Chapters authored
Gait Generation of Multilegged Robots by using Hardware Artificial Neural Networks
Living organisms can act autonomously because biological neural networks process the environmental information in continuous time. Therefore, living organisms have inspired many applications of autonomous control to small-sized robots. In this chapter, a small-sized robot is controlled by a hardware artificial neural network (ANN) without software programs. Previously, the authors constructed a multilegged walking robot. The link mechanism of the limbs was designed to reduce the number of actuators. The current paper describes the basic characteristics of hardware ANNs that generate the gait for multilegged robots. The pulses emitted by the hardware ANN generate oscillating patterns of electrical activity. The pulse-type hardware ANN model has the basic features of a class II neuron model, which behaves like a resonator. Thus, gait generation by the hardware ANNs mimics the synchronization phenomena in biological neural networks. Consequently, our constructed hardware ANNs can generate multilegged robot gaits without requiring software programs.
Part of the book: Advanced Applications for Artificial Neural Networks
Powder Process with Photoresist for Ceramic Electronic Components
This chapter proposed a patterning process for ceramic electronic components. The proposed process uses a photoresist, and it is combined with the photolithography process and the printing process. By using both technologies, a high-aspect-ratio and fine conductive pattern is achieved because the patterned photoresist hold the filling paste during the dry process. Moreover, a different material pattern in a ceramic sheet can be formed simultaneously when the photoresist covers on the ceramic sheet with a through-hole pattern. The examples of the patterning process and the fabricated pattern are shown. The fine conductive pattern was formed by using a liquid photoresist, and the line width and the thickness were 10.3 and 1.85 μm, respectively. In the ceramic pattern, the conductive paste and low-temperature co-fired ceramic (LTCC) slurry were filled to the ferrite sheet. As a result, the ceramic sheet that had three different materials was achieved. It realizes the miniature ceramic inductor suppressing the minor loop. However, the photoresist process showed some problems with the fine pattern and the different material pattern. These problems are solved by adjusting the viscosity and the composite ratio of the slurry. The optimization of the type and thickness of the photoresist is required.
Part of the book: Powder Technology
Milliwatt-Level Electromagnetic Induction-Type MEMS Air Turbine Generator
In this chapter, an electromagnetic induction-type MEMS air turbine generator that combined with the MEMS technology and the multilayer ceramic technology is proposed. Three types of MEMS air turbine generators that included the different bearing systems, shape of the rotor and shape of the magnetic circuits are discussed to achieve the high output power. In the MEMS air turbine, the purpose is to achieve high-speed rotational motion. As a result of the comparison between the different structures, a rim-type rotor and a miniature ball bearing system showed the high rotational speed than a flat-type rotor and a fluid dynamic bearing system. The maximum rotational speed of the fabricated air turbine was 290,135 rpm. Moreover, it is important to introduce the magnetic flux to the magnetic circuit. By the multilayer ceramic technology, the three-dimensional coil in miniature monolithic structure was fabricated. The magnetic core that was designed to introduce the magnetic flux showed the low magnetic flux loss. The fabricated MEMS air turbine and the multilayer ceramic magnetic circuit were combined, and the miniature electromagnetic induction-type generator was achieved. The output power was 2.41 mVA, when the load resistance and the output voltage were 8 Ω and 139 mV, respectively.
Part of the book: MEMS Sensors
Active Gaits Generation of Quadruped Robot Using Pulse-Type Hardware Neuron Models
In this chapter, the authors will propose the active gait generation of a quadruped robot. We developed the quadruped robot system using self-inhibited pulse-type hardware neuron models (P-HNMs) as a solution to elucidate the gait generation method. We feedbacked pressures at the robot system’s each foot to P-HNM and varied the joints’ angular velocity individually. We experimented with making the robot walk from an upright position on a flat floor. As a result of the experiment, we confirmed that the robot system spontaneously generates walk gait and trot gait according to the moving speed. Also, we clarified the process by which the robot actively generates gaits from the upright state. These results suggest that animals may generate gait using a similarly simple method because P-HNM mimics biological neurons’ function. Furthermore, it shows that our robot system can generate gaits adaptively and quite easily.
Part of the book: Biomimetics