• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.8
• /
• pp.667-675
• /
• 2013

This paper presents vision-based techniques for underwater landmark detection, map-based localization, and SLAM (Simultaneous Localization and Mapping) in structured underwater environments. A variety of underwater tasks require an underwater robot to be able to successfully perform autonomous navigation, but the available sensors for accurate localization are limited. A vision sensor among the available sensors is very useful for performing short range tasks, in spite of harsh underwater conditions including low visibility, noise, and large areas of featureless topography. To overcome these problems and to a utilize vision sensor for underwater localization, we propose a novel vision-based object detection technique to be applied to MCL (Monte Carlo Localization) and EKF (Extended Kalman Filter)-based SLAM algorithms. In the image processing step, a weighted correlation coefficient-based template matching and color-based image segmentation method are proposed to improve the conventional approach. In the localization step, in order to apply the landmark detection results to MCL and EKF-SLAM, dead-reckoning information and landmark detection results are used for prediction and update phases, respectively. The performance of the proposed technique is evaluated by experiments with an underwater robot platform in an indoor water tank and the results are discussed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.1
• /
• pp.217-225
• /
• 2015

Recently, as the supply of smart phone is spreading and the exhibition industries are rapidly growing, future exhibitions are evolving toward active, customized, interactive, tangible services, which can give more satisfaction to visitors. To realize this services, the indoor localization in the exhibition of visitors is very important and according to the accuracy of localization the quality of services for exhibition are also different. In this paper, state-of-the art indoor localization techniques are investigated and new localization method are proposed. To achieve this goal, future exhibition service types are proposed, which are connected with IT technology. And also, BLE(Bluetooth Low Energy) technology including comparison of specifications and representative localization technologies are analysed. Furthermore we performed comparison study and simulation between RF and VLC channels. Finally based on this, we proposed converged VLC and RF(Wi-Fi and BLE) localization technique for exhibition.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.17 no.2
• /
• pp.182-188
• /
• 2014

Source localization is an important problem in the field of sonar and radar, etc. For the purpose of source localization, two or more spatially separated sensors are often used to measure the time difference of arrivals of a radiating source whose transmitted signal waveform is unknown. The NLS(Nonlinear Least Square) cost function with curve fitting method was proposed recently, which provide robust source localization performance by reducing estimation ambiguity. However, even this algorithm shows degraded performance in a multipath environment. To estimates source localization correctly, source localization algorithm that eliminate the effect of multipath signals is required. In this paper, PMP(Power Matching Procedure) is added to the algorithm, which provides improved source localization performance by properly cutting out the effect of multipath signals. Through simulation the performance of the proposed source localization algorithm is verified.

• Journal of Advanced Navigation Technology
• /
• v.12 no.6
• /
• pp.619-626
• /
• 2008

In this paper, we proposed a RSS based cooperative localization algorithm using VRN for wireless sensor networks, which can estimate the BN position. The proposed localization system monitoring all nodes estimates a position of BN, and calculates an intersection area with cooperative localization. From the results, we confirm that BN intersection area is reduced as the number of RN is increased. In addition, the fewer RN exists, the more iteration needs at least 4 times. Moreover, the propose algorithm using 4 RNs is improved 71.6% estimation performance than conventional method. Therefore, the cooperative localization algorithm with VRN provides higher localization accuracy than RSS based conventional method.

• Asian-Australasian Journal of Animal Sciences
• /
• v.31 no.4
• /
• pp.499-504
• /
• 2018

Objective: Recent studies have challenged the traditional paradigm that growth hormone receptor (GHR) displays physiological functions only in the cell membrane. It has been demonstrated that GHR localizes to the cell nucleus and still exhibits important physiological roles. The phenomenon of nuclear localization of growth hormone (GH)-induced GHR has previously been described in vitro. However, until recently, whether GH could induce nuclear localization of GHR in vivo was unclear. Methods: In the present study, we used pig as an animal model, and porcine growth hormone (pGH) or saline was injected into the inferior vena cava. We subsequently observed the localization of porcine growth hormone receptor (pGHR) using multiple techniques, including, immunoprecipitation and Western-blotting, indirect immunofluorescence assay and electronmicroscopy. Results: The results showed that pGH could induce nuclear localization of pGHR. Taken together, the results of the present study provided the first demonstration that pGHR was translocated to cell nuclei under pGH stimulation in vivo. Conclusion: Nuclear localization of pGHR induced by the in vivo pGH treatment suggests new functions and/or novel roles of nuclear pGHR, which deserve further study.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.8
• /
• pp.745-754
• /
• 2013

An efficient urban outdoor localization and navigation system is proposed for car-like robots. First an accurate outdoor localization method is suggested using line/arc features and 2.5D map matching with LRFs (Laser Range Finders), which can reduce the number of singular cases and increase accuracy. Also, path generation, path tracking, and path modification algorithms are proposed for navigation. All these algorithms are implemented on an electric scooter to construct an autonomous urban outdoor localization and navigation system. Experiments reveal the practicality of the proposed system.

• Journal of Information Processing Systems
• /
• v.16 no.4
• /
• pp.774-783
• /
• 2020

For the issue of subsurface target localization by reverse projection, a new approach of target localization with different distances based on symmetric sub-array multiple-input multiple-output (MIMO) radar is proposed in this paper. By utilizing the particularity of structure of the two symmetric sub-arrays, the received signals are jointly reconstructed to eliminate the distance information from the steering vectors. The distance-independent direction of arrival (DOA) estimates are acquired, and the localizations of subsurface targets with different distances are realized by reverse projection. According to the localization mechanism and application characteristics of the proposed algorithm, the grid zooming method based on spatial segmentation is used to optimize the locaiton efficiency. Simulation results demonstrate the effectiveness of the proposed localization method and optimization scheme.

• Journal of Information Processing Systems
• /
• v.6 no.2
• /
• pp.147-162
• /
• 2010

In this paper, we present a fine-grained localization algorithm for wireless sensor networks using a mobile beacon node. The algorithm is based on distance measurement using RSSI. The beacon node is equipped with a GPS sender and RF (radio frequency) transmitter. Each stationary sensor node is equipped with a RF. The beacon node periodically broadcasts its location information, and stationary sensor nodes perceive their positions as beacon points. A sensor node's location is computed by measuring the distance to the beacon point using RSSI. Our proposed localization scheme is evaluated using OPNET 8.1 and compared with Ssu's and Yu's localization schemes. The results show that our localization scheme outperforms the other two schemes in terms of energy efficiency (overhead) and accuracy.

• ETRI Journal
• /
• v.33 no.6
• /
• pp.924-934
• /
• 2011

Sensor networks play an important role in making the dream of ubiquitous computing a reality. With a variety of applications, sensor networks have the potential to influence everyone's life in the near future. However, there are a number of issues in deployment and exploitation of these networks that must be dealt with for sensor network applications to realize such potential. Localization of the sensor nodes, which is the subject of this paper, is one of the basic problems that must be solved for sensor networks to be effectively used. This paper proposes a probabilistic support vector machine (SVM)-based method to gain a fairly accurate localization of sensor nodes. As opposed to many existing methods, our method assumes almost no extra equipment on the sensor nodes. Our experiments demonstrate that the probabilistic SVM method (PSVM) provides a significant improvement over existing localization methods, particularly in sparse networks and rough environments. In addition, a post processing step for PSVM, called attractive/repulsive potential field localization, is proposed, which provides even more improvement on the accuracy of the sensor node locations.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.8 no.2 s.21
• /
• pp.49-57
• /
• 2005

The target localization using the line arrays buried in the seabed is a difficult problem due to the complex sea bottom characteristics and need to compensate the wave propagation effect to localize the target accurately Sound speed mismatch in the seabed causes a bias in the target bearing estimation and induces the localization error. In this paper we describe a target localization method with improved accuracy of target bearing and localization by calibration the sound speed in the seabed. The proposed algorithm is verified through the ocean data.