Minami Takato

Biomimetics Micro Robot with Active Hardware Neural Networks Locomotion Control and Insect-Like Switching Behaviour:

In this paper, we presented the 4.0, 2.7, 2.5 mm, width, length, height size biomimetics micro robot system which was inspired by insects. The micro robot system was made from silicon wafer fabricated by micro electro mechanical systems (MEMS) technology. The mechanical system of the robot was equipped with small size rotary type actuators, link mechanisms and six legs to realize the insect-like switching behaviour. In addition, we constructed the active hardware neural networks (HNN) by analogue CMOS circuits as a locomotion controlling system. The HNN utilized the pulse-type hardware neuron model (P-HNM) as a basic component. The HNN outputs the driving pulses using synchronization phenomena such as biological neural networks. The driving pulses can operate the actuators of the biomimetics micro robot directly. Therefore, the HNN realized the robot control without using any software programs or A/D converters. The micro robot emulated the locomotion method and the neural networks of an insect with rotary type actuators, link mechanisms and HNN. The micro robot performed forward and backward locomotion, and also changed direction by inputting an external trigger pulse. The locomotion speed was 26.4 mm/min when the step width was 0.88 mm.

A Millimetre-Sized Robot Realized by a Piezoelectric Impact-Type Rotary Actuator and a Hardware Neuron Model

Micro-robotic systems are increasingly used in medicine and other fields requiring precision engineering. This paper proposes a piezoelectric impact-type rotary actuator and applies it to a millimetre-size robot controlled by a hardware neuron model. The rotary actuator and robot are fabricated by micro-electro-mechanical systems (MEMS) technology. The actuator is composed of multilayer piezoelectric elements. The rotational motion of the rotor is generated by the impact head attached to the piezoelectric element. The millimetre-size robot is fitted with six legs, three on either side of the developed actuator, and can walk on uneven surfaces like an insect. The three leg parts on each side are connected by a linking mechanism. The control system is a hardware neuron model constructed from analogue electronic circuits that mimic the behaviour of biological neurons. The output signal ports of the controller are connected to the multilayer piezoelectric element. This robot system requires no specialized software programs or A/D converters. The rotation speed of the rotary actuator reaches 60 rpm at an applied neuron frequency of 25 kHz during the walking motion. The width, length and height of the robot are 4.0, 4.6 and 3.6 mm, respectively. The motion speed is 180 mm/min.

Miniaturized Rotary Actuators Using Shape Memory Alloy for Insect-Type MEMS Microrobot

Although several types of locomotive microrobots have been developed, most of them have difficulty locomoting on uneven surfaces. Thus, we have been focused on microrobots that can locomote using step patterns. We are studying insect-type microrobot systems. The locomotion of the microrobot is generated by rotational movements of the shape memory alloy-type rotary actuator. In addition, we have constructed artificial neural networks by using analog integrated circuit (IC) technology. The artificial neural networks can output the driving waveform without using software programs. The shape memory alloy-type rotary actuator and the artificial neural networks are constructed with silicon wafers; they can be integrated by using micro-electromechanical system (MEMS) technology. As a result, the MEMS microrobot system can locomote using step patterns. The insect-type MEMS microrobot system is 0.079 g in weight and less than 5.0 mm in size, and its locomotion speed is 2 mm/min. The locomotion speed is slow because the heat of the shape memory alloy conducts to the mechanical parts of the MEMS microrobot. In this paper, we discuss a new rotary actuator compared with the previous model and show the continuous rotation of the proposed rotary actuator.

Neural Networks Integrated Circuit for Biomimetics MEMS Microrobot

In this paper, we will propose the neural networks integrated circuit (NNIC) which is the driving waveform generator of the 4.0, 2.7, 2.5 mm, width, length, height in size biomimetics microelectromechanical systems (MEMS) microrobot. The microrobot was made from silicon wafer fabricated by micro fabrication technology. The mechanical system of the robot was equipped with small size rotary type actuators, link mechanisms and six legs to realize the ant-like switching behavior. The NNIC generates the driving waveform using synchronization phenomena such as biological neural networks. The driving waveform can operate the actuators of the MEMS microrobot directly. Therefore, the NNIC bare chip realizes the robot control without using any software programs or A/D converters. The microrobot performed forward and backward locomotion, and also changes direction by inputting an external single trigger pulse. The locomotion speed of the microrobot was 26.4 mm/min when the step width was 0.88 mm. The power consumption of the system was 250 mWh when the room temperature was 298 K.

Piezo impact type MEMS rotary actuator and application to millimeter size AI controlled robot

Microrobotic systems are increasingly used in medicine and other fields requiring precision engineering. This paper proposes a piezo impact-type rotary actuator and applies it to a millimeter-size robot controlled by an artificial intelligence (AI) system. The rotary actuator and robot are fabricated by micro electro mechanical systems (MEMS) technology using a silicon wafer. The actuator is composed of multilayer piezoelectric elements. The rotational motion of the rotor is generated by the impact head attached to the piezoelectric element. The millimeter-size robot is fitted with six legs on either side of the developed actuator, and can walk on uneven surfaces like an insect. The three leg parts are connected by a link mechanism. The control system is constructed from analog electronic circuits that mimic the behavior of biological neurons. The output signal ports of the controller are connected to the multilayer piezoelectric element. This robot system requires no specialized software programs or A/D converters. The rotation speed of the rotary actuator reaches 60 rpm at an applied AI frequency of 25 kHz. The sideways, endways, and height dimensions of the robot are 4.0, 4.6, and 3.6 mm, respectively. The motion speed is 180.0 mm/min.

Hexapod Type MEMS Microrobot Equipped with an Artificial Neural Networks IC

This paper proposes a hexapod type microrobot controlled by an artificial neural networks IC. The structural component of the microrobot is produced by micro electro mechanical systems (MEMS) process. The rotary actuator 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.

SMA actuator and pulse-type hardware neural networks IC for fast walking motion of insect-type MEMS microrobot

In this study, the actuator system and an integrated circuit (IC) neural network for a hexapod locomotive microrobot is discussed with the aim of achieving walking motion. Miniature size robots such as insects are a field of interest in robotic studies. However, the realization of such a small robot, especially with micro-mechanisms and an artificial brain, similar to those of real organisms, is difficult. We propose the use of micro-electro mechanical systems (MEMS) for the micro-mechanisms and pulse-type hardware neural networks for the brain of a microrobot. The silicon structural component was produced using MEMS. Shape memory alloy-based artificial muscle wires were used for the rotational actuator, and gait motion was generated using link mechanisms. We compared two types of rotors with different shapes and thermal capacities. By optimizing the design of the rotary actuator and the driving current, the robot exhibited faster and stable walking motion. Furthermore, we developed an IC for pulse-type hardware neural networks to act as an artificial brain for the gait controller and the bare chip was connected to the MEMS robot.

Development of quadruped robot with locomotion rhythm generator using pulse-type hardware neural networks

This paper discussed about development of quadruped robot which could perform the quadruped animal-like locomotion. Locomotion rhythm of the quadruped robot was generated using the pulse-type hardware neural networks (P-HNN). Quadruped robot had mechanical components and electrical components. The mechanical components of the quadruped robot consist of the body frame, link mechanisms, 4 legs and 4 servo motors to realize the quadruped animal-like locomotion. The body frame, link mechanisms and 4 legs were made from aluminum base alloy. The electrical components of the quadruped robot consist of control board, battery and P-HNN. P-HNN generates the locomotion rhythms using synchronization phenomena such as biological neural networks. The control board actuates the servo motors according to the generated locomotion rhythms. As a result, constructed quadruped robot could perform the quadruped animal-like locomotion using the generated locomotion rhythm, which was shown in this paper.

Multilayer ceramic coil for wireless power transfer system by photo resist film process

This paper proposes a multilayer ceramic coil for a wireless power transfer system that fabricated by a photo resist film process. The wireless power transfer technology has been focused as power supply of miniaturized communication devices because it is not required the connecting cable, and it is suitable to carry. Moreover, the electromagnetic induction type that is usually used is constructed by only coil structure for receiver. Therefore, it will be possible to conserve space inside the devices. Conventionally, the spiral structure coil is used for the transfer coil. However, the spiral coil is including problems such as a high internal resistance and consumption of large area. Moreover, the coil requires the magnetic material to catch the magnetic flux. Therefore, in this paper, the multilayer ceramic coil for the wireless power transfer system was proposed. The coil was fabricated by the multilayer ceramic technology which is used for miniaturized electric components. This technology has the advantage that it is possible to forming a helical structure and to use a magnetic material. In addition, the coil pattern is formed by the photo resist film process. In the conventional process, deformation of the conductive pattern by screen printing method was problem. The proposed process can be solved this problem because the conductive pattern was held by the resist film. In this paper, the rectangle conductive pattern in the cross-sectional was achieved. Moreover, the cross-sectional area was changed by the thickness of the resist film, and the coil pattern that has the cross-sectional pattern with 0.85 mm × 0.022 mm was achieved. In this pattern, the multilayer ceramic coil that has the internal resistance of 1 ohm was achieved. Therefore, the helical coil structure that has the magnetic core and low internal inductance was realized.

Hardware neural network models of CPG and PWM for controlling servomotor system in quadruped robot

This paper discusses the pulse-type hardware neural networks (P-HNNs) that contain a central pattern generator (CPG) and a pulsewidth modulation (PWM) servomotor controller and the application to quadruped robots. The purpose of our study is mimicking the biological neural networks and reproducing the similar motion of the living organisms in the robot. The CPG of the living organism generates the walking rhythms. We mimicked this CPG by modeling the cell body and the synapse of the living organism. The developed CPG composed of the P-HNN output four pulse signal sequences and the four outputs are introduced to each leg of the quadruped robot. On the other hand, the angle of the servomotor is controlled by the PWM. The PWM is obtained by modeling the axon of the living organism. The CPG and the PWM servo control system perform the walking motion of the quadruped robot. Moreover, the gate pattern change of quadruped animals is reproduced by these P-HNNs.