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
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