interlimb coordination in quadruped locomotion. Animal locomotion, such as walking, running, swimming, and flying, is based on periodic rhythmic movements. These rhythmic movements are driven by the biological neural network, called the central pattern generator (CPG). In recent years, many researchers have applied CPG to locomotion controllers in robotics. However, most of these have been developed with digital processors and, thus, have several problems, such as high power consumption. In order to overcome such problems, a CPG controller with analog CMOS circuit is proposed. Since the CMOS transistors in the circuit operate in their subthreshold region and under low supply voltage, the controller can reduce power consumption. Moreover, low-cost production and miniaturization of controllers are expected. We have shown through computer simulation, such circuit has the capability to generate several periodic rhythmic patterns and transitions between their patterns promptly.

[1]  Zhiwei Luo,et al.  A mathematical model of adaptive behavior in quadruped locomotion , 1998, Biological Cybernetics.

[2]  Hiroshi Shimizu,et al.  Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment , 1991, Biological Cybernetics.

[3]  Kiyotoshi Matsuoka,et al.  Mechanisms of frequency and pattern control in the neural rhythm generators , 1987, Biological Cybernetics.

[4]  Jun Nishii,et al.  Legged insects select the optimal locomotor pattern based on the energetic cost , 2000, Biological Cybernetics.

[5]  Randall D. Beer,et al.  Evolution and Analysis of Model CPGs for Walking: II. General Principles and Individual Variability , 1999, Journal of Computational Neuroscience.

[6]  F. Delcomyn Neural basis of rhythmic behavior in animals. , 1980, Science.

[7]  Terri S. Fiez,et al.  Analog VLSI : signal and information processing , 1994 .

[8]  J. Cowan,et al.  Excitatory and inhibitory interactions in localized populations of model neurons. , 1972, Biophysical journal.

[9]  Michael A. Arbib,et al.  The handbook of brain theory and neural networks , 1995, A Bradford book.

[10]  S. Amari,et al.  Characteristics of Random Nets of Analog Neuron-Like Elements , 1972, IEEE Trans. Syst. Man Cybern..

[11]  H. Yuasa,et al.  Coordination of many oscillators and generation of locomotory patterns , 1990, Biological Cybernetics.

[12]  Ralph Etienne-Cummings,et al.  Control of a robot leg with an adaptive aVLSI CPG chip , 2001, Neurocomputing.

[13]  T. Brown On the nature of the fundamental activity of the nervous centres; together with an analysis of the conditioning of rhythmic activity in progression, and a theory of the evolution of function in the nervous system , 1914, The Journal of physiology.

[14]  Susanne Still,et al.  Controller for a Four-Legged Walking Machine , 1998 .

[15]  Shun-ichi Amari,et al.  Characteristics of Random Nets of Analog Neuron-Like Elements , 1988, IEEE Trans. Syst. Man Cybern..

[16]  Akio Ishiguro,et al.  Generation of an adaptive controller CPG for a quadruped robot with neuromodulation mechanism , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[17]  A. Dagg Gaits in mammals , 1973 .

[18]  Yasuhiro Fukuoka,et al.  Adaptive dynamic walking of a quadruped robot using a neural system model , 2001, Adv. Robotics.

[19]  F. Delcomyn Foundations of neurobiology , 1997 .

[20]  Aude Billard,et al.  Biologically inspired neural controllers for motor control in a quadruped robot , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

[21]  Jiang Shan Neural Locomotion Controller Design and Implementation for Humanoid Robot HOAP-1 ○ , 2022 .

[22]  Jeremy Holleman,et al.  Analog VLSI Model of Intersegmental Coordination with Nearest-Neighbor Coupling , 1997, NIPS.

[23]  S. Hooper Neural Circuits: Functional Reconfiguration , 2001 .