• Journal of Positioning, Navigation, and Timing
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• v.1 no.1
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• pp.35-43
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• 2012

The UGV is one of the special field robot developed for mine detection, surveillance and transportation. To achieve successfully the missions of the UGV, the accurate and reliable navigation data should be provided. This paper presents design and implementation of multi-sensor-based open architecture integrated navigation for localization of UGV. The presented architecture hierarchically classifies the integrated system into four layers and data communications between layers are based on the distributed object oriented middleware. The navigation manager determines the navigation mode with the QoS information of each navigation sensor and the integrated filter performs the navigation mode-based data fusion in the filtering process. Also, all navigation variables including the filter parameters and QoS of navigation data can be modified in GUI and consequently, the user can operate the integrated navigation system more usefully. The conventional GPS/INS integrated system does not guarantee the long-term reliability of localization when GPS solution is not available by signal blockage and intentional jamming in outdoor environment. The presented integration algorithm, however, based on the adaptive federated filter structure with FDI algorithm can integrate effectively the output of multi-sensor such as 3D LADAR, vision, odometer, magnetic compass and zero velocity to enhance the accuracy of localization result in the case that GPS is unavailable. The field test was carried out with the UGV and the test results show that the presented integrated navigation system can provide more robust and accurate localization performance than the conventional GPS/INS integrated system in outdoor environments.

• Spatial Information Research
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• v.16 no.4
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• pp.455-465
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• 2008

Augmented reality (AR) has tremendous potential in visualizing geospatial information, especially on the actual physical scenes. However, to utilize augmented reality in mobile system, many researches have undergone with GPS or ubiquitous marker based approaches. Although there are several papers written with vision based markerless tracking, previous approaches provide fairly good results only in largely under "controlled environments." Localization and tracking of current position become more complex problem when it is used in indoor environments. Many proposed Radio Frequency (RF) based tracking and localization. However, it does cause deployment problems of large RF-based sensors and readers. In this paper, we present a noble markerless AR approach for indoor (possible outdoor, too) navigation system only using monoSLAM (Monocular Simultaneous Localization and Map building) algorithm to full-fill our grand effort to develop mobile seamless indoor/outdoor u-GIS system. The paper briefly explains the basic SLAM algorithm, then the implementation of our system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.8
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• pp.750-757
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• 2011

Wireless Sensor Network is composed of a lot of sensor nodes that are densely deployed in a field. So generally this sensor nodes are spreaded using Helicopter or Fixed wing. Each node delivers own location and acquired information to user when it detects specific events. In this paper, we propose localization algorithm without range information in wireless sensor network using helicopter. Helicopter broadcasts periodically beacon signal for sensor nodes. Sensor nodes stored own memory this beacon signal until to find another beacon point(satisfied special condition). This paper develops a localization mechanism using the geometry conjecture(perpendicular bisector of a chord) to know own location. And the simulation results demonstrate that our localization scheme outperforms Centroid, APIT in terms of a higher location accuracy.

• Journal of IKEEE
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• v.24 no.1
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• pp.40-45
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• 2020

In this paper, we consider an efficient design of quantizers at sensor nodes for sequence-based localization (SBL) systems which recently show a competitive performance for in-door positioning, Since SBL systems locate targets by partitioning the sensor field into subregions, each with an unique sequence number, we use the distance samples between sensors and the sequences for quantizer design in order to propose a low weight design process. Furthermore, we present a new cost function devised to assign the number of samples and the number of unique sequences uniformly into each of quantization partitions and design quantizers by searching the quantization partitions and codewords that minimize the cost function. We finally conduct experiments to demonstrate that the proposed algorithm offers an outstanding localization performance over typical designs while maintaining a substantial reduction of design complexity.

• The Journal of the Acoustical Society of Korea
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• v.35 no.1
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• pp.35-41
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• 2016

Based on correlation and least square method, a closed-form algorithm for estimating the location of mixed far-field and near-field source is presented using the Uniform Circular Array (UCA). Recently, for a homogeneous circular arrangement case, a correlation based closed-form algorithm is proposed to estimate 2-D angle (azimuth, elevation) and the extended algorithm is proposed to 3-D location (azimuth, elevation, range). These algorithms assume the far-field source or near-field source only. Therefore, for mixed source localization, the proposed algorithm estimates source location with the assumption of far-field source, and then estimates the range to distinguish the far-field from the near-field source. For both cases, numerical experiments have been performed, which confirmed the validity of the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.49-59
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• 2008

SIFT(Scale Invariant Feature Transform) is an algorithm to extract vectors at pixels around keypoints, in which the pixel colors are very different from neighbors, such as vortices and edges of an object. The SIFT algorithm is being actively researched for various image processing applications including 3-D image constructions, and its most computation-intensive stage is a keypoint localization. In this paper, we develope a fixed-point model of the keypoint localization and propose its efficient hardware architecture for embedded applications. The bit-length of key variables are determined based on two performance measures: localization accuracy and error rate. Comparing with the original algorithm (implemented in Matlab), the accuracy and error rate of the proposed fixed point model are 93.57% and 2.72% respectively. In addition, we found that most of missing keypoints appeared at the edges of an object which are not very important in the case of keypoints matching. We estimate that the hardware implementation will give processing speed of $10{\sim}15\;frame/sec$, while its fixed point implementation on Pentium Core2Duo (2.13 GHz) and ARM9 (400 MHz) takes 10 seconds and one hour each to process a frame.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.1
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• pp.15-21
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• 2011

In the range-based localization, the localization accuracy will be high dependent on the accuracy of distance measurement between two nodes. The received signal strength(RSS) is one of the simplest methods of distance measurement, and can be easily implemented in a ranging-based method. However, a RSS-based localization scheme has few problems. One problem is that the signal in the communication channel is affected by many factors such as fading, shadowing, obstacle, and etc, which makes the error of distance measurement occur and the localization accuracy of sensor node be low. The other problem is that the sensor node estimates its location for itself in most cases of the RSS-based localization schemes, which makes the sensor network life time be reduced due to the battery limit of sensor nodes. Since beacon nodes usually have more resources than sensor nodes in terms of computation ability and battery, the beacon node based localization scheme can expand the life time of the sensor network. In this paper, therefore we propose a beacon node based localization algorithm using received signal strength(RSS) and path loss calibration in order to overcome the aforementioned problems. Through simulations, we prove the efficiency of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.318-326
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• 2013

In this paper, a novel WUSB (Wireless USB) over WBAN (Wireless Body Area Networks) MAC protocol is proposed to improve efficiency of sensing the personal information. Furthermore, a localization technique based on that protocol is also proposed for indoor localization in a ship. For this purpose, the proposed localization algorithm minimizes power consumption and estimates location with accuracy. It is executed independently at each sensor node on the basis of WUSB over WBAN protocol. And it minimizes power consumption by estimating locations of sensor nodes without GPS (Global Positioning Systems).

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.674-684
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• 2011

More and more elderly and disabled people are using electric scooters instead of electric wheelchairs because of higher mobility. However, people with high levels of impairment or the elderly still have difficulties in driving the electric scooters safely. Semi-autonomous electric scooter system is one of the solutions for the safety: Either manual driving or autonomous driving can be used selectively. In this paper, we implement a semi-autonomous electric scooter system with functions of localization and path following. In order to recognize the pose of electric scooter in outdoor environments, we design an outdoor localization system based on the extended Kalman filter using DGPS (Differential Global Positioning System) and wheel encoders. We added an accelerometer to make the localization system adaptable to road condition. Also we propose a path following algorithm using two arcs with current pose of the electric scooter and a given path in the map. Simulation results are described to show that the proposed algorithms provide the ability to drive an electric scooter semi-autonomously. Finally, we conduct outdoor experiments to reveal the practicality of the proposed system.

• Journal of Ocean Engineering and Technology
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• v.19 no.2 s.63
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• pp.74-81
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• 2005

A 3-D localization method of an autonomous underwater vehicle (AUV) has been developed, which can solve the limitations oj the conventional localization, such as LBL or SBL that reduces the flexibility and availability of the AUV. The system is composed of a mother ship (small unmanned marine prober) on the surface of the water and an unmanned underwater vehicle in the water. The mother ship is equipped with a digital compass and a GPS for position information, and an extended Kalman filter is used for position estimation. For the localization of the AUV, we used only non-inertial sensors, such as a digital compass, a pressure sensor, a clinometer, and ultrasonic sensors. From the orientation and velocity information, a priori position of the AUV is estimated by applying the dead reckoning method. Based on the extended Kalman filter algorithm, a posteriori position of the AUV is, then, updated by using the distance between the AUV and a mother ship on the surface of the water, together with the depth information from the pressure sensor.