The World robot summit disaster robotics category – achievements of the 2018 preliminary competition

The World Robot Summit is a robot Olympics and aims to be held in a different country every four years from 2020. The concept of the Plant Disaster Prevention challenge is daily inspections, checks, and emergency response in industrial plants, and in this competition, robots must carry out these types of missions in a mock-up plant. The concept of the Tunnel Disaster Response and Recovery challenge is emergency response to tunnel disasters, and is a simulation competition whereby teams compete to show their ability to deal with disasters, by collecting information and removing debris. The Standard Disaster Robotics challenge assesses, in the form of a contest, the standard performance levels of a robot that are necessary for disaster prevention and emergency response. The World Robot Summit Preliminary Competition was held at Tokyo Big Sight in October 2018, and 36 teams participated in the Disaster Robotics Category. UGVs and UAVs contended the merits of new technology for solving complex problems, using core technologies such as mobility, sensing, recognition, performing operations, human interface, autonomous intelligence etc., as well as system integration and implementation of strategies for completing missions, gaining high-level results.     

Upflow anaerobic sludge blanket (UASB) treatment of supernatant of cow manure by thermal pre-treatment.

Upflow anaerobic sludge blanket (UASB) methane fermentation treatment of cow manure that was subjected to screw pressing, thermal treatment and subsequent solid-liquid separation was studied. Conducting batch scale tests at temperatures between 140 and 180 degrees C, the optimal temperature for sludge settling and the color suppression was found to be between 160-170 degrees C. UASB treatment was carried out with a supernatant obtained from the thermal treatment at the optimal conditions (170 degrees C for 30 minutes) and polymer-dosed solid-liquid separation. In the UASB treatment with a COD(Cr) loading of 11.7 kg/m3/d and water temperature of 32.2 degrees C, the COD(Cr) level dropped from 16,360 mg/L in raw water to 3,940 mg/L in treated water (COD(Cr), removal rate of 75.9%), and the methane production rate per COD(Cr) was 0.187 Nm3/kg. Using wastewater thermal-treated at the optimal conditions, also a methane fermentation treatment with a continuously stirred tank reactor (CSTR) was conducted (COD(Cr) in raw water: 38,000 mg/L, hydraulic retention time (HRT): 20 days, 35 degrees C). At the COD(Cr) loading of 1.9 kg/m3/d, the methane production rate per COD(Cr), was 0.153 Nm3/kg. This result shows that UASB treatment using thermal pre-treatment provides a COD(Cr), loading of four times or more and a methane production rate of 1.3 times higher than the CSTR treatment.     

Fabrication of lotus-type porous carbon steel by the continuous zone melting method and its mechanical properties

A lotus-type porous carbon steel with cylindrical pores was fabricated by the continuous zone melting method in a pressurized mixture of hydrogen and helium gases. The porosity increases with increasing partial pressure of the hydrogen gas, while the pore diameter remains almost constant, independent of the pressure. The ultimate tensile strength of the specimen with cylindrical pores parallel to the tensile direction is lower than the estimated value, assuming that the strength is decreased in proportion to the decrease of the cross-sectional area of the specimen, while the yield strength is higher than the estimated value. The compressive yield strength is also higher than the estimated value. The increase in yield strength is considered to be due to precipitation strengthening. The tensile strength is increased by quenching and tempering, while the elongation decreases. Such mechanical properties are discussed in terms of the microstructural analysis.     

Membrane separation of indigenous noroviruses from sewage sludge and treated wastewater.

In this study, feasibility of membrane separation for the removal of indigenous noroviruses (NVs) is evaluated. The indigenous NV gene was never detected from ultrafiltration (UF) permeates of sewage sludge and treated wastewater. Indigenous NV gene was also not detected from permeates of sewage sludge and treated wastewater by microfiltration (MF) with a pore size of 0.1 microm (MF0.1). Even though the pore size of MF (0.1 microm) was much larger than the diameter of virus particle (approximately 30-40nm), more than 4-log10 reduction value (LRV) at maximum was achieved by membrane separation with MF0.1. NV genes were often detected from permeates of sewage sludge and treated wastewater by MF with a pore size of 0.45 microm (MF0.45), although the maximum log10 reduction values were more than 3.59 for sewage sludge and more than 2.90 for treated wastewater. It is important to verify factors determining the removal efficiency of viruses with MF membranes.     

Robust vector control of induction motors using full-order observer in consideration of core loss

This paper proposes a method for designing a robust full-order observer for vector-controlled induction motors taking core loss into account. Although conventional research focuses on parameter identification, global stability of the identification remains questionable. Therefore, robustness against some parameters is required. This paper describes the design of a robust full-order observer which takes core loss into account, using both the gain-scheduled H/sub /spl infin// control and the linear matrix inequality technique. This design always results in a stable controller. The robustness of the proposed method against variations of resistances is evaluated by experiments.     

Photocatalytic oxidation of low concentration 2,4-D solution with new TiO2 fiber catalyst in a continuous flow reactor.

Environmental pollution by low concentrations of 2,4-Dichlorophenoxyacetic acid (2,4-D) is a concern these days due to ever increasingly stringent regulations. Photocatalysis with immobilized TiO2 fiber is a promising oxidation method. Laboratory experiments on photocatalytic degradation of 0.045 mmol l(-1) 2,4-D with the world's first high-strength TiO2 fiber catalyst were carried out in a continuous flow reactor in which the degradations were, in general, similar to those with high 2,4-D concentrations investigated elsewhere. Degradation and mineralization of 2,4-D were significantly enhanced with no initial pH adjustments. The rate constants for total organic carbon (TOC) without pH adjustment were about two-fold bigger than the pH adjustment cases. CO2 gas measurement and carbon mass-balance were carried out for the first time, where about 34% organic carbon converted into CO2 gas during four-hour oxidation. 2,4-Dichlorophenol (2,4-DCP), phenol, benzyl alcohol and two unknowns (RT = 2.65 and 3.78 min.) were detected as aromatic intermediates while Phenol was the new aromatic in HPLC analysis. Dechlorination efficiencies were high (> 70%) in all the cases, and more than 90% efficiencies were observed in chloride mass balance. Bigger flow rates and solution temperature fixed at 20 degrees C without pH adjustment greatly enhanced 2,4-D mineralization. These results can be an important basis in applying the treatment method for dioxin-contaminated water and wastewater.     

A method for conflict detection based on team intention inference

One of the typical causes of errors in team cooperative activities, such as in central control rooms of power plants and cockpits in aircrafts, is conflicts among team members' intentions. If mutual awareness and communication were perfectly established and maintained, conflicts could be detected and recovered by team members; however, this does not happen in practice. In this paper, we provide a framework for detecting conflicts among team members' intentions based on team intention inference, aiming to make machines function as a coordinator for cooperative activities. In previous work, we developed a method for team intention inference based on a definition of ‘we-intention’. We-intention is other-regarding intentions relating to situations in which some agents act together, and is represented as a set of individual intentions and mutual beliefs. In this framework, a conflict can be defined as a set of individual intentions and false beliefs (undesired procedures), and detected by searching for such combinations. We applied the proposed method to the operation of a plant simulator operated by a two-person team, and it was confirmed through an experiment that this method could list candidates for conflicts by type and set the actual conflict high in priority in the tested context.     

Optical-transmission characteristics of optical-fiber cables and installed optical-fiber cable networks for WDM systems

Many cables containing 1.3-/spl mu/m zero-dispersion single-mode (SM) optical fibers are installed in trunk and access networks. Recently, there have been a number of studies on wavelength-division-multiplexing (WDM) systems designed to increase transmission capacity and flexibility. If we can construct WDM systems using SM optical-fiber cable networks designed to transmit using wavelengths in the 1.3-/spl mu/m window (O-band), this will prove very effective in reducing construction costs. It is therefore important to examine the wavelength dependence of the transmission characteristics of SM optical-fiber cables and networks that have already been installed and in which several optical fibers are joined. In this paper, we describe the measured optical characteristics of SM optical-fiber cables and installed optical-fiber cable networks at various wavelengths. The optical characteristics were stable in the 1.46 to 1.625-/spl mu/m wavelength range and we confirmed that the installed SM optical-fiber cable networks could be used for WDM system applications.     

Self-reflective segmentation of human bodily motions using recurrent neural networks

For realizing a naturalistic collaboration between the human and the robot, we have to establish the intention sharing from the series of motion data that are observed and exchanged between the human and the machine. In a word, this is a problem to detect "meanings" out of the digitized data stream. In this paper, we propose a novel approach based on semiosis, and present a method of interpreting bodily motions using recurrent neural networks called Elman networks. We made some experiments using the raw data acquired while a human performs a simple task of fetching objects by stretching and folding his/her arm, and demonstrate that the network can learn invariant features of the generalized motion concepts, classify the motion by referring to self-organized memory structure, and understand a task structure of the observed human bodily motion. These capabilities are essential for machine intelligence to establishing the human-robot shared autonomy, a new style of human-machine collaboration proposed in the area of robotics.