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
Link To Document :
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