• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.24-31
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• 2020

Alternative navigation in underwater environments is essential to prevent accumulating drift error of dead reckoning. In case of using an external positioning system, the installation and management process of the transmission station is cumbersome, and the operation range of underwater vehicle is limited. In order to solve this problem, navigation using geophysical information such as terrain, geomagnetic field and gravity can be used. Unlike the terrain, geomagnetic field and gravity are composed of 3-D information, so continuation process is required. In this paper, we present a integrated navigation algorithm using multiple geophysical information for long-term operation of UUV. The proposed algorithm is verified through numerical simulation in an artificially generated environments. As a result, integrated navigation showed higher navigation accuracy than single alternative navigation.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.2
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• pp.133-138
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• 2011

RFID system can be used to improve object recognition, map building and localization for robot area. A novel method of indoor navigation system for a mobile robot is proposed using RFID technology. The mobile robot With a RFID reader and antenna is able to find what obstacles are located where in circumstance and can build the map similar to indoor circumstance by combining RFID information and distance data obtained from sensors. Using the map obtained, the mobile robot can avoid obstacles and finally reach the desired goal by $A^*$ algorithm. 3D map which has the advantage of robot navigation and manipulation is able to be built using z dimension of products. The proposed robot navigation system is proved to apply for SLAM and path planning in unknown circumstance through numerous experiments.

• Journal of Advanced Navigation Technology
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• v.17 no.2
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• pp.247-254
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• 2013

The task of 3D gesture recognition for controlling equipments is highly challenging due to the propagation of 3D smart TV recently. In this paper, the AdaBoost algorithm is applied to 3D gesture recognition by using Kinect sensor. By tracking time interval trajectory of hand, wrist and arm by Kinect, AdaBoost algorithm is used to train and classify 3D gesture. Experimental results demonstrate that the proposed method can successfully extract trained gestures from continuous hand, wrist and arm motion in real time.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.454-460
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• 2003

while they cannot overcome the limitation that arises in the process of representing the 3D real world to the 2D plane. Also, there exists requirements on performance to support realtime navigation capability.In this paper, therefore, we propose a cell loading algorithm for navigating virtual space that can support realtime visualization according to the multimedia objects in variety and the change of the view point by user, and that can accommodate the capacity imposed in the process of navigation regardless of the number of objects.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2211-2216
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• 2005

This paper describes a novel navigation algorithm using a locomotion interface with two 6-DOF parallel robotic manipulators. The suggested novel navigation system can induce user's real walking and generate realistic visual feedback during navigation, using robotic manipulators. For realistic visual feedback, the virtual environment is designed with three components; 3D object modeler for buildings and terrains, scene manager and communication manager component. The walking velocity of the user is directly translated to VR actions for navigation. Finally, the functions of the RPC interface are utilized for each interaction mode. The suggested navigation system can allow a user to explore into various virtual terrains with real walking and realistic visual feedback.

• Spatial Information Research
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• v.15 no.4
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• pp.363-370
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• 2007

This study has been carried for the development of the basic algorithm of helicopter navigation system based on TRN (Terrain Referenced Navigation) with information input from the GPS. The helicopter determines flight path due to Origination-Destination analysis on the Cartesian coordinate system of 3-D DTM. This system shows 3-D mesh map and the O-D flight path profile for the pilot's acknowledgement of the terrain, at first. The system builds TCF (terrain clearance floor) far the buffer zone upon the surface of ground relief to avid the ground collision. If the helicopter enters to the buffer zone during navigation, the real-time warning message which commands to raise the body pops up using Matlab menu. While departing or landing, control of the height of the body is possible. At present, the information (x, y, z coordinates) from the GPS is assumed to be input into the system every 92.8 m of horizontal distance while navigating along flight path. DTM of 3" interval has been adopted from that which was provided by ChumSungDae Co., Ltd..

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1208-1211
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• 1996

In this paper, an efficient and robust robot path planning technique is discussed. Concentric Ripple Edge Evaluation and Progression( CREEP ) algorithm[1] has been elaborated and expanded to carry out 3-D path planning. Like the 2-D case, robot can always find a path, if one exists, in a densely cluttered, unknown and unstructured 3-D obstacle environment. 3-D space in which the robot is expected to navigate is modeled by stacking cubic cells. The generated path is resolution optimal once the terrain is fully explored by the robot or all the information about the terrain is given. Path planning times are significantly reduced by local path update. Accuracy and efficiency of wave propagation in CREEP algorithm are achieved by virtual concentric sphere wave propagation. Simulations in 2-D and 3-D spaces are performed and excellent results are demonstrated.

• ETRI Journal
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• v.45 no.5
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• pp.836-846
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• 2023

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.

• Bulletin of the Korean Space Science Society
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• 2008.10a
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• pp.34.3-34.3
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• 2008

Relative navigation system is presented using measurements from a single-channel global positioning system (GPS) simulator. The objective of this study is to provide real-time relative navigation results as well as absolute navigation results for two formation flying satellites separated about 1km in low earth orbit. To improve the performance, more accurate dynamic model and modified relative measurement model are developed. This modified method prevents non-linearity of the measurement model from degrading precision by applying linearization about the states from absolute navigation algorithm not about a priori states. Furthermore, absolute states are obtained using ion-free GRAPHIC pseudo-ranges and precise relative states are provided using double differential carrier-phase data based on Extended Kalman Filter. The software-based simulation is performed and achieved meter-level precision for absolute navigation and millimeter-level precision for relative navigation. The absolute and relative accuracies at steady state are about 0.77m and 4mm respectively (3D, r.m.s.). In addition, Integer ambiguity algorithm (LAMBDA method) improves simulation performances.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.6
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• pp.358-366
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• 2006

This paper describes a novel navigation algorithm using a locomotion interface with two 6-DOF programmable foot platforms. When a human walks on the locomotion interface (LI), the walking motions of the human are recognized by several sensors. Then, the sensed information is used by the LI for generation of infinite surfaces for continuous walking and the virtual environments for scene update according to motions of the human walking. The suggested novel navigation system can induce user's real walking and generate realistic visual feedback during navigation. A novel navigation algorithm is suggested to allow natural navigation in virtual environments by utilizing conditions of normal gait analysis. For realistic visual feedback, the virtual environment is designed with three components; 3D object modeler for buildings and terrains, scene manager and communication manager component. From experiments, the subjects were satisfied with the reality of the suggested navigation algorithm using the locomotion interface. Therefore, the suggested navigation system can allow a user to explore into various virtual terrains with real walking and realistic visual feedback.