• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.7-13
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• 2015

Unmanned air vehicles (UAVs) are getting popular not only as a private usage for the aerial photograph but military usage for the surveillance, reconnaissance and supply missions. For an UAV to successfully achieve these kind of missions, geolocation (localization) must be implied to track an interested target or fly by reference. In this research, we adopted multi-sensor fusion (MSF) algorithm to increase the accuracy of the geolocation and verified the algorithm using two multicopter UAVs. One UAV is equipped with an optical camera, and another UAV is equipped with an optical camera and a laser range finder. Throughout the experiment, we have obtained measurements about a fixed ground target and estimated the target position by a series of coordinate transformations and sequential Kalman filter. The result showed that the MSF has better performance in estimating target location than the case of using single sensor. Moreover, the experimental result implied that multi-sensor geolocation algorithm is able to have further improvements in localization accuracy and feasibility of other complicated applications such as moving target tracking and multiple target tracking.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.353-361
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• 2011

A precise embedded ultrasonic localization system is developed for autonomous mobile robots in indoor environments, which is essential for autonomous navigation of mobile robots with various tasks. Although ultrasonic sensors are more cost-effective than other sensors such as LRF (Laser Range Finder) and vision, they suffer inaccuracy and directional ambiguity. First, we apply the matched filter to measure the distance precisely. For resolving the computational complexity of the matched filter for embedded systems, we propose a new matched filter algorithm with fast computation in three points of view. Second, we propose an accurate ultrasonic localization system which consists of three ultrasonic receivers on the mobile robot and two or more transmitters on the ceiling. Last, we add an extended Kalman filter to estimate position and orientation. Various simulations and experimental results show the effectiveness of the proposed system.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.243-250
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• 2012

This paper proposes a 3D map-building algorithm using one LRF (Laser Range Finder) while a mobile robot is navigating on the slanted surface. There are several researches on 3D map buildings using the LRF. However most of them are performing the map building only on the flat surface. While a mobile robot is moving on the slanted surface, the view angle of LRF is dynamically changing, which makes it very difficult to build the 3D map using encoder data. To cope with this dynamic change of the view angle in build 3D map, IMU and balance filters are fused to correct the unstable encoder data in this research. Through the real navigation experiments, it is verified that the fusion of multiple sensors are properly performed to correct the slope angle of the slanted surface. The effectiveness of the balance filter are also checked through the hill climbing navigations.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.2
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• pp.160-167
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• 2016

This paper reports a localization method of a mobile robot using ceiling image. The ceiling has landmarks which are not distinguishablefrom one another. The location of every landmark in a map is given a priori while correspondence is not given between a detected landmark and a landmark in the map. Only the initial pose of the robot relative to the landmarks is given. The method uses particle filter approach for localization. Along with estimating robot pose, the method also associates a landmark in the map to a landmark detected from the ceiling image. The method is tested in an indoor environment which has circular landmarks on the ceiling. The test verifies the feasibility of the method in an environment where range data to walls or to beacons are not available or severely corrupted with noise. This method is useful for localization in a warehouse where measurement by Laser range finder and range data to beacons of RF or ultrasonic signal have large uncertainty.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.315-327
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• 2017

In this paper, we present a method for estimating of position and velocity of a moving target by using the range and the bearing measurements from multiple sensors of aiming unit. In many cases, conventional low cost gyro sensor and a portable laser range finder(LRF) degrade the accuracy of estimation. To enhance these problems, we propose two methods. The first is background image tracking and the other is principal component analysis (PCA). The background tracking is used to assist the low cost gyro censor. And the PCA is used to cope with the problems of a portable LRF. In this paper, we prove that our method is robust with respect to low-frequency, biased and noisy inputs. We also present a comparison between our method and the extended Kalman filter(EKF).

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.379-385
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• 2012

This paper developes the navigation visual aid supporting a watch officer's situation awareness and analyzes its performance test result. Developing the equipment made from composite video sensor which transfer video signal, ranger laser measurement model which search out distance, Pan/ Tilt, center control device. The developed equipment with Pan/Tilt was made from high performance video sensor and ranger laser measurement. To make a real ship test, we carried on setting the developed equipment on ship, observed a danger factor and analyzed a image, and from that we can evaluate marine environment awareness. Through this result, the developed equipment can show effective ability of the awareness of the clearer check and resolution situation when compare with the binocular.

• Journal of Advanced Navigation Technology
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• v.3 no.2
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• pp.97-107
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• 1999

Passive sensors such as Laser Range Finder(LRF) and Forward Looking Infrared(FLIR) camera frequently used for tracking aircraft landing produce the measurements of elevation angle contaminated by large noise due to the exhaust plume disturbance. This results in poor tracking performance if the extended Kalman filter is used for estimation of the range and elevation which are corrupted by the non-Gaussian noise such as plume disturbance. In this paper, an adaptive estimation filter and the extended Kalman filter is combined to produce a combination-type filter. In this approach the adaptive filter is used for the plume-type disturbance noise and the extended Kalman filter is utilized for the measurement of Gaussian type. The proposed combination filter is effective for the trajectory estimation of landing aircraft under the influence of unknown bias and numerical simulations illustrate the performance of the proposed filter.

• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.121-129
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• 2009

This paper presents a goal-directed reactive obstacle avoidance method based on lane method. The reactive collision avoidance is necessarily required for a robot to navigate autonomously in dynamic environments. Many methods are suggested to implement this concept and one of them is the lane method. The lane method divides the environment into lanes and then chooses the best lane to follow. The proposed method does not use the discrete lane but chooses a line closest to the original target line without collision when an obstacle is detected, thus it has a merit in the aspect of running time and it is more proper for narrow corridor environment. If an obstacle disturbs the movement of a robot by blocking a target path, a robot generates a temporary target line, which is parallel to an original target line and tangential to an obstacle circle, to avoid a collision with an obstacle and changes to and follows that line until an obstacle is removed. After an obstacle is clear, a robot returns to an original target line and proceeds to the goal point. Obstacleis recognized by laser range finder sensor and represented by a circle. Our method has been implemented and tested in a corridor environment and experimental results show that our method can work reliably.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.199-206
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• 2021

This paper describes the feasibility and reliability verification of installing a protective structure to protect attack periscopes. The attack periscope is the critical equipment of a submarine to enable the user to monitor surface and air activity, collect navigational data, and detect and identify targets. The attack periscope provides target information acquired through TV, IR camera, and laser range finder to the combat system. In the product improvement program, the upper part of the masts was exposed to the outside of the sail because the existing attack periscope was replaced with a new one. On the other hand, the head sensor can be damaged by floating objects, such as fishing nets, during sea navigation. Therefore, the installation of a protective structure for an attack periscope improved the equipment operation performance. The feasibility and reliability of the installation of the protective structure were verified by examining the influence of URN.