• DocumentCode
    3496246
  • Title

    Pulse-Type Hardware Inhibitory Neural Networks for MEMS micro robot using CMOS technology

  • Author

    Saito, Ken ; Okazaki, Kazuto ; Sakata, Kentaro ; Ogiwara, Tatsuya ; Sekine, Yoshifumi ; Uchikoba, Fumio

  • Author_Institution
    Dept. of Precision Machinery Eng., Nihon Univ., Chiba, Japan
  • fYear
    2011
  • fDate
    July 31 2011-Aug. 5 2011
  • Firstpage
    1606
  • Lastpage
    1611
  • Abstract
    This paper presents the locomotion generator of MEMS (Micro Electro Mechanical Systems) micro robot. The locomotion generator demonstrates the locomotion of the micro robot, controlled by the P-HINN (Pulse-Type Hardware Inhibitory Neural Networks). P-HINN generates oscillatory patterns of electrical activity such as living organisms. Basic components are the cell body models and inhibitory synaptic models. P-HINN has the same basic features of biological neurons such as threshold, refractory period, spatio-temporal summation characteristics and enables the generation of continuous action potentials. P-HINN was constructed by MOSFETs, can be integrated by CMOS technology. Same as the living organisms P-HINN realized the robot control without using any software programs, or A/D converters. The size of the micro robot fabricated by the MEMS technology was 4×4×3.5 mm. The frame of the robot was made of silicon wafer, equipped with the rotary type actuators, the link mechanisms and 6 legs. The MEMS micro robot emulated the locomotion method and the neural networks of the insect by the rotary type actuators, link mechanisms and P-HINN. As a result, we show that P-HINN can control the forward and backward locomotion of fabricated MEMS micro robot, and also switched the direction by inputting the external trigger pulse. The locomotion speed was 19.5 mm/min and the step width was 1.3 mm.
  • Keywords
    CMOS integrated circuits; actuators; microrobots; motion control; neurocontrollers; CMOS technology; MEMS microrobot; biological neuron; cell body model; complementary metal oxide semiconductor; inhibitory synaptic model; link mechanism; locomotion method; microelectromechanical system; neuron refractory period feature; neuron spatio-temporal summation characteristics; neuron threshold feature; pulse-type hardware inhibitory neural networks; rotary type actuators; Actuators; Biological system modeling; Integrated circuit modeling; Micromechanical devices; Neurons; Robots; Semiconductor device modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), The 2011 International Joint Conference on
  • Conference_Location
    San Jose, CA
  • ISSN
    2161-4393
  • Print_ISBN
    978-1-4244-9635-8
  • Type

    conf

  • DOI
    10.1109/IJCNN.2011.6033416
  • Filename
    6033416