• Journal of the Korean Society of Industry Convergence
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• v.20 no.4
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• pp.299-305
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• 2017

This study proposes a new technique to design and control of robot hand gripper for assembling and disassembling of a machine parts. The motion equation describing dynamics of the manipulators and object together with geometric constraint is formulated by Lagrange-Euler's equation. And the problems of controlling both the grasping force and the rotation angle of the grasped object under the constraints are analyzed. The effect of geometric constraints and a method of computer simulation for overall system is verified. Finally, it is illustrated that even in case of there exists a sensory feedback from sensing data of the rotational angle of the object to command inputs control of joint and this feedback connection from sensing data to control grasping of machinery parts.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.155-162
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• 2012

In this paper, we proposed a method of improving the location estimation error existing in RTLS (Real Time Location Service) system for the mobility individual. According as Ubiquitous comes, interest for indoor location tracking system was more increased socially. However, existing indoor location tracking system doesn't correspond actively in frequent change of indoor environment, and there is a problem that correct location measurement of transfer object is difficult by NLOS property of indoor environment. Purpose of this paper proposes environment accommodation location tracking system that is improved location precision of transfer object and grasps location of indoor transfer object effectively that is essential element effectively to provide service to satisfy various user's request according as Ubiquitous comes.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.357-362
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• 2019

This paper proposes a model and train method that can real-time detect objects and distances estimation based on a monocular camera by applying deep learning. It used YOLOv2 model which is applied to autonomous or robot due to the fast image processing speed. We have changed and learned the loss function so that the YOLOv2 model can detect objects and distances at the same time. The YOLOv2 loss function added a term for learning bounding box values x, y, w, h, and distance values z as 클래스ification losses. In addition, the learning was carried out by multiplying the distance term with parameters for the balance of learning. we trained the model location, recognition by camera and distance data measured by lidar so that we enable the model to estimate distance and objects from a monocular camera, even when the vehicle is going up or down hill. To evaluate the performance of object detection and distance estimation, MAP (Mean Average Precision) and Adjust R square were used and performance was compared with previous research papers. In addition, we compared the original YOLOv2 model FPS (Frame Per Second) for speed measurement with FPS of our model.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.556-562
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• 2000

This paper presents new sensitivity analysis algorithm for the dynamic response of three dimensional rectilinear type structure. This method is derived from a combination of the transfer stiffness coefficient method(TSCM) and the Newmark method. We developed dynamic response analysis algorithm by TSCM. This method has more safe computational precision and time than transfer matrix method(TMM). We defined new design variable and object function, and computated simple three dimensional computation model by TSCM. The presented analysis algorithm was validated by results of changing design variable.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.237-250
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• 2022

In this study, we propose a method to estimate the biomass of invertebrate grazers from the videos with underwater drones by using a multi-object tracking model based on deep learning. In order to detect invertebrate grazers by classes, we used YOLOv5 (You Only Look Once version 5). For biomass estimation we used DeepSORT (Deep Simple Online and real-time tracking). The performance of each model was evaluated on a workstation with a GPU accelerator. YOLOv5 averaged 0.9 or more mean Average Precision (mAP), and we confirmed it shows about 59 fps at 4 k resolution when using YOLOv5s model and DeepSORT algorithm. Applying the proposed method in the field, there was a tendency to be overestimated by about 28%, but it was confirmed that the level of error was low compared to the biomass estimation using object detection model only. A follow-up study is needed to improve the accuracy for the cases where frame images go out of focus continuously or underwater drones turn rapidly. However,should these issues be improved, it can be utilized in the production of decision support data in the field of invertebrate grazers control and monitoring in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.813-815
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• 2011

This study inspects the fault of the vehicle forming assembly and the assembly state of components at high speed and high degree of precision. This study also proposes the general inspection system capable of adapting to a number of products. The inspection program is composed of the fault inspection algorithm to examine the surface of the object and the state of the assembly and the high speed procession algorithm for the real time examination. The fault inspection algorithm is processed largely by a method using average of pixel in ROI and a method dividing the area and checking the presence of the object. Lastly, we verified the efficiency of the sysytem through the evaluation of its accuracy and processing time.

• Journal of Korean Association for Spatial Structures
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• v.21 no.3
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• pp.25-34
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• 2021

This study develops a new device system for measuring a slope of object with non-adhesive, non-contact and non-face-to-face, namely Inclinometer Slope Laser Measuring (ISLM), that is applicable in the field. This system includes cradle, laser, camera, and computer and the filming and is performed after laser projection at programmed intervals. After measuring the amount of displacement converted to numerical values, these values can then be transferred to the office using the selected data transmission method. The obtained results from the test carried out to verify the reliability of the ISLM system indicated that the ISLM system can measure with accurately level of 0.1mm/Pixel at 1m distance and when increasing the camera resolution, the precision might increase proportionally. Therefore, the proposed measure system may widely apply on-site for various constructions, especially, in the case of object with very high surface temperature where exhibits difficulty to directly measure the adjacent structures. However, due to the sensitive reaction to the illuminance, this method can be applied with caution at times of large changes in illuminance, such as at dawn and at dusk.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.167-175
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• 2020

In this paper, we propose a traffic accident detection on vehicle-mounted camera. In the proposed method, the minimum bounding box coordinates the central coordinates on the bird's eye view and motion vectors of each vehicle object, and ego-motions of the vehicle equipped with dash-cam are extracted from the dash-cam video. By using extracted 4 kinds features as the input of Bi-LSTM (bidirectional LSTM), the accident probability (score) is predicted. To investigate the effect of each input feature on the probability of an accident, we analyze the performance of the detection the case of using a single feature input and the case of using a combination of features as input, respectively. And in these two cases, different detection models are defined and used. Bi-LSTM is used as a cascade, especially when a combination of the features is used as input. The proposed method shows 76.1% precision and 75.6% recall, which is superior to our previous work.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.119-125
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• 2023

Through the Ukraine-Russia war, the military importance of drones is being reassessed, and North Korea has completed actual verification through a drone provocation towards South Korea at 2022. Furthermore, North Korea is actively integrating artificial intelligence (AI) technology into drones, highlighting the increasing threat posed by drones. In response, the Republic of Korea military has established Drone Operations Command(DOC) and implemented various drone defense systems. However, there is a concern that the efforts to enhance capabilities are disproportionately focused on striking systems, making it challenging to effectively counter swarm drone attacks. Particularly, Air Force bases located adjacent to urban areas face significant limitations in the use of traditional air defense weapons due to concerns about civilian casualties. Therefore, this study proposes a new passive air defense method that aims at disrupting the object detection capabilities of AI models to enhance the survivability of friendly aircraft against the threat posed by AI based swarm drones. Using laser-based adversarial examples, the study seeks to degrade the recognition accuracy of object recognition AI installed on enemy drones. Experimental results using synthetic images and precision-reduced models confirmed that the proposed method decreased the recognition accuracy of object recognition AI, which was initially approximately 95%, to around 0-15% after the application of the proposed method, thereby validating the effectiveness of the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.8
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• pp.40-47
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• 2001

Optical measurement methods make it possible to detect object displacements with high resolution and noncontact measurements. Also, they are very robust against EMI noises and have long operation range. An optical triangulation sensor is one of widely used displacement measurement sensors for its sub-micron resolution, fast response, simple structure, and low cost. However. there are several errors caused by inclinations of a surface. speckle effects, power fluctuations of light sources, and noises of detectors. In this paper, in order to minimize error effects, we performed error analysis and proposed a new structure. Then, we setup a new modeling method and verify it through simulations and experiments. Based on the new model. we propose a new sensor structure and establish design criteria. Finally, we design a signal processing system to overcome a resolution-limited problem of light detectors. The resolution of the proposed system is 0.2${\mu}{\textrm}{m}$ in 5mm operating range.