What kind of floor am I standing on? Floor surface identification by a small humanoid robot through full-body motions

This study addresses a floor identification method for small humanoid robots that work in such daily environments as homes. The fundamental difficulty lays in a method to understand the physical properties of floors. To achieve floor identification with small humanoid robots, we used inertial sensors that can be easily installed on such robots, and dynamically selected a full-body motion that physically senses floors to achieve accurate floor identification. We collected a training data-set over 10 different kinds of common floors in home environments. We achieved 85.7% precision with our proposed method. We also demonstrate that our robot could appropriately change its locomotion behaviours depending on the floor identification results.     

Meter-scale large area LED-embedded light fabric for the application of fabric ceilings in rooms

We have developed a meter-scale light emitting diode (LED)-embedded light fabric and its weaving machine for application to a light device for fabric ceilings, which have recently become desired for lightweight safe ceilings in Japan and other countries with frequent earthquakes. The LED fabric structure is 1.2-m-wide woven fabric that has 5-mm-wide LED chip-mounted printed circuit board (PCB) tapes as wefts. LEDs are mounted on the tape of PCBs with a reel-to-reel chip mounting system. Then, the LED-mounted tapes are woven with a developed automatic looming machine that aligns the weft with an accuracy of 0.9 mm, which is suitable for precise arrangement of LEDs and wiring to power supply. A 1.2 × 1.2 m LED-embedded light fabric weighing 320 g/m² was woven. The luminance of the LED fabric is 353 lx at a distance of 1 m, which is the luminance of conventional office lighting. The temperature increase of LEDs without a rigid cooling aluminum plate is only 5.8 °C, and the LED fabric is flexible enough to sustain 1,000 bends down to a radius of 3 mm. This LED fabric and its weaving technology will lead to light devices that have lightweight, large area, and high flexibility for fabric ceilings, walls, and other large areas in homes and offices.     

Set-based particle swarm optimization with status memory for knapsack problem

Set-based particle swarm optimization (S-PSO) operates on discrete space. S-PSO can solve combinatorial optimization problem with high quality and is successful to apply to the large-scale problem. In S-PSO, a velocity is a set with possibility and a position is a candidate solution. In this paper, we present a novel algorithm of set-based particle swarm optimization with status memory (S-PSOSM) to decide the position based on the previous position for solving knapsack problem. Some operators are redefined for S-PSOSM. S-PSOSM is a simple algorithm because the state of probability reduces. In addition, the weight of S-PSOSM is discussed. S-PSOSM shows high qualities in experimental results.     

Study on stiffness visualization and safety control based on will-consensus building for tele-palpation robot system

This paper proposes a method for visualizing the stiffness of a soft object in a palpation-support information system by the teleoperation of a robot hand. It is important that a palpation system display a body’s shape and stiffness. In our method, the stiffness of the contact area between the soft object and the robot finger is estimated by a recursive least-squares method with forgetting factor that uses an impedance dynamics model. With the estimated stiffness and direction of contact force, we calculate the scalar parameter for visualization of stiffness. Moreover, we propose a safety control method for the palpation system, which is part of a tele-control method based on will-consensus building. The system configuration, estimated algorithm, and experimental results are presented.     

A content search system considering the activity and context of a mobile user

People routinely carry mobile devices in their daily lives and obtain a variety of information from the Internet in many different situations. In searching for information (content) with a mobile device, a user’s activity (e.g., moving or stationary) and context (e.g., commuting in the morning or going downtown in the evening) often change, and such changes can affect the user’s degree of concentration on his or her mobile device’s display and information needs. Therefore, a search system should provide the user with an amount of information suitable for the current activity and a type of information suitable for the current context. In this study, we present the design and implementation of a content search system that considers a mobile user’s activity and context, with the goal of reducing the user’s operation load for content search. The proposed system switches between two kinds of content search systems according to the user’s activity: the location-based content search system is activated when the user is stationary (e.g., standing and sitting), while a menu-based content search system is activated when the user is moving (e.g., walking). Both systems present information according to user context. The location-based system presents detailed information via menus and a map according to location-based categories. The menu-based system presents only a few options to enable users to get content easily. Through user experiments, we confirmed that participants could get desired information more easily with this system than with a commercial search system.     

A manufacturing XML schema definition and its application to a data management system on the shop floor

Digitization for sharing knowledge on the shop floor in the machinery industry has been given much attention recently. To help engineers use digitization practically and efficiently, this paper proposes a method based on manufacturing case data that has a direct relation to manufacturing operations. The data are represented in XML schema, as it can be easily applied to Web-based systems on the shop floor. The definitions were made for eight manufacturing methods including machining and welding. The derived definitions consist of four divisions of metadata, work-piece, process and evaluation. Three divisions except for the “process” division are common to the manufacturing methods. The average number of elements for a manufacturing method is about 200. The represented schema is also used to convey knowledge such as operation standards and manufacturing troubleshooting on the shop floor. Using the definitions, a data management system is developed. It is a Web-based Q&A system, in which the engineers specify the manufacturing case data mainly by selecting from the candidates. Then, the system fills in the blank portions and/or shows messages to help complete the case data. The proposed method is evaluated through practical scenarios of arc welding and machining.     

Micromachining of electroformed nickel mold using thick photoresist microstructure for imprint technology

In order to fabricate polymer-based microstructures with feature sizes on the order of micrometers, we have been developing a microimprint technology with a fine nickel (Ni) mold instead of a conventional photolithography technique. The Ni mold was successfully fabricated by electroforming using a positive thick photoresist microstructure patterned on a silicon substrate as a replication master. The photoresist microstructure with excellent edge quality can be obtained under irradiation with single wavelength (g line) selected from a high-pressure mercury lamp. In addition, its sidewall angle in the range of 65° to 84° can be controlled precisely by varying the distance between a photomask and a photoresist surface. On the structured photoresist master, Ni was electroplated up to a thickness of about 110 μm, and then removed from the master. In this process, two-step electroplating at different current densities was carried out in order to prevent deformation of the photoresist master due to stress generated in a Ni electrodeposit. With the Ni mold, fine patterns with a width of 10 or 30 μm and a depth of 24 μm were almost completely transferred to polymetric materials (PMMA). The geometrical dimensions of the fabricated PMMA microstructures were found to be only about 10% reduction against the Ni mold.     

A multi-objective strategy in genetic algorithms for gene selection of gene expression data

A microarray machine offers the capacity to measure the expression levels of thousands of genes simultaneously. It is used to collect information from tissue and cell samples regarding gene expression differences that could be useful for cancer classification. However, the urgent problems in the use of gene expression data are the availability of a huge number of genes relative to the small number of available samples, and the fact that many of the genes are not relevant to the classification. It has been shown that selecting a small subset of genes can lead to improved accuracy in the classification. Hence, this paper proposes a solution to the problems by using a multiobjective strategy in a genetic algorithm. This approach was tried on two benchmark gene expression data sets. It obtained encouraging results on those data sets as compared with an approach that used a single-objective strategy in a genetic algorithm. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Selecting informative genes from microarray data by using hybrid methods for cancer classification

Gene expression technology, namely microarrays, offers the ability to measure the expression levels of thousands of genes simultaneously in biological organisms. Microarray data are expected to be of significant help in the development of an efficient cancer diagnosis and classification platform. A major problem in these data is that the number of genes greatly exceeds the number of tissue samples. These data also have noisy genes. It has been shown in literature reviews that selecting a small subset of informative genes can lead to improved classification accuracy. Therefore, this paper aims to select a small subset of informative genes that are most relevant for cancer classification. To achieve this aim, an approach using two hybrid methods has been proposed. This approach is assessed and evaluated on two well-known microarray data sets, showing competitive results. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Refined mapping of a gene responsible for Fukuyama-type congenital muscular dystrophy: evidence for strong linkage disequilibrium

Fukuyama-type congenital muscular dystrophy (FCMD), the second most common form of childhood muscular dystrophy in Japan, is an autosomal recessive severe muscular dystrophy associated with an anomaly of the brain. After our initial mapping of the FCMD locus to chromosome 9q31-33, we further defined the locus within a region of approximately 5 cM between loci D9S127 and CA246, by homozygosity mapping in patients born to consanguineous marriages and by recombination analyses in other families. We also found evidence for strong linkage disequilibrium between FCMD and a polymorphic microsatellite marker, mfd220, which showed no recombination and a lod score of (Z) 17.49. A "111-bp" allele for the mfd220 locus was observed in 22 (34%) of 64 FCMD chromosomes, but it was present in only 1 of 120 normal chromosomes. This allelic association with FCMD was highly significant (chi 2 = 50.7; P < .0001). Hence, we suspect that the FCMD gene could lie within a few hundred kilobases of the mfd220 locus.