In this study, a ship motion control system design method is introduced for autonomous ships. Some related research results and technologies for autonomous ships have already been developed and applied to testing ships. Recently, the Norwegian Maritime Authority and the Coastal Administration have signed an agreement and started to test autonomous ships in the defined area. Considering recent technology trends and background, in this paper, the authors also try to develop autonomous ship control technologies. In the designed control system, an observer is introduced to estimate unmeasurable system states. Based on the servosystem with state estimator, ship motion control experiment is performed to evaluate control performance using a model ship in water basin.

In this paper, a design for a vehicle body of an armored robot for complex disasters is described. The proposed design considers various requirements in complex disaster situations. Fire, explosion, and poisonous gas may occur simultaneously under those sites. Therefore, the armored robot needs a vehicle body that can protect people from falling objects, high temperature, and poisonous gas. In addition, it should provide intuitive control devices and realistic surrounding views to help the operator respond to emergent situations. To fulfill these requirements of the vehicle body, firstly, the frame was designed to withstand the impact of falling objects. Secondly, the positive pressure device and the cooling device were applied. Thirdly, a panoramic view was implemented that enables real-time observation of surroundings through a number of image sensors. Finally, the cockpit in the vehicle body was designed focused on the manipulability of the armored robot in disaster sites.

In this paper, we introduce a target position reasoning system based on Bayesian network that selects destinations of robots on a map to explore compound disaster environments. Compound disaster accidents have hazardous conditions because of a low visibility and a high temperature. Before firefighters enter the environment, the robots notify information in advance, such as victim’s positions, number of victims, and status of debris of building. The problem of the previous system is that the system requires a target position to operate the robots and the firefighter need to learn how to use the robot. However, selecting the target position is not easy because of the information gap between eyewitness accounts and map coordinates. In addition, learning the technique how to use the robots needs a lot of time and money. The proposed system infers the target area using Bayesian network and selects proper x, y coordinates on the map based on image processing methods of the map. To verify the proposed system, we designed three example scenarios based on eyewetinees testimonies and compared time consumption between human and the system. In addition, we evaluate the system usability by 40 subjects.

In this paper, we introduce the pipe cleaning robot developed to clean the gas impurities of the iron manufacturing equipments. The pipe cleaning robot is composed of two driving modules and one cleaning module. 2-DOF joint units were developed for connections among the modules. To maximize the traction power of the driving parts, it became caterpillar type. The extension links have been developed to maintain the traction force in case the pipe inner diameters change. Three cleaning modules were developed for the effective cleaning in the pipe. The driving and cleaning performance tests of the pipe cleaning robot were proceeded in the field of the iron manufacturing equipments.

This paper presents a localization system using ceiling images in a large indoor environment. For a system with low cost and complexity, we propose a single camera based system that utilizes ceiling images acquired from a camera installed to point upwards. For reliable operation, we propose a method using hybrid features which include natural landmarks in a natural scene and artificial landmarks observable in an infrared ray domain. Compared with previous works utilizing only infrared based features, our method reduces the required number of artificial features as we exploit both natural and artificial features. In addition, compared with previous works using only natural scene, our method has an advantage in the convergence speed and robustness as an observation of an artificial feature provides a crucial clue for robot pose estimation. In an experiment with challenging situations in a real environment, our method was performed impressively in terms of the robustness and accuracy. To our knowledge, our method is the first ceiling vision based localization method using features from both visible and infrared rays domains. Our system can be easily utilized with a variety of service robot applications in a large indoor environment.

본 논문에서는 항만 자동화를 위해 새로이 제안된 리니어 모터 기반 컨테이너 이송시스템에 지능제어기법을 이용하여 그 정밀도를 향상시키고자 한다. LMCTS(Linear Motor-based Container Transfer System)는 스케일의 거대함 때문에 일반 리니어 모터에서 중요시 되지 않는 정지마찰력과 디텐트럭(detent force)이 정밀제어에 큰 문제가 된다. 특히, 컨테이너 적제유무에 따라 시스템 자체가 급격히 변하므로 기존의 PID형 제어기로는 좋은 성능을 얻기 어렵다. 따라서 본 논문에서는 같은 구조를 갖는 두 개의 DR-FNN(Dynamically- constructed Recurrent Fuzzy Neural Network)를 제어기와 에뮬레이터로 구성하여 이러한 문제를 해결하고자 하였다.

Where no records are available at a site, a preliminary estimate may be made from relations between floods and catchment characteristics. A number of these characteristics were chosen for testing and were measured for those catchments where mean annual flood estimates were available. Although the improvement using extended data in regression of flood estimates on catchment characteristics was small, this may be due to the limitations of the regression model. When an individual short term record is to be extended, more detailed attention can be given; an example is presented of the technique which should be adopted in practice, particularly when a short term record covers a period which is known to be biassed. A method of extending the peaks over a threshold series is presented with a numerical example. The extension of records directly from rainfall by means of a conceptual model is discussed, although the application of such methods is likely to be limited by lack of recording raingauge information. Methods of combining information from various sources are discussed in terms of information from catchment characteristics supplemented by records. but are generally applicable to different sources of information. The application of this technique to estimating the probable maximum flood requires more conservative assumptions about the antecedent condition, storm profile and unit hydrograph. It is suggested that the profile and catchment wetness index at the start of the design duration should be based on the assumption that the estimated maximum rainfall occurs in all durations centered on the storm peak.