• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.4
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• pp.173-180
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• 2006

A key component of autonomous navigation of intelligent home robot is localization and map building with recognized features from the environment. To validate this, accurate measurement of relative location between robot and features is essential. In this paper, we proposed relative localization algorithm based on 3D reconstruction of scale invariant features of two images which are captured from two parallel cameras. We captured two images from parallel cameras which are attached in front of robot and detect scale invariant features in each image using SIFT(scale invariant feature transform). Then, we performed matching for the two image's feature points and got the relative location using 3D reconstruction for the matched points. Stereo camera needs high precision of two camera's extrinsic and matching pixels in two camera image. Because we used two cameras which are different from stereo camera and scale invariant feature point and it's easy to setup the extrinsic parameter. Furthermore, 3D reconstruction does not need any other sensor. And the results can be simultaneously used by obstacle avoidance, map building and localization. We set 20cm the distance between two camera and capture the 3frames per second. The experimental results show :t6cm maximum error in the range of less than 2m and ${\pm}15cm$ maximum error in the range of between 2m and 4m.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.307-309
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• 2012

노드의 위치인식은 M2M 무선센서네트워크에서의 위치에 기반을 둔 여러 응용들을 위해 매우 중요한 문제이다. 센서 네트워크에서의 위치인식은 거리 정보가 사용되느냐 그렇지 않느냐에 따라 range-free와 range-based 기법으로 분류될 수 있는데, 센서노드 특성상 제한된 하드웨어로 동작해야 한다는 점에서 range-free 위치인식 기법이 range-based 기법에 비해 효율적인 방법이라 할 수 있다. DV-Hop은 range-free 위치인식 기법 중 대표적인 것으로서 홉 수와 거리 간 추정을 사용한다. 본 논문에서는 홉 수와 거리 간 추정을 위해 홉 수보다 거리와의 상관도가 높은 홉 수 평균을 사용하여 DV-Hop 에 비해 정확도를 향상시킨 DV-ANHC 알고리즘을 제시한다.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1158-1168
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• 2020

The distance vector-hop wireless sensor node location method is one of typical range-free location methods. In distance vector-hop location method, if a wireless node A can directly communicate with wireless sensor network nodes B and C at its communication range, the hop count from wireless sensor nodes A to B is considered to be the same as that form wireless sensor nodes A to C. However, the real distance between wireless sensor nodes A and B may be dissimilar to that between wireless sensor nodes A and C. Therefore, there may be a discrepancy between the real distance and the estimated hop count distance, and this will affect wireless sensor node location error of distance vector-hop method. To overcome this problem, it proposes a wireless sensor network node location method by modifying the method of distance estimation in the distance vector-hop method. Firstly, we set three different communication powers for each node. Different hop counts correspond to different communication powers; and so this makes the corresponding relationship between the real distance and hop count more accurate, and also reduces the distance error between the real and estimated distance in wireless sensor network. Secondly, distance difference between the estimated distance between wireless sensor network anchor nodes and their corresponding real distance is computed. The average value of distance errors that is computed in the second step is used to modify the estimated distance from the wireless sensor network anchor node to the unknown sensor node. The improved node location method has smaller node location error than the distance vector-hop algorithm and other improved location methods, which is proved by simulations.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.1
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• pp.69-74
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• 2016

A technique for improving estimation accuracy is introduced in order to locate the impact position of artillery shell during the weapon scoring test. Study on localization of impacts using acoustic measurement has been conducted and the usability of sensor array is verified with experiments. When the blast occurs above the ground in the firing range, the acoustic sensor above the ground can measure the directly propagated sound with the ground-reflected one. In this study, a method for reducing estimation error by using the reflection signal measurements based on the time difference of arrival method. Considering the reflection sound works as same as placing a virtual sensor symmetrically through the ground. This idea enables a virtual three-dimensional array configuration with a two-dimensional plane array above the ground as such. The time difference between the direct and the reflected propagations can be estimated using cepstrum analysis. Performance test has been made in the simulation experiment in the football size area.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.1227-1230
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• 2003

In this paper, we propose a pose estimation method using local map acquired from 2d laser range finder information. The proposed method uses extended kalman filter. The state equation is a navigation system equation of Nomad Super Scout II. The measurement equation is a map-based measurement equation using a SICK PLS 101-112 sensor. We describe a map consisting of geometric features such as plane, edge and corner. For pose estimation we scan external environments by laser rage finer. And then these data are fed to kalman filter to estimate robot pose and position. The proposed method enables very fast simultaneous map building and pose estimation.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.87-93
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• 2019

This paper presents a 6-DOF relocalization using a 3D laser scanner and a monocular camera. A relocalization problem in robotics is to estimate pose of sensor when a robot revisits the area. A deep convolutional neural network (CNN) is designed to regress 6-DOF sensor pose and trained using both RGB image and 3D point cloud information in end-to-end manner. We generate the new input that consists of RGB and range information. After training step, the relocalization system results in the pose of the sensor corresponding to each input when a new input is received. However, most of cases, mobile robot navigation system has successive sensor measurements. In order to improve the localization performance, the output of CNN is used for measurements of the particle filter that smooth the trajectory. We evaluate our relocalization method on real world datasets using a mobile robot platform.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2033-2038
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• 2003

This paper describes an integrated navigation strategy for the autonomous service robot PSR. The PSR is under development at the KIST for service tasks in indoor public environments. The PSR is a multi-functional mobile-manipulator typed agent, which works in daily life. Major advantages of proposed navigation are as follows: 1) Structured control architecture for a systematic integration of various software modules. A Petri net based configuration design enables stable control flow of a robot. 2) A range sensor based generalized scheme of navigation. Any range sensor can be selectively applied using the proposed navigation scheme. 3) No need for modification of environments. (No use of artificial landmarks.) 4) Hybrid approaches combining reactive behavior as well as deliberative planner, and local grid maps as well as global topological maps. A presented experimental result shows that the proposed navigation scheme is useful for mobile service robot in practical applications.

• Smart Media Journal
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• v.8 no.4
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• pp.85-90
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• 2019

The Ultra-Wide Band sensor is widely used as a wireless indoor localization technology with frequency bands in the GHz range. Meanwhile, in museums, not only the real-time location of visitors but also information on visit route and duration time is required for patrons' behavior analysis. In this paper, the analysis system based Ultra-Wide Band radar for visitor's viewing behavior is introduced and experimented in the real environment. We built the system in National Museum of Korea, and its 22 Ultra-Wide Band radar sensors receive the real-time location of their visitors: this analyzes the visit route and visit time for patrons.

• ETRI Journal
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• v.43 no.4
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• pp.603-616
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• 2021

Over the last few years, autonomous vehicles have progressed very rapidly. The odometry technique that estimates displacement from consecutive sensor inputs is an essential technique for autonomous driving. In this article, we propose a fast, robust, and accurate odometry technique. The proposed technique is light detection and ranging (LiDAR)-based direct odometry, which uses a spherical range image (SRI) that projects a three-dimensional point cloud onto a two-dimensional spherical image plane. Direct odometry is developed in a vision-based method, and a fast execution speed can be expected. However, applying LiDAR data is difficult because of the sparsity. To solve this problem, we propose an SRI generation method and mathematical analysis, two key point sampling methods using SRI to increase precision and robustness, and a fast optimization method. The proposed technique was tested with the KITTI dataset and real environments. Evaluation results yielded a translation error of 0.69%, a rotation error of 0.0031°/m in the KITTI training dataset, and an execution time of 17 ms. The results demonstrated high precision comparable with state-of-the-art and remarkably higher speed than conventional techniques.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.1
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• pp.114-120
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• 2013

Recently, navigation systems based on wireless communication have been applied to the internal structures such as building or ship. If a stable azimuth information is obtained, these systems can effectively guide the direction of the user's progress through the information and then can improve the performance of guidance. Since conventional method which has acquired an azimuth information using geomagnetic and acceleration sensor(azimuth sensor hereafter) is sensitive to the effects of the magnetic field, it has unstable error range according to the surrounding environment. In order to improve these problems, this paper presents a new relative azimuth estimation algorithm using the displacement of a mobile node and its rotation angle based on Wireless communication. For the performance assessment of the proposed algorithm, experiments using rotating arm are performed and the results are confirmed that the proposed system can estimate the relative azimuth without using additional sensors.