• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.1
• /
• pp.9-16
• /
• 2014

The localization compensation algorithm for moving objects using the least-squares method is suggested and the performance of the algorithm is analyzed in this paper. The suggested compensation algorithm measures the distance values of the mobile object moving as a constant speed by the TMVS (TWR Minimum Value Selection) method, estimates the location of the mobile node by the trilateration scheme based on the values, and the estimated location is compensated using the least-squares method. By experiments, it is confirmed that the localization performance of the suggested compensation algorithm is largely improved to 58.84% and 40.28% compared with the conventional trilateration method in the scenario 1 and 2, respectively.

• Proceedings of the IEEK Conference
• /
• 2003.07c
• /
• pp.2581-2584
• /
• 2003

In this paper, we propose a self-localization algorithm using vertical line segments. Indoor environment is consist of horizontal and vertical line features such as doors, furniture, and so on. From the input image, vertical line edges are detected by an edge operator, Then, line segments are obtained by projecting edge image vertically and detecting local maximum from the projected histogram. From the relation of horizontal position of line segments and the location of the robot, nonlinear equations are come out Localization is done by solving the equations by using Newton's method. Experimental results show that the proposed algorithm using one camera is simple and applicable to indoor environment.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.255-256
• /
• 2008

Distributed localization algorithms are required for large-scale wireless sensor network applications. In this paper, we introduce an efficient algorithm, termed weighted neighbor-node distribution localization(WNDL), which emphasizes simple refinement and low system-load for low-cost and low-rate wireless sensors. We inspect WNDL algorithm through MATLAB simulation.

• The Journal of Korea Robotics Society
• /
• v.3 no.3
• /
• pp.237-244
• /
• 2008

Nowadays, research on human-robot interaction has been getting increasing attention. In the research field of human-robot interaction, speech signal processing in particular is the source of much interest. In this paper, we report a speaker localization system with six microphones for a humanoid robot called MAHRU from KIST and propose a time delay of arrival (TDOA)-based feature matrix with its algorithm based on the minimum sum of absolute errors (MSAE) for sound source localization. The TDOA-based feature matrix is defined as a simple database matrix calculated from pairs of microphones installed on a humanoid robot. The proposed method, using the TDOA-based feature matrix and its algorithm based on MSAE, effortlessly localizes a sound source without any requirement for calculating approximate nonlinear equations. To verify the solid performance of our speaker localization system for a humanoid robot, we present various experimental results for the speech sources at all directions within 5 m distance and the height divided into three parts.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.5
• /
• pp.2126-2134
• /
• 2015

The present study suggests a localization method for the first (S₁) and the second (S₂) feature of heart sounds, based on an algorithm involving frequency filtering, energy detection, and interval regulation. Localization accuracy was evaluated by comparing the algorithm with the traditional Hilbert transform-based localization method. Results show that the sensitivity and the positive predictivity value of proposed method, respectively, were 97.27 % and 99.94 % in S₁ detection and 94.99 % and 100 % in S₂ detection.

• Journal of information and communication convergence engineering
• /
• v.9 no.2
• /
• pp.155-160
• /
• 2011

In distributed source localization where sensors transmit measurements to a fusion node, we address the sensor selection problem where the goal is to find the best set of sensors that maximizes localization accuracy when quantization of sensor measurements is taken into account. Since sensor selection depends heavily upon rate assigned to each sensor, joint optimization of rate allocation and sensor selection is required to achieve the best solution. We show that this task could be accomplished by solving the problem of allocating rates to each sensor so as to minimize the error in estimating the position of a source. Then we solve this rate allocation problem by using the generalized BFOS algorithm. Our experiments demonstrate that the best set of sensors obtained from the proposed sensor selection algorithm leads to significant improvements in localization performance with respect to the set of sensors determined from a sensor selection process based on unquantized measurements.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.9
• /
• pp.925-930
• /
• 2008

Many sensor network applications require that each node's sensor data stream be annotated with its physical location in some coordinate system. Equipping GPS on every sensor node is often expensive and does not work in indoor deployments. Recently, cricket-based localization system is often used for indoor localization system. It is very important to know the exact position of beacons in cricket-based localization system for identifying moving sensor node's position. In this paper, a new method, Mobile Listener Detect Algorithm (MLD) which can automatically calculate the unknown newly installed beacons is proposed. For the verification of the feasibility of the proposed scheme, we have conducted several experiments.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2016.10a
• /
• pp.168-171
• /
• 2016

In recent years, indoor localization in Wi-Fi environment has been researched for its location determining capability. The fingerprint and RF propagation models has been the main approach in determining indoor positioning. With the use of fingerprint, a low-cost, versatile localization system can be achieved without the use of external hardware. However, only a few research have been made on virtual access points (VAPs) among indoor localization models. In this paper, the idea of indoor localization system using fingerprint with the addition of VAP in Wi-Fi environment is discussed. The idea is to virtually add APs in the existing indoor Wi-Fi system, this would mean additional virtually APs in the network. The experiments of the proposed algorithm shows the positive results when 2VAPs are used compared with only APs. A combination of 3APs and 2VAPs had the lowest average error in all 4 scenarios with 3.99 meters.

• The Journal of Korea Robotics Society
• /
• v.3 no.1
• /
• pp.33-41
• /
• 2008

Based on object recognition technology, we present a new global localization method for robot navigation. For doing this, we model any indoor environment using the following visual cues with a stereo camera; view-based image features for object recognition and those 3D positions for object pose estimation. Also, we use the depth information at the horizontal centerline in image where optical axis passes through, which is similar to the data of the 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an indoor environment metric map and an object location map. Based on such modeling, we suggest a coarse-to-fine strategy for estimating the global localization of a mobile robot. The coarse pose is obtained by means of object recognition and SVD based least-squares fitting, and then its refined pose is estimated with a particle filtering algorithm. With real experiments, we show that the proposed method can be an effective vision- based global localization algorithm.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2007.06a
• /
• pp.279-284
• /
• 2007

The cultural noise sources in magnetotellurics were localized using the source localization method. Conventional beamforming techniques are not applicable for electromagnetic source localization. In this study, the matched field processing and genetic algorithm are used to localize an electromagnetic source and estimate the polarization direction. The source localization using MT field data shows the characteristics of estimated source distribution related to the strength of cultural noise.