• Journal of Satellite, Information and Communications
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• v.10 no.3
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• pp.32-37
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• 2015

Unmaned Aerial Vehical(UAV) is a flight which is automatically flying by remote control on th ground. However UAV has an advantage of control that is easy, but has an disadvantage of not hovering. By comparison, quadcopter which is one of the UAV is easily operated. Also quadcopter has hovering function and high stability. In this paper, we propose stable flight algorithm associated PID(proportional-integral-derivative) control with fuzzy contorl to implement stable quadcopter system. After getting a positioning information of the drone, This proposed system is implemented for stable flight through flight attitude control using gyro and acceleration sensor. We also propose the flight mode system to hover drone with GPS sensor.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.213-220
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• 2008

This paper analyzes a broadcasting technique for wireless multi-hop sensor networks that uses a form of cooperative diversity called opportunistic large arrays (OLAs). We propose a method for autonomous scheduling of the nodes, which limits the nodes that relay and saves as much as 32% of the transmit energy compared to other broadcast approaches, without requiring global positioning system (GPS), individual node addressing, or inter-node interaction. This energy-saving is a result of cross-layer interaction, in the sense that the medium access control (MAC) and routing functions are partially executed in the physical (PHY) layer. Our proposed method is called OLA with a transmission threshold (OLA-T), where a node compares its received power to a threshold to decide if it should forward. We also investigate OLA with variable threshold (OLA-VT), which optimizes the thresholds as a function of level. OLA-T and OLA-VT are compared with OLA broadcasting without a transmission threshold, each in their minimum energy configuration, using an analytical method under the orthogonal and continuum assumptions. The trade-off between the number of OLA levels (or hops) required to achieve successful network broadcast and transmission energy saved is investigated. The results based on the analytical assumptions are confirmed with Monte Carlo simulations.

• Journal of Sensor Science and Technology
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• v.25 no.3
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• pp.202-207
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• 2016

Estimation of vertical position is critical in applications of sports science and fall detection and also controls of unmanned aerial vehicles and motor boats. Due to low accuracy of GPS(global positioning system) in the vertical direction, the integration of IMU(inertial measurement unit) with the GPS is not suitable for the vertical position estimation. This paper investigates an IMU-barometer integration for estimation of vertical position (as well as vertical velocity). In particular, a new two-step Kalman/complementary filter is proposed for accurate and efficient estimation using 6-axis IMU and barometer signals. The two-step filter is composed of (i) a Kalman filter that estimates vertical acceleration via tilt orientation of the sensor using the IMU signals and (ii) a complementary filter that estimates vertical position using the barometer signal and the vertical acceleration from the first step. The estimation performance was evaluated against a reference optical motion capture system. In the experimental results, the averaged estimation error of the proposed method was 19.7 cm while that of the raw barometer signal was 43.4 cm.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.6
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• pp.74-80
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• 2009

Path tracking of unmanned vehicle is a basis of autonomous driving and navigation. For the path tracking, it is very important to find the exact position of a vehicle. GPS is used to get the position of vehicle and a direction sensor and a velocity sensor is used to compensate the position error of GPS. To detect path lines in a road image, the bird's eye view transform is employed, which makes it easy to design a lateral control algorithm simply than from the perspective view of image. Because the driving speed of vehicle should be decreased at a curved lane and crossroads, so we suggest the speed control algorithm used GPS and image data. The control algorithm is simulated and experimented from the basis of expert driver's knowledge data. In the experiments, the results show that bird's eye view transform are good for the steering control and a speed control algorithm also shows a stability in real driving.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.3
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• pp.253-259
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• 2014

There has been a need for replacing human labors with a robot in such dangerous and hard jobs of various construction sites. For that reason, many researches have been made about the high quality robot, which performs its duty instead of human labors. This study is about auto surveying system development based on VRS-GPS which enables autodriving in dangerous areas where it's difficult for humans to measure directly. This study is about the auto-surveying system development, based on VRS-GPS, which enables auto-drive in dangerous areas, whereas difficult for humans to measure directly. The GPS is made with GRXI and SHC250 controllers of the SOKKIA company. The auto surveying system is composed of DPS module, geomagnetism sensor, bluetooth, gimbals, IMU, etc to automatic drive via enter into a route of position. The developed auto surveying system has installed the carmeras for front and vertical axis as well as systems to grasp situation of surveying with smartphone in real time. The result from analysed RMSE of auto surveying system and VRS-GPS surveying is 0.0169m of X-axis and 0.0246m of Y-axis.

• Laser Solutions
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• v.12 no.1
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• pp.19-24
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• 2009

Because of its fast and precise welding performance, laser welding is becoming a new excellent welding method. However, the precise focusing and robust seam tracking are required to apply laser welding to the practical fields. In order to laser weld a type of T joint like a circular pipe on a square pipe, which could be met in the three dimensional structure such as an aluminum space frame, a visual sensor system was developed for automation of focusing and seam tracking. The developed sensor system consists of a digital CCD camera, a structured laser, and a vision processor. It is moved and positioned by a 2-axis motorized stage, which is attached to a 6 axis robot manipulator with a laser welding head. After stripe-type structured laser illuminates a target surface, images are captured through the digital CCD camera. From the image, seam error and defocusing error are calculated using image processing algorithms which includes efficient techniques handling continuously changed image patterns. These errors are corrected by the stage off-line during welding or teaching. Laser welding of a circular pipe on a square pipe was successful with the vision tracking system by reducing the path positioning and de focusing errors due to the robot teaching or a geometrical variation of specimens and jig holding.

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.33-34
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• 2012

무선 센서 네트워크의 다양한 응용에 있어 센서 노드의 지리학적 위치 측정은 매우 중요하다. 이를 위해 비-거리(Range-Free) 기반 위치 측정 기법에 대한 연구가 활발하게 진행 중이며, 비 균일 네트워크 환경에서 위치 정확도를 향상하기 위한 밀집 확률 기반의 위치 측정 기법이 제안되었다. 밀집 확률 기반의 위치 측정 기법에서 추정 거리 산출 시 노드 통신 반경 내 1-홉 거리는 모두 동일한 값을 갖는데 이는 반경 내 가까운 이웃 노드와 먼 이웃 노드가 있어도 모두 같은 거리로 추정하기 때문에 위치 측정 시 오차가 발생 할 수 있다. 따라서 본 논문에서는 이러한 오차를 줄이기 위해 각 노드마다 거리 추정 후 센싱 반경을 조절하여 2차 지역 거리 평가를 통해 센서의 위치를 측정하는 기법을 제안한다. 성능평가 결과, 제안하는 기법이 기존 기법에 비해 측위 정확도가 크게 향상되었다.

• The Journal of Engineering Research
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• v.7 no.1
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• pp.61-70
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• 2005

Conventional geological survey utilizes the manual compass for mass amount of measurements of the geologic structure. Portable multifunction digital compass system was required by more detailed geological survey, due to increasing construction for rock slopes and runnels. In this paper, the system was implemented by using Intel PXA 255 embedded board as a system controller, and was composed of tilting sensor, digital azimuth sensor, and Global Positioning System (GPS) module. After the measured location, strike, and the angle of dip with our implemented system were transmitted to Personal Digital Assistant (PDA) or notebook, these data could be used for geologic structure analysis. It is expected that the availability of cheap and improved digital compass will reduce the coast and time of geological survey extensively.

• Annual Conference of KIPS
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• 2018.10a
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• pp.430-433
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• 2018

This paper proposes the Kalman filter (KF) with optical flow method to estimate the position and the velocity of unmanned aerial vehicles (UAVs) in the absence of global positioning system (GPS). A downward-looking camera, a gyroscope and an ultrasonic sensor are fused to compensate the measurement from optical-flow method. To overcome the problem of dealing with noise in onboard sensors, the KF is incorporated to efficiently predict the velocity and estimate the position. Basic mechanisms of optical flow and the KF are introduced and experiments are conducted to show how the techniques involved improve the estimations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3889-3903
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• 2017

Fast and accurate localization of randomly deployed nodes is required by many applications in wireless sensor networks (WSNs). However, mobile nodes localization in WSNs is more difficult than static nodes localization since the nodes mobility brings more data. In this paper, we propose a Range-based Monte Carlo Box (RMCB) algorithm, which builds upon the Monte Carlo Localization Boxed (MCB) algorithm to improve the localization accuracy. This algorithm utilizes Received Signal Strength Indication (RSSI) ranging technique to build a sample box and adds a preset error coefficient in sampling and filtering phase to increase the success rate of sampling and accuracy of valid samples. Moreover, simplified Particle Swarm Optimization (sPSO) algorithm is introduced to generate new samples and avoid constantly repeated sampling and filtering process. Simulation results denote that our proposed RMCB algorithm can reduce the location error by 24%, 14% and 14% on average compared to MCB, Range-based Monte Carlo Localization (RMCL) and RSSI Motion Prediction MCB (RMMCB) algorithm respectively and are suitable for high precision required positioning scenes.