Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 28–31___________________________________________________________________________________________________________Hexapod Type MEMS Microrobot Equipped with an Artificial Neural Networks ICKazuki Sugita

Graduate School of Precision Machinery Engineering College of Science and Technology, Nihon University,
7-24-1, Narashinodai, Funabashi, Chiba, 274-8501, Japan
Taisuke Tanaka, Yuya Nakata, Minami Takato, Ken Saito, Fumio Uchikoba

Department of Precision Machinery Engineering College of Science and Technology, Nihon University,
7-24-1, Narashinodai, Funabashi, Chiba, 274-8501, Japan
E-mail: cska15018@g.nihon-u.ac.jp, takato@eme.cst.nihon-u.ac.jp, kensaito@eme.cst.nihon-u.ac.jp,
uchikoba@eme.cst.nihon-u.ac.jp

Abstract
This paper proposes a hexapod type microrobot controlled by an artificial neural networks IC. The structuralcomponent of the microrobot is produced by micro electro mechanical systems (MEMS) process. The rotaryactuator inside the robot is composed of the artificial muscle wire of shape memory alloy (SMA) material. The
artificial neural networks IC includes cell body models, inhibitory synaptic models and current mirror circuits. By
reducing the heat capacity of the actuator and the length of electrical wire to the actuator, the walking speed
achieved 12 mm/min.
Keywords: Microrobot, MEMS, Artificial neural networks, SMA, Artificial muscle wire

production process, which applies photolithography ona silicon wafer.
Some studies have considered artificial neuralnetworks as a new alternative control method forrobots.4 The study of the artificial neural networks isroughly divided into software models and hardware
models. The software model is a numerical simulation
method using a computer system. To achieve thefabrication of large-scale neural networks using
software models, processing in continuous time isdifficult. The hardware model is imitating the neuralnetworks using electronic circuits. The nonlinear
operation of an electronic circuit can be performed at ahigh speed and processed in continuous time. Therefore,
the hardware neural networks can obtain an output inreal time, even if the circuits scale increases.
Previously, we developed the microrobot that
imitates the hexapod walking motion of insects using

1. Introduction
Several studies have reported the miniaturization ofrobots.1-2 Microrobots are suggesting possibility ofactivities in a small space. However, the miniaturizationand high functionalization of microrobots have not been
sufficiently achieved yet.
In heading toward the implementation of moresophisticated microrobots, biomimetics, a technologythat imitates living organisms, is attracting attention.3
Insects have the compact walking mechanisms and theexcellent flexible control systems using biologicalneural networks. Hence, the realization of small walking
systems with the size of an insect is valuable. However,the processing of the miniature component as small as
the insect is difficult only by the conventional
mechanical machining. One of the solutions is microelectro mechanical systems (MEMS). The MEMS
process is based on the integrated circuit (IC)Copyright © 2017, the Authors. Published by Atlantis Press.
This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 28–31___________________________________________________________________________________________________________type rotor is expected for faster revolving cycle because
new design can suppress the heat capacity. Also, we
installed the lead wire inside the microrobot to reduce
the harmful element of the weight balance.

MEMS technology. We fabricated small walking
systems equipped with the actuator using artificial
muscle wires based on shape memory alloy (SMA). The
lead wires electrically connecting the microrobot andartificial neural networks IC were exposed outside themicrorobot. This wire connection was harmful for therobot balance. This microrobot walked at a locomotion
speed of 2.8 mm/min.
In this study, we report that the faster walking
motion of the hexapod-type MEMS microrobot. The
miniaturization of rotor parts was performed to reduce
its heat capacity. The electrical wires were leaded inside
the microrobot. It improved the weight balance of themicrorobot. As a result, the microrobot could achieve
the walking speed at 12 mm/min.

2.5 mm
4.0 mm

2.7 mmFig. 1. Hexapod type microrobot.

2. Mechanism of the MEMS Microrobot

Rotor

The microrobot that we manufactured is shown in Fig.
1. The microrobot is a hexapod walking robot with a
total length of 5 mm or less. The components of themicrorobot are the frame, the rotary actuator, the shaft,and six legs. The each part is fabricated from siliconwafers using MEMS process. We used link mechanism
and the artificial muscle wire to achieve the further
advanced miniaturization required for a small walking
system. As the material of the artificial muscle wire
itself has the function of generating the displacement,
this is suitable for the miniaturization of the microrobot.
Artificial muscle wires and a ground (GND) wire
are electrically and mechanically connected to the rotor
part through the silver conductive paste. The
displacement of the artificial muscle wires changed bysuccessively applying an electrical current to generatejoule heat. Previously, we applied a circle-type rotor forthe rotary actuator as shown in Fig. 2 (a). This circletype rotor was completely over-coated with the silver
conductive paste. On the contrary, the two-hole-typerotor in this paper can fix the artificial muscle wire
firmly by the hole. So, the amount reduction of thesilver conductive paste was achieved (see Fig. 2 (b)).
We compared the heat capacity calculated based on
the weight of two-type rotors. The weight of siliconparts of the circle-type rotor and two-hole-type rotor
were 52.4 μg and 18.1 μg, respectively. The weight ofsilver conductive paste were 1.18 mg and 139 μg,respectively.
In terms of the two-type-rotors, the calculated heat
capacity is shown in Table 1. As a result, the two-hole-

Lead wires

200 µmFrames0.22 mm0.61 mm0.94 mm 0.3 mm

1.2 mm(a)(b)

Fig. 2. Structure of the microrobot.
Table 1. Heat capacity of two-type rotors

Heat capacity ofrotor part [μJ/K]
Heat capacity of
conductive paste[μJ/K]

Circle-typerotor

Two-hole-typerotor

38.8

13.4

277

32.7

2.1. Walking mechanism
We employed a link mechanism that converts the rotary
motion of the actuator to walking motion. The linkmechanism connects the middle leg to the front and rearlegs. The locomotion pattern generates a 180° phase29

Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 28–31___________________________________________________________________________________________________________shift on each side. Therefore, the microrobot performs ahexapod walking by grounding the three legs like aninsect (see Fig. 3).

iSCG
MC3MC4VC

MC2CM

MC1VAFig. 4. Circuit diagram of the cell body model.
CIS1
MIS12VDD
MIS13Fig. 3. Locomotion diagrams of the microrobot.

3.

VC1

Artificial Neural Networks

The neural networks present in their brains consist ofcell bodies, dendrites, axons and synapses. The cellbody fires electrical pulses by changing the membranepotential. The signals for electrical pulses aretransmitted to the dendrites of another neuron throughthe axon. The synapses change signals for electricalpulses by inhibit or promote transmitting of electricalpulses.
In this study, we modeled the cell body and theinhibitory synapse as shown in the Fig. 4 and Fig. 5.
The cell body model has a refractory period, an analog
characteristic for the output pulse, and time varying
negative resistance characteristics. The circuit
parameters for the cell body model were VA = 2.8 V,
MC1, MC2: W/L = 10, MC3: W/L = 0.1, MC4: W/L = 0.3,
CG = 4.7μF, CM = 1.0μF. A cell body model connectedby an inhibitory synaptic model causes anti-phasesynchronization. The circuit parameters for theinhibitory synaptic model were VISDD = 2.8 V, CIS = 1
pF, MIS1, MIS2, MIS3, MIS11, MIS12: W/L = 1.
We used the four cell body models that coupledinhibitory mutually using 12 inhibitory synaptic models
as shown in the Fig. 6. The artificial neural networks
and the current mirror circuit for obtaining a driving
current of the actuator were constructed on an IC. The
layout pattern of the IC is shown in Fig. 7. The design
rule of the IC was 4 metal 2 poly CMOS 0.35 μm. The
chip size was 2.45 mm square.

MIS11MIS2MIS3iS

Fig. 5. Circuit diagram of the inhibitory synaptic model.
Output ports

Input ports: Cell body model: Synaptic modelFig. 6. Connection diagram of the artificial neural networks.

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Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 28–31___________________________________________________________________________________________________________

Artificial neural networks

Current mirror circuit

2.45 mm

2.45 mmFig. 7. Layout pattern of the artificial neural networks IC.

3s

6s

9s

Fig. 9. Walking locomotion of the microrobot.

4. Results

5. Conclusion

Fig. 8(a), (b) shows the microrobots equipped theartificial neural networks IC. The side, the end, andheight dimensions of the microrobot include the wholecircuit were 4.0, 2.7, and 5.0 mm, respectively. Only
power sources were connected externally. While theprevious microrobot had lead wires outside themicrorobot, in this case, we installed the lead wire
inside the microrobot. As a result, the internal wiring
achieved excellent weight balance and structurally
stable performance of the microrobot.
The hexapod walking locomotion of the microrobot
was achieved as shown in fig. 9. Previously, the input
pulse duration was a 0.5 s, and cycle period was 2.0 s.
The new two-hole-type rotor was possible to accelerate
the revolving frequency of the actuator. Therefore, wecould shorten the input pulse width and cycle period to
0.3 s and 1.2 s, respectively, and consequently increased
the rotation speed of the rotary actuator. The locomotion
speed of the microrobot accelerated from 2.8 mm/min to
12 mm/min.

In this study, we proposed the hexapod type MEMS
microrobot controlled by the artificial neural networks
IC. We designed two type actuators using artificial
muscle wires. The new two-hole-type rotor was possible
to reduce the thermal capacity of the rotor by reducing
the size and the amount of the conductive paste. The
new microrobot had lead wires inside of the microrobot,
and achieved the better weight balance. It was possible
to mount a driving circuit on the microrobot by using abare chip IC. As a result, the speed of the hexapod typemicrorobot increased to 12 mm/min. The microrobot
equipped all of constituent elements except the powersource. In the future works, we will develop internal
power source system.
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Hattori, Microwave Energy Transmission System forMicro-robot, IEICE Trans. ELECTRON. E80-C(2)(1997) 303–308.
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3. A. T. Baisch, P. S. Sreetharan and R. J. Wood, E. H.
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robot, in Proc. Int. Conf. on Intelligent Robots andsystems, (2010), pp. 5360–5365.
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Mobile robot control using combined neural-fuzzy andneural network, in Proc. 12th IEEE Int. Symposium on
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351–356.

5.0 mm(a) Previous robot
with outside wire0s

4.0 mm
2.7 mm(b) Present robot
with inside wire

Fig. 8. Fabricated microrobot equipped driving circuit.

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