• Journal of Electrical Engineering and Technology
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• v.7 no.4
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• pp.606-614
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• 2012

A practical recursive linear robust estimation scheme is proposed for target localization in the sensor network which provides range difference of arrival (RDOA) measurements. In order to radically solve the known practical difficulties such as sensitivity for initial guess and heavy computational burden caused by intrinsic nonlinearity of the RDOA based target localization problem, an uncertain linear measurement model is newly derived. In the suggested problem setting, the target localization performance of the conventional linear estimation schemes might be severely degraded under the low SNR condition and be affected by the target position in the sensor network. This motivates us to devise a new sensor network localization algorithm within the framework of the recently developed robust least squares estimation theory. Provided that the statistical information regarding RDOA measurements are available, the estimate of the proposition method shows the convergence in probability to the true target position. Through the computer simulations, the omnidirectional target localization performance and consistency of the proposed algorithm are compared to those of the existing ones. It is shown that the proposed method is more reliable than the total least squares method and the linear correction least squares method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.293-299
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• 2010

The multiple block localization method in a wide area for multiple robots using iGS is proposed in this paper. The iGS is developed for the indoor global localization using ultrasonic and RF sensors. To measure the distance between a mobile robot and a beacon, the tag on the mobile robot wakes up one beacon to send out the ultrasonic signal and measures the traveling time from the beacon to the mobile robot. As the number of robots is increased, the sampling time of localization also becomes longer. Note that only one robot can localize its own position calling beacons one by one during each of the sampling interval. This is a severe constraint for the localization of multiple robots in a wide area. This paper proposes an efficient localization algorithm for the multiple robots in a wide area which can be divided into multiple blocks. For a given block, a master beacon is designated to synchronize robots. By the access of the synchronization signal, each beacon in the selected group sends out an ultrasonic signal. When the robots in the block receive the ultrasonic signal, they can calculate their own locations based on the distances to the beacons, which are obtained by the multiplication of flight time and velocity of the ultrasonic signal. The efficiency of the algorithm is verified through the real experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1738-1745
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• 2016

In this paper, we present localization and autonomous navigation method using GPU(Graphics Processing Unit)-based SIFT(Scale-Invariant Feature Transform) algorithm and virtual force method for mobile robots. To do this, at first, we propose the localization method to recognize the landmark using the GPU-based SIFT algorithm and to update the position using extended Kalman filter. And then, we propose the A-star algorithm for path planning and the virtual force method for autonomous navigation of the mobile robot. Finally, we demonstrate the effectiveness and applicability of the proposed method through some experiments using the mobile robot with OPRoS(Open Platform for Robotic Services).

• The Journal of the Acoustical Society of Korea
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• v.25 no.1E
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• pp.8-13
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• 2006

In this paper, an Optimized Ambisonic Panning Algorithm (OAPA) which reduces sound localization error, is proposed. In the conventional Ambisonic Panning Algorithm (APA), sound localization is usually different from the panning angle, especially when listeners are not in an ideal listening position, because of low signal separation among other channels. To overcome this problem, an OAPA using window functions is proposed. A proper window function can be verified, comprising of higher harmonic components than 2M+1 and improved DPC and channel separation. Analysis results demonstrate that the proposed method results in higher signal separation among other channels and lower sound localization errors than the conventional APA.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.795-800
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• 2008

The paper presents research for the established experiment environment of multi vehicle robot, localization algorithm that is based on vehicle control, and path tracking. The established experiment environment consists of ultrasonic positioning system, vehicle robot, server and wireless module. Ultrasonic positioning system measures positioning for using ultrasonic sensor and generates many errors because of the influence of environment such as a reflection of wall. For a solution of this fact, localization algorithm is proposed to determine a location using vehicle kinematics and selection of a reliable location data. And path tracking algorithm is proposed to apply localization algorithm and LOS, finally, that algorithms are verified via simulation and experimental

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.264-267
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• 2000

This paper describes a real-time 3D sound localization algorithm to be implemented with the use of a Bow power embedded DSP. This algorithm first divides the audible frequency band into three, on the basis of the analysis of the sound reflection and diffraction effects through different media from a certain sound source to human ears, and then in each subband a specific procedure is devised fur the 3D sound localization so as to operate real-time on a low power embedded DSP This algorithm aims at providing a listener with the 3D sound effects through a headphone at low cost and low power consumption.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2015.11a
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• pp.4-7
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• 2015

In this paper, we propose a matrix completion algorithm for Internet of Things (IoT) localization. The proposed algorithm recovers the Gram matrix of sensors by performing optimization over the Riemannian manifold of fixed-rank positive semidefinite matrices. We compute and show the closed forms of all the differentially geometric components required for applying nonlinear conjugate gradients combined with Armijo line search method. The numerical experiments show that the performance of the proposed algorithm in solving IoT localization is outstanding compared with the state-of-the-art matrix completion algorithms both in noise and noiseless scenarios.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.678-687
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• 2005

This paper describes a relative localization algorithm using odometry data and consecutive local maps. The purpose of this paper is the odometry error correction using the area matching of two consecutive local maps. The local map is built up using a sensor module with dual laser beams and USB camera. The range data form the sensor module is measured using the structured lighting technique (active stereo method). The advantage in using the sensor module is to be able to get a local map at once within the camera view angle. With this advantage, we propose the AVS (Aligned View Sector) matching algorithm for. correction of the pose error (translational and rotational error). In order to evaluate the proposed algorithm, experiments are performed in real environment.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.141-143
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• 2004

This paper presents an algorithm in which a feature map is built and localization of a mobile robot is carried out for indoor environments. The algorithm proposes an approach which extracts scale-invariant features of natural landmarks from a pair of stereo images. The feature map is built using these features and updated by merging new landmarks into the map and removing transient landmarks over time. And the position of the robot in the map is estimated by comparing with the map in a database by means of an Extended Kalman filter. This algorithm is implemented and tested using a Pioneer 2-DXE and preliminary results are presented in this paper.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2435-2437
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• 2004

In this paper, an obstacle avoidance algorithm is proposed for a network-based robot considering network delay by distribution. The proposed algorithm is based on the VFH(Vector Field Histogram) algorithm, and for the network-based robot system, in which it is assumed robot localization information is transmitted through network communication. In this paper, target vector for the VFH algorithm is estimated through the robot localization information and the measurement of its delay by distribution. The delay measurement is performed by time-stamp method. To synchronize all local clocks of the nodes distributed on the network, a global clock synchronization method is adopted. With the delay measurement, the robot localization estimation is performed by calculating the kinematics of the robot. The validation of the proposed algorithm is performed through the performance comparison of the obstacle avoidance between the proposed algorithm and the existing VFH algorithm on the network-based autonomous mobile robot.