This paper proposes a novel upward-looking camera-based global localization using a ceiling image map. The ceiling images obtained through the SLAM process are integrated into the ceiling image map using a particle filter. Global localization is performed by matching the ceiling image map with the current ceiling image using SURF keypoint correspondences. The robot pose is then estimated by the coordinate transformation from the ceiling image map to the global coordinate system. A series of experiments show that the proposed method is robust in real environments.

Localization is one of the essential tasks necessary to achieve autonomous navigation of a mobile robot. One such localization technique, Monte Carlo Localization (MCL) is often applied to a digital surface model. However, there are differences between range data from laser rangefinders and the data predicted using a map. In this study, commonly observed from air and ground (COAG) features and candidate selection based on the shape of sensor data are incorporated to improve localization accuracy. COAG features are used to classify points consistent with both the range sensor data and the predicted data, and the sample candidates are classified according to their shape constructed from sensor data. Comparisons of local tracking and global localization accuracy show the improved accuracy of the proposed method over conventional methods.

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

This paper verifies the performance of Extended Kalman Filter(EKF) and MCL(Monte Carlo Localization) approach to localization of an underwater vehicle through experiments. Especially, the experiments use acoustic range sensor whose measurement accuracy and uncertainty is not yet proved. Along with localization, the experiment also discloses the uncertainty features of the range measurement such as bias and variance. The proposed localization method rejects outlier range data and the experiment shows that outlier rejection improves localization performance. It is as expected that the proposed method doesn’t yield as precise location as those methods which use high priced DVL(Doppler Velocity Log), IMU(Inertial Measurement Unit), and high accuracy range sensors. However, it is noticeable that the proposed method can achieve the accuracy which is affordable for correction of accumulated dead reckoning error, even though it uses only range data of low reliability and accuracy.

게임개발환경의 빠른 성장에 맞춰 게임시장은 더욱 실질적인 게임기술을 필요로 하지만 중국 온라인 게임은 같은 장르의 대부분 게임 스타일이 비슷하며 게임유저 선호에 밀접한 독창성에 대한 부분은 미흡하다. 따라서 전 세계에 거친 유저들이 동시에 이용하는 온라인 게임의 경우 각 나라만의 게임그래픽 선호도의 지침이 중요한 사항인데 반해 제작국가의 불분명성에 기인한 디자인이 만연하다. 한국, 중국, 일본은 이미 유명한 스토리텔링의 주제인 "삼국지"를 기반으로 중국의 전통문화와 자기나라의 상황을 결합하여 게임 디자인을 진행하였다. 각 나라의 독특한 게임디자인 스타일은 분명히 존재하며 산업적 활용성 차원의 게임디자인에 도움이 되는 연구가치로써 중요한 배경을 이룬다. 본 연구는 각 나라의 25개의 "삼국지 게임"을 주제로 한 온라인 게임을 연구대상으로 게임 배경 디자인 요소를 회귀분석을 통한 비교분석을 진행하여 각 나라의 디자인 특징을 설명, 향후 동종연구자들 및 실질적인 게임그래픽 디자이너의 게임디자인 개발에 효율적인 방향을 제언하려 한다.

Rice is a staple food crop in the world. A number of agronomically important traits including enhancement of stress tolerance, quality improvement, and nutrition value increases have been introduced to rice. In this study, an Oryza sativa cDNA containing a U-box motif was cloned; its deduced amino acid sequence was compared to that of other U-box genes and indicated that encodes a U-box-containing E3 ligase. E3 ligases are structurally divided into three groups. We isolated the OsUPS gene from rice (Oryza sativa). The OsUPS protein has domain which is a single~70-amino acid region of the protein and GKL domain containing conserved Glycine, Lysine/ Araginine residues and leucine-rich feature. A full-length expression of OsUPS was up-regulated in the rice plant and in cell culture in the absence of phosphate. To express the OsUPS cDNA, it was inserted into the pGEX-2T vector. And the gene was expressed in E.coli strain BL21 (DE3). Induced after 3h of IPTG treatment and was isolated by affinity chromatography. Using the GUS reporter genes regulated by the OsUPS promoter, we have carried out the analysis of transcriptional and spatial regulation of gene expression. To investigate the function of these genes, the CaMV 35S promoter-driven these genes were introduced into Arabidopsis and rice via Agrobacterium tumefaciens-mediated gene transformation. We found that full-length expression of OsUPS was up-regulated in both rice plants and cell culture in the absence of inorganic phosphate (Pi). A self-ubiquitination assay indicated that the bacterially expressed OsUPS protein had E3 ligase activity, and subcellular localization results showed that OsUPS was located in the chloroplast. These results support the notion that OsUPS plays an important role in the Pi signaling pathway through the ubiquitin-26S proteasome system.

In this paper, a localization algorithm and an autonomous controller for PETASUS system II which is an underwater vehicle-manipulator system, are proposed. To estimate its position and to identify manipulation targets in a structured environment, a multi-rate extended Kalman filter is developed, where map information and data from inertial sensors, sonar sensors, and vision sensors are used. In addition, a three layered control structure is proposed as a controller for autonomy. By this controller, PETASUS system II is able to generate waypoints and make decisions on its own behaviors. Experiment results are provided for verifying proposed algorithms.

Due to the low localization accuracy and the requirement of special infrastructure, current LBS(Localization Based Service) is limited to show P.O.I.(Point of Interest) nearby. Improvement of IMU(Inertial Measurement Unit) based deadreckoning is presented in this paper. Additional sensors such as the magnetic compass and magnetic flux sensors are used as well as the accelerometer and the gyro for getting more information of movement. Based on the pedestrian movement, appropriate sensor information is selected and the complementary filter is used in order to enhance the accuracy of the localization.

This paper proposes particle filter(PF) method using acoustic signal for localization of an underwater robot. The method uses time of arrival(TOA) or time difference of arrival(TDOA) of acoustic signals from beacons whose locations are known. An experiment in towing tank uses TOA information. Simulation uses TDOA information and it reveals dependency of the localization performance on the uncertainty of robot motion and senor data. Also, comparison of the PF method with the least squares method of spherical interpolation(SI) and spherical intersection(SX) is provided. Since PF uses TOA or TDOA which comes from measurement of external information as well as internal motion information, its estimation is more accurate and robust to the sensor and motion uncertainty than the least squares methods.

Brown planthopper (BPH) is a destructive insect pest of rice in Korea. Identification and the incorporation of newBPH resistance genes into modern rice cultivars are important breeding strategies to control the damage caused by BPH. To expand genetic resource against BPH in Korea, we screened more than 2,500 mutant lines, which were derived from EMS treatment on Namil, a high yielding Korean japonica cultivar. One mutant line, Namil(EMS)M2-1463-1-1-1-1, designated as ‘Namil(EMS)-bl10,bph1’ performed high level of resistance against BPGH and rice blast, while the wild type, Namil, performed highly susceptible to rice blast as well as BPH. A mapping population was constructed by using F2 progeny lines derived from cross between Namil(EMS)-bl10,bph1 and Milyang23, a BPH susceptible Tongil type cultivar. DNAs prepared from F2 individuals were used for SSR marker based linkage map skeleton, and F2:3 seeds were subjected to BPH infestation to infer resistance level of corresponding F2 plant. Association analysis between marker genotype and evaluated survival ratio of each progeny line were used to localize the putative chromosomal location(s) involved to BPH resistance. The location was initially located on the subterminal region of the long arm of chromosome 12 flanked by the SSR markers RM1337 and RM277, where at least three BPH resistance genes, Bph1, Bph18, and Bph21, were localized previously.

Plants are known to have homeostatic cellular mechanisms to control the concentration of heavy metal inside the cell. We tried to retrieve rice RING finger protein genes, which are believed to regulate substrates via ubiqitinations, related to metal ions detoxification mechanisms. A total of 48 rice RING finger proteins were randomly selected and then examined for their expression patterns as exposed to cadmium and arsenic treatments. We discovered a RING finger protein gene that was significant up-regulated against both treatments and then named Oryza sativa heavy metal induced 1 (OsHMI1). We tested subsequently OsHMI1 expression patterns against to salinity, dehydration, cold, heat stress and phytohormones treatments. In addition, we evaluated its subcellular localization and determined E3 ligase activity. The interaction partner proteins were screened via yeast-two hybridization. These results might shed further light on the understanding of homeostatic cellular mechanisms to control heavy metal detoxification via protein degradation in plants.

This paper proposes how to improve the performance of CSS-based indoor localization system. CSS based localization utilizes signal flight time between anchors and tag to estimate distance. From the distances, the 3-dimensional position is calculated through trilateration. However the error in distance caused from multi-path effect transfers to the position error especially in indoor environment. This paper handles a problem of reducing error in raw distance information. And, we propose the new localization method by pattern matching instead of the conventional localization method based on trilateration that is affected heavily on multi-path error. The pattern matching method estimates the position by using the fact that the measured data of near positions possesses a high similarity. In order to gain better performance of localization, we use EKF(Extended Kalman Filter) to fuse the result of CSS based localization and robot model.

The Egr family of zinc finger transcription factors consisting of 4 members (Egr1 to -4) regulates critical genetic programs involved in cellular growth, differentiation, and function. Especially, the critical role for Egr1 in regulating luteinizing hormone responsiveness was demonstrated by using gene-targeted mouse models. Other members of Egr family were shown to be involved in other cellular and developmental processes. To understand if Egr3 is implicated in ovarian functions, we focused on identifying cell type-specific and subcellular localization of Egr3 in cycling mouse ovaries and oocytes. RT-PCR analyses show that Egr3 mRNA is expressed in the mouse ovary and oocytes. By immunofluorescence staining, we observed that Egr3 is weakly expressed in subsets of granulosa cells. Interestingly, Egr3 seems to be co-localized with meiotic spindle in some oocytes in the ovarian section. Therefore, we examined Egr3 localization in MI oocytes cultured in vitro. We confirmed co-localization of Egr3 and microtubule in the mouse oocyte during meiosis I. Egr3 localization is noted around condensing chromosomes during prometaphase I (PMI). At metaphase I (MI) and MII, Egr3 is localized on meiotic spindle and also around each cytosolic microtubule organizing centers (MTOCs) in a punctate pattern. To examine if microtubule is required for correct positioning of Egr3 on this structure, we observed the pattern of Egr3 in oocytes matured under taxol or nocodazole. In taxol-treated oocyte, Egr3 and gamma-tubulin complex are enlarged. In nocodazole-treated oocyte, Egr3 localization on spindle and MTOCs are abolished. Thus, Egr3 localization seems to require the presence of intact microtubule. Collectively, our result shows for the first time that Egr3, a transcription factor, is localized on meiotic spindle of maturing mouse oocytes. The work suggests a novel role for Egr3 as a factor involved in MTOC dynamics during meiosis.

Global positioning system (GPS) is widely used to measure the position of a vehicle. However, the accuracy of the GPS can be severely affected by surrounding environmental conditions. To deal with this problem, the GPS and odometry data can be combined using an extended Kalman filter. For stable navigation of an outdoor mobile robot using the GPS, this paper proposes two methods to evaluate the reliability of the GPS data. The first method is to calculate the standard deviation of the GPS data and reflect it to deal with the uncertainty of the GPS data. The second method is to match the GPS data to the traversability map which can be obtained by classifying outdoor terrain data. By matching of the GPS data with the traversability map, we can determine whether to use the GPS data or not. The experimental results show that the proposed methods can enhance the performance of the GPS‐based outdoor localization.

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.

This paper propose a localization system of indoor mobile robots. The localization system includes camera and artificial landmarks for global positioning, and encoders and gyro sensors for local positioning. The Kalman filter is applied to take into account the stochastic errors of all sensors. Also we develop a dead reckoning system to estimate the global position when the robot moves the blind spots where it cannot see artificial landmarks, The learning engine using modular networks is designed to improve the performance of the dead reckoning system. Experimental results are then presented to verify the usefulness of the proposed localization system.

This paper proposes a technique of indoor localization for mobile robot by so called indoor GPS and EKF. Basically the concept of indoor GPS is similar outdoor GPS, and the indoor GPS gets distances between Anchors and Tag by a ranging method of CSS and then estimates the coordinate by distances and known Anchor positions. After we performed performance test of indoor GPS system in ideal and multipath environment, we configured that the indoor GPS has internal error factors and external error factors. This paper handled a multipath problem belonging to external error factors. At first various direct physical method are introduced to fix the multipath problems, and as expected we got errors corrected considerably. And then the method of selective anchors for indoor GPS is applied. With these two level improvement of indoor GPS performance, EKF(Extended Kalman Filter) is applied to mobile robot in indoor environment. The usefulness of the proposed methods are shown by a series of experiments in a environment giving contaminated data by multipath.