Title :
A study on CPG model transition swing and stance pattern with interstitial cells
Author :
Saeki, Kota ; Tatebe, T. ; Sekine, Yasuhito
Author_Institution :
Dept. of Electron. & Comput. Sci., Nihon Univ., Funabashi, Japan
Abstract :
It is known that quadruped locomotion patterns are generated by CPG (Central Pattern Generator) with interstitial cells in the central nervous system. Therefore, many investigators study the control adaptations of robots using CPG models. Previously, we proposed a CPG model to generate and control quadruped locomotion by giving external inputs of one pulse to CPG model. Moreover, the previous model was necessary to use large amount of capacitance as μF order for generating about 1-10[Hz] rhythm pattern to control robot. In this paper, we suggest a CPG model generating swing and stance patterns with interstitial cells by HSPICE. Furthermore, we investigate the design of an integrated circuit by 0.18μm process rule for generating low frequency rhythm patterns using a low amount of capacitance. As a result, it is shown that the proposed CPG model using interstitial cells model configured less than 10-4 amount of capacitance compared with the previous model. It is able to transit each locomotion swing and stance pattern by controlling synaptic connection. In addition, it is shown that the layout pattern area of the proposed CPG model configured as eight interstitial cells is able to be designed in one chip.
Keywords :
SPICE; biomedical electronics; cellular biophysics; integrated circuit design; legged locomotion; medical robotics; motion control; CPG model generating swing; CPG model transition swing; HSPICE; capacitance; central nervous system; central pattern generator; control adaptation; integrated circuit design; interstitial cells; layout pattern area; low frequency rhythm pattern; quadruped locomotion pattern; robot control; size 0.18 mum; stance pattern; synaptic connection; Capacitance; Integrated circuit modeling; Legged locomotion; Neurons; Oscillators; Radio frequency; Semiconductor device modeling;
Conference_Titel :
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1488-6
Electronic_ISBN :
2161-4393
DOI :
10.1109/IJCNN.2012.6252387