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We have developed a human tracking system for use by robots that integrate sound and face localization. Conventional systems usually require many microphones and/or prior information to localize several sound sources. Moreover, they are incapable of coping with various types of background noise. Our system, the cross-power spectrum phase analysis of sound signals obtained with only two microphones, is used to localize the sound source without having to use prior information such as impulse response data. An expectation-maximization (EM) algorithm is used to help the system cope with several moving sound sources. The problem of distinguishing whether sounds are coming from the front or back is also solved with only two microphones by rotating the robot's head. A developed method that uses facial skin colors classified by another EM algorithm enables the system to detect faces in various poses. It can compensate for the error in the sound localization for a speaker and also identify noise signals entering f...

People usually talk face to face when they communicate with their partner. Therefore, in robot audition, the recognition of the front talker is critical for smooth interactions. This paper presents an enhanced speech detection method for a humanoid robot that can separate and recognize speech signals originating from the front even in noisy home environments. The robot audition system consists of a new type of voice activity detection (VAD) based on the complex spectrum circle centroid (CSCC) method and a maximum signal-to-noise ratio (SNR) beamformer. This VAD based on CSCC can classify speech signals that are retrieved at the frontal region of two microphones embedded on the robot. The system works in real-time without needing training filter coefficients given in advance even in a noisy environment (SNR > 0 dB). It can cope with speech noise generated from televisions and audio devices that does not originate from the center. Experiments using a humanoid robot, SIG2, with two microphones showed that ou...

Interconnect test for highly integrated environments becomes more important in terms of its test time and a complete diagnosis, as the complexity of the circuit increases. Since the board-level interconnect test is based on boundary scan technology, it takes a long test time to apply test vectors serially through a long scan chain. Complete diagnosis is another important issue. Since the board-level test is performed for repair, noticing the faulty position is an essential element of any interconnect test. Generally, the interconnect test algorithms that need a short test time cannot perform the complete diagnosis and the algorithms that perform the complete diagnosis need a lengthy test time. To overcome this problem, a new interconnect test algorithm is developed. The new algorithm can provide the complete diagnosis of all faults with a shorter test time compared to the previous algorithms.

Cyclopolymerization of 1,6-heptadiyne derivatives containing the bulky substitutents was carried out by metathesis catalyst systems. The catalytic activity of molybdenum (V) chloride (MoCl5) in homopolymerization is greater than that of the MoCl5-cocatalyst system, and copolymerization is vice versa in catalytic activity. Newly synthesized homo- and copolymers were soluble in common organic solvents and could afford thin film by solution-casting onto the indium–tin oxide coated glass substrate. The NMR, Fourier transform infrared spectroscopic, and UV–visible spectra indicated that these polymers have a linear conjugated cyclic polyene structure having a bulky substitutent as a pendant group. The number-average molecular weight of these polymers was in the range of 2.4–6.27 × 103. The copolymers exhibited a relatively higher molecular weight than that of the homopolymers. The copolymers were stable up to 380 °C. The electrical conductivities of the I2-doped copolymer thin film by the four-point probe method and surface plasmon resonance spectroscopy were about 500 and 600 S/cm, respectively. © 2002 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 40: 958–964, 2002

Interpolymer complex formation between basic polypeptides, poly(L-proline) Form I [PLP(I)], Form II [PLP(II)] and poly-4-hydroxy-L-proline (PHLP), and acidic polypeptides, poly(L-glutamic acid) (PLGA), poly(D- glutamic acid) (PDGA) and poly(L-aspartic acid) (PLAA), has been studied in water-methanol (1:2 v/v) mixed-solvent by viscometry, potentiometry, light scattering and circular dichroism (CD) measurements. It has been found that polymer complexes between basic- and acidic- polypeptides are formed via hydrogen bonding with a stoichiometric ratio of basic/acidic polypeptides = 1:2 (in unit mole ratio) and that PLP(II) forms polymer complex more favorably with PLGA than with PLAA, and the complex of PLP(II) with PLGA is also more favorable than the complex formation of PHLP with PLGA. In addition, the complex formation is highly dependent on the conformation, especially the optical structure of the component polymers, i.e., the stereoselective complexation is observed. The PLGA having a right-handed helix at pH 3.2 formed the complex favorably and quickly with left-handed helix PLP(II), whereas PDGA having a left-handed helix at pH 3.2 favorably formed the complex with right-handed helix PLP(I).

Interpolymer complex formations between Form II helical poly(L-proline)[(PLP(II)] and Form I helical poly(L-proline)[PLP(I)] and poly(carboxylic acids) such as polyacrylic acid(PAA), atatic polymethacrylic acid(at-PMAA), and syndiotatic polymethacrylic acid( st-PMAA) have been studied by FT-IR, X-ray diffraction, and light scattering measurements. It was found that the interpolymer complexes were formed via hydrogen bonding. The helical PLP(II) formed polymer complex more favorably with PAA and at-PMAA having a disordered structure than wih st-PMAA having a ordered structure. In contrast, the helical PLP(I) formed polymer complex more favorably with st-PMAA than with PAA and at-PMAA. In addition, PLP(II) helix was destroyed on the complexation with PAA and at-PMAA, but the PLP(II) helix was perserved on the complexation with st-PMAA. However, the PLP(I) helix was all perserved on the complexation with poly(carboxylic acids). These findings could be explained in terms of molecular conformation of the complementary polymers associated with the complex formation.

Robot capability of listening to several things at once by its own ears, that is,robot audition, is important in improving interaction and symbiosis between humans and robots. The critical issue in robot audition is real-time processing and robustness against noisy environments with high flexibility to support various kinds of robots and hardware configurations. This paper presents two important aspects of robot audition; Missing-Feature-Theory (MFT) approach and active audition. HARK open-source robot audition incorporates MFT approach to recognize speech signals that are localized and separated from a mixture of sound captured by 8- channel microphone array. HARK is ported to four robots, Honda ASIMO, SIG2, Robovie-R2 and HRP-2, with different microphone configurations and recognizes three simultaneous utterances with 1.9 sec latency. In binaural hearing, the most famous problem is a front-back confusion of sound sources. Active binaural robot audition implemented on SIG2 disambiguates the problem well by rotating its head with pitting. This active audition improves the localization for the periphery.

The complex formation between helical poly-L-glutamic acid (PLGA) and helical poly-L-proline (PLP) was studied in a methanol-water (2 : 1) cosolvent and a propanol-water cosolvent (9 : 1). Reduced viscosity, circular dichroism, pH, and molar absorptivity were measured. The experimental results exhibit that the interpolymer complex was formed between helical PLGA and helical PLP through hydrogen bonding. When the complex was formed the unit mole ratio of PLGA : PLP(II) is 2 : 1 and PLGA : PLP(I) is 1.5 : 1, the ability of complex formation of PLP (II) with PLGA is better than that of PLP(I). On complexation the conformations of PLGA and PLP change and this change is more enhanced in the PLGA-PLP(II) than the PLGA-PLP(I) complex; its cause is studied. © 1993 John Wiley & Sons, Inc.

In normal human communication, people face the speaker when listening and usually pay attention to the speakerpsila face. Therefore, in robot audition, the recognition of the front talker is critical for smooth interactions. This paper presents an enhanced speech detection method for a humanoid robot that can separate and recognize speech signals originating from the front even in noisy home environments. The robot audition system consists of a new type of voice activity detection (VAD) based on the complex spectrum circle centroid (CSCC) method and a maximum signal-to-noise (max-SNR) beamformer. This VAD based on CSCC can classify speech signals that are retrieved at the frontal region of two microphones embedded on the robot. The system works in real-time without needing training filter coefficients given in advance even in a noisy environment (SNR>0 dB). It can cope with speech noise generated from televisions and audio devices that does not originate from the center. Experiments using a humanoid robot, SIG2, with two microphones showed that our system enhanced extracted target speech signals more than 12 dB (SNR) and the success rate of automatic speech recognition for Japanese words was increased about 17 points.

We propose a way to evaluate various sound localization systems for moving sounds under the same conditions. To construct a database for moving sounds, we developed a moving sound creation tool using the API library developed by the ARINIS Company. We developed a two-channel-based sound source localization system integrated with a cross-power spectrum phase (CSP) analysis and EM algorithm. The CSP of sound signals obtained with only two microphones is used to localize the sound source without having to use prior information such as impulse response data. The EM algorithm helps the system cope with several moving sound sources and reduce localization error. We evaluated our sound localization method using artificial moving sounds and confirmed that it can well localize moving sounds slower than 1.125 rad/sec. Finally, we solve the problem of distinguishing whether sounds are coming from the front or back by rotating a robotpsilas head equipped with only two microphones. Our system was applied to a humanoid robot called SIG2, and we confirmed its ability to localize sounds over the entire azimuth range.

The purpose of this research is to accurately classify the speech signals originating from the front even in noisy home environments. This ability can help robots to improve speech recognition and to spot keywords. We therefore developed a new voice activity detection (VAD) based on the complex spectrum circle centroid (CSCC) method. It can classify the speech signals that are received at the front of two microphones by comparing the spectral energy of observed signals with that of target signals estimated by CSCC. Also, it can work in real time without training filter coefficients beforehand even in noisy environments (SNR > 0 dB) and can cope with speech noises generated by audio-visual equipments such as televisions and audio devices. Since the CSCC method requires the directions of the noise signals, we also developed a sound source localization system integrated with cross-power spectrum phase (CSP) analysis and an expectation-maximization (EM) algorithm. This system was demonstrated to enable a robot to cope with multiple sound sources using two microphones.

The conformational transition of Form II → Form I of Poly-L-proline and the intermolecular aggregation of the product Form I during and after the transition in the HOAc-propanol mixture solvent were studied, the ratio of HOAc:propanol being changed as 1:9, 1:6, and 1:4 v/v. For the study, the viscosity, light scattering, and dynamic light scattering of the system were measured. The experimental results exhibit that the concentration of Form II promotes the end-to-end type aggregation during and after the transition Form II → I. The extent of the aggregation is reduced in the order of the ratios of HOAc/propanol 1:9, 1:6, and 1:4 v/v. The end-to-end type aggregation is also reduced at higher temperatures. It was also observed that the end-to-end type aggregation occurs abruptly and strongly after the transition of Form II → I occurred to some extent. The point of the abrupt occurrence depends on the solvents and temperature. The light scattering and translational diffusion-coefficient measurements showed also similar phenomena. It was also observed that the side-by-side type aggregation occurs when the initial concentration of Form II of poly-L-proline is relatively small, and the transition temperature is relatively high (35 and 45°C). All the above mentioned experimental results are explained by a simple principle described in the text.

The purpose of this research is to develop techniques that enable robots to choose and track a desired person for interaction in daily-life environments. Therefore, localizing multiple moving sounds and human faces is necessary so that robots can locate a desired person. For sound source localization, we used a cross-power spectrum phase analysis (CSP) method and showed that CSP can localize sound sources only using two microphones and does not need impulse response data. An expectation-maximization (EM) algorithm was shown to enable a robot to cope with multiple moving sound sources. For face localization, we developed a method that can reliably detect several faces using the skin color classification obtained by using the EM algorithm. To deal with a change in color state according to illumination condition and various skin colors, the robot can obtain new skin color features of faces detected by OpenCV, an open vision library, for detecting human faces. Finally, we developed a probability based method to integrate auditory and visual information and to produce a reliable tracking path in real time. Furthermore, the developed system chose and tracked people while dealing with various background noises that are considered loud, even in the daily-life environments.

This paper presents techniques that enable talker tracking for effective human-robot interaction. To track moving people in daily-life environments, localizing multiple moving sounds is necessary so that robots can locate talkers. However, the conventional method requires an array of microphones and impulse response data. Therefore, we propose a way to integrate a cross-power spectrum phase analysis (CSP) method and an expectation-maximization (EM) algorithm. The CSP can localize sound sources using only two microphones and does not need impulse response data. Moreover, the EM algorithm increases the system's effectiveness and allows it to cope with multiple sound sources. We confirmed that the proposed method performs better than the conventional method. In addition, we added a particle filter to the tracking process to produce a reliable tracking path and the particle filter is able to integrate audio-visual information effectively. Furthermore, the applied particle filter is able to track people while dealing with various noises that are even loud sounds in the daily-life environments.

This paper presents techniques that enable a talker tracking for effective human-robot interaction. We propose new way of integrating an EM algorithm and a particle filter to select an appropriate path for tracking the talker. It can easily adapt to new kinds of information for tracking the talker with our system. This is because our system estimates the position of the desired talker through means, variances, and weights calculated from EM training regardless of the numbers or kinds of information. In addition, to enhance a robot's ability to track a talker in real-world environments, we applied the particle filter to talker tracking after executing the EM algorithm. We also integrated a variety of auditory and visual information regarding sound localization, face localization, and the detection of lip movement. Moreover, we applied a sound classification function that allows our system to distinguish between voice, music, or noise. We also developed a vision module that can locate moving objects.

In this paper, we have developed not only a probabilistic sound localization system including VAD (Voice Activity Detection) component using three microphones but also a face tracking system using a vision camera. Moreover, we have proposed a way to integrate these systems to compensate the errors in the localization of a speaker and to reject unnecessary speech or noise signals entering from the undesired directions effectively. For the purpose of verifying our system's performances, we have installed the proposed audition and vision system to the prototype robot, called IROBAA (Intelligent ROBot for Active Audition), and showed how to integrate an audio-visual system.

In this paper, we not only developed a reliable sound localization system including VAD (voice activity detection) component using three microphones but also a face tracking system using a vision camera. Moreover, we proposed a way to integrate these systems in the human-robot interaction to compensate the errors in the localization of a speaker and to reject unnecessary speech or noise signals entering from the undesired directions effectively. For the purpose of verifying our system's performances, we installed the proposed audition and vision system to the prototype robot, called IROBAA (Intelligent ROBot for Active Audition), and showed how to integrate an audio-visual system

In this paper, we propose reliable detection of sound's direction for human robot interaction. Compared with previous researches, this system comprises simpler algorithm and a proposed nonlinear amplifier which has advantages to increase a detectible distance of sound signal in spite of simple circuits. Moreover, we propose the new performance index using cross-correlation to make reliable detection of sound's direction. Also, since this system include a function to detect a period of voice signals, the robot can know when to start finding sound's direction and performing speech recognition automatically. In order to verify our system's performances, we install the proposed audition system to the prototype robot, called IROBAA (intelligent robot for active audition), and describe the experimental results.

In this paper, we propose reliable detection of sound’s direction for human robot interaction. Compared with previous researches, this system comprises simpler algorithm and a proposed nonlinear amplifier which has advantages to increase a detectible distance of sound signal in spite of simple circuits. Moreover, we propose the new performance index using cross-correlation to make reliable detection of sound’s direction. Also, since this system include a function to detect a period of voice signals, the robot can know when to start finding sound’s direction and performing speech recognition automatically. In order to verify our system's performances, we install the proposed audition system to the prototype robot, called IROBAA (Intelligent ROBot for Active Audition), and describe the experimental results.

This paper presents a new liquid-based electrostatic energy harvester that converts the mechanical energy of human-motion-induced vibrations to electrical energy. The basic design uses a conducting liquid to enhance sensitivity to human motion, the frequency of which is typically as low as several hertz; it also uses a hydrophobic coating to provide a broad frequency bandwidth. As liquid slops in accordance with external motions, proposed energy harvester shows large capacitance variations. The device was tested under various conditions with periodic and nonperiodic movements. The maximum capacitance obtained from the fabricated device was about 10 nF, whereas the minimum capacitance was 5 pF, resulting in an extremely high capacitance ratio of 2000. The hydrophobic treatment enables the fabricated device to work well for periodic motions with a frequency range of 2–5 Hz. The power generated from a human running motion at a speed of 8 km h−1 is theoretically estimated to be 35.3 µW with charge-constrained conversion and an auxiliary voltage of 1 V.

We have studied on the usage reduction and anti-migration properties of newly formulated lead-Free (Bi-based) Ag/Frit modified address electrode (hereinafter VE electrode) systems in PDPs (Plasma Display Panels). It is thought that their high performance such as anti-migration and the cost-competitiveness without any loss of performance in paste, process and luminous efficacy are originated from the optimum controlling of Ag/Frit weight ratio and low specific gravity by low Ag contents, respectively. Currently, lead-free VE electrodes are being applied as main electrode materials of PDP panels fabricated by SDI photo-imageable patterning process including ultra-fine resolution models.