Thermal Behavior of BaTiO3 Particles Synthesized by Plasma Chemical Vapor Deposition

The thermal behavior of nanoparticles BaTiO₃, prepared by a radio-frequency plasma chemical vapor deposition (RF-plasma CVD) method, was characterized by various analysis methods. The BaCO₃ phase was included in the powder as byproducts, which is also observed in hydrothermal BaTiO₃ powder. The BaCO₃ phase decomposed and disappeared by annealing at 873 K for 30 min. H₂O, N₂, CO₂ and H₂, were detected by a thermal desorption spectra measurement from BaTiO₃ powder. The annealed powder became well-crystallized particles without grain growth, although as-prepared powder included polycrystalline particles. We successfully observed in-situ grain growth for BaTiO₃ nanoparticles by thermal transmission electron microscope. At the initial step of normal grain growth, very fine particles with 40–60 nm diameters started to merge into the larger grains around 1083 K. The migration rate was measured by video images and a grain boundary diffusion coefficient D_gb was calculated.     

Surface Chemistry of Lead Titanate and Its Impact on Binder Removal

Carbon residue after binder burnout was characterized for several nonstoichiometric lead titanate powders. Thermal decomposition of the poly(methyl methacrylate) (PMMA) binder was performed in nitrogen at 600°C. A drastic decrease in carbon retention was obtained in the case of the titanium-rich samples. The amount of carbon retention varies from 0.2 mg/m² to 1.2 mg/m² by changing the Pb/Ti molar ratio from 0.92 to 1.08. The surface reaction between PMMA and lead titanate particles was studied by diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS). Surface hydroxyls reacted with ester groups in the PMMA or the methylmethacrylate monomer produced upon pyrolysis. The DRIFTS results showed that titaniumrich samples are less reactive and produce less surfacebound organic groups. Interestingly, titanium-rich samples contained more surface hydroxyls. Isoelectric point measurements, however, show that titanium-rich samples are more acidic. Thus, the reactivity of the surface hydroxyls is determined primarily by their acid-base characteristics rather than their concentration. Lead titanate powder was exposed to MMA vapor in a tube furnace at the indicated temperatures using nitrogen carrier gas as a model experiment. DRIFTS difference spectroscopy and Raman spectroscopy were performed on these samples after the exposure. MMA reacts with lead titanate powder in manner similar to PMMA. Analysis for sp ² and sp ³ absorbance of Raman spectra of these exposed powders at 400°–600°C showed pyrolysis behavior of surface-reacted species. The relative amount of sp ² bonded carbon decreases with increasing exposure temperature.     

Stick-slip motion control based on cutter location data for an orthogonal-type robot

In this article, a new desktop orthogonal-type robot, which has the capacity of stick-slip motion control based on cutter location data, is presented for lapping small metallic molds with a curved surface. The robot consists of three single-axis devices with a high position resolution of 1 μm. A thin wooden stick tool with a ball-end shape is attached to the tip of the z-axis. In order to improve the lapping performance, a novel stick-slip motion control method is developed in the control system. The small stick-slip motion is orthogonally generated in the direction of the tool’s movement. The effectiveness of stick-slip motion control is examined through an actual lapping test of an LED lens cavity.     

iOS application for quadrotor remote control

With the progress of electronics technology, the development of civilian UAV (unmanned aerial vehicle) applications becomes possible. In addition, smartphones have rapidly gained popularity and become very important due to the simple operability and mobility. Hence, there is a need to have an easy and flexible way to control a UAV using such technology. In this study, a remote controller using an iOS device is developed for a quadrotor to enable remote control with easy operations. Four basic programs for obtaining compass information, controlling a gimbal, autopilot function for return, and video preview function are developed and implemented for an iOS device. The basic functionalities of the programs are evaluated and confirmed through experiments using a quadrotor and an iOS device.     

Control of three-link underactuated manipulators using a switching method of fuzzy energy regions

In general, manipulators used for industry and in academic laboratories have actuators to drive each joint. On the other hand, underactuated manipulators handled by our research have some passive or free joints without actuators and brakes. We recently developed a switching method of fuzzy energy regions to control such manipulators. In such a method, it is necessary to design parameters related to energy regions and the gains of some partly stable controllers based on the computed torque method. Here, the switching method is applied for a three-link underactuated manipulator. We optimize such design parameters related to fuzzy energy regions by a genetic algorithm. The effectiveness of the present method is illustrated with some simulations. This work was presented in part at the 12th International Symposium on Artificial Life and Robotics, Oita, Japan, January 25–27, 2007     

Modular fuzzy-neuro controller driven by spoken language commands.

We present a methodology of controlling machines using spoken language commands. The two major problems relating to the speech interfaces for machines, namely, the interpretation of words with fuzzy implications and the out-of-vocabulary (OOV) words in natural conversation, are investigated. The system proposed in this paper is designed to overcome the above two problems in controlling machines using spoken language commands. The present system consists of a hidden Markov model (HMM) based automatic speech recognizer (ASR), with a keyword spotting system to capture the machine sensitive words from the running utterances and a fuzzy-neural network (FNN) based controller to represent the words with fuzzy implications in spoken language commands. Significance of the words, i.e., the contextual meaning of the words according to the machine's current state, is introduced to the system to obtain more realistic output equivalent to users' desire. Modularity of the system is also considered to provide a generalization of the methodology for systems having heterogeneous functions without diminishing the performance of the system. The proposed system is experimentally tested by navigating a mobile robot in real time using spoken language commands.     

Omnifocus video camera

The omnifocus video camera takes videos, in which objects at different distances are all in focus in a single video display. The omnifocus video camera consists of an array of color video cameras combined with a unique distance mapping camera called the Divcam. The color video cameras are all aimed at the same scene, but each is focused at a different distance. The Divcam provides real-time distance information for every pixel in the scene. A pixel selection utility uses the distance information to select individual pixels from the multiple video outputs focused at different distances, in order to generate the final single video display that is everywhere in focus. This paper presents principle of operation, design consideration, detailed construction, and over all performance of the omnifocus video camera. The major emphasis of the paper is the proof of concept, but the prototype has been developed enough to demonstrate the superiority of this video camera over a conventional video camera. The resolution of the prototype is high, capturing even fine details such as fingerprints in the image. Just as the movie camera was a significant advance over the still camera, the omnifocus video camera represents a significant advance over all-focus cameras for still images.     

Adaptive Learning with Large Variability of Teaching Signals for Neural Networks and Its Application to Motion Control of an Industrial Robot

Recently, various control methods represented by proportional-integral-derivative (PID) control are used for robotic control.To cope with the requirements for high response and precision, advanced feedforward controllers such as gravity compensator,Coriolis/centrifugal force compensator and friction compensators have been built in the controller.Generally, it causes heavy computational load when calculating the compensating value within a short sampling period.In this paper, integrated recurrent neural networks are applied as a feedforward controller for PUMA560 manipulator.The feedforward controller works instead of gravity and Coriolis/centrifugal force compcusators.In the learning process of the neural network by using back propagation algorithm, the learning coefficient and gain of sigmoid function are tuned intuitively and empirically according to teaching signals.The tuning is complicated because it is being conducted by trial and error.Especially, when the scale of teaching signal is large, the problem becomes crucial.To cope with the problcm which concerns the learning performance, a simple and adaptive learning technique for large scale teaching signals is proposed.The learning techniques and control effectiveness are evaluated through simulations using the dynamic model of PUMA560 manipulator.