• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1098-1102
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• 2014

Localization of aerial vehicles and map building of flight environments are key technologies for the autonomous flight of small UAVs. In outdoor environments, an unmanned aircraft can easily use a GPS (Global Positioning System) for its localization with acceptable accuracy. However, as the GPS is not available for use in indoor environments, the development of a SLAM (Simultaneous Localization and Mapping) system that is suitable for small UAVs is therefore needed. In this paper, we suggest a vision-based SLAM system that uses vision sensors and an AHRS (Attitude Heading Reference System) sensor. Feature points in images captured from the vision sensor are obtained by using GPU (Graphics Process Unit) based SIFT (Scale-invariant Feature Transform) algorithm. Those feature points are then combined with attitude information obtained from the AHRS to estimate the position of the small UAV. Based on the location information and color distribution, a Gaussian process model is generated, which could be a map. The experimental results show that the position of a small unmanned aircraft is estimated properly and the map of the environment is constructed by using the proposed method. Finally, the reliability of the proposed method is verified by comparing the difference between the estimated values and the actual values.

• The Journal of Korea Robotics Society
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• v.10 no.4
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• pp.186-192
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• 2015

This paper proposes a robust balance and driving control for omni-directional ball robot(generally called ball-bot) with two axis mecanum wheel. Slip between ball and mecanum wheel actuator inevitably occurs along diagonal axis due to its instantaneous strong torque. In order to reduce and saturate slip, exact distance calculation scheme especially for rotational movement is essential. So this research solved Euler-Lagrange dynamics for proposed two axis ball robot based on practical mechanical modeling. Robust balance control was carried out by PID controller according to the pitch and roll angles of ball robot by using sensor fusion between AHRS and wheel encoder. Proposed PID controller enhances stability by reducing steady state error and settling time. Proposed slip control algorithm for omni-directional ball robot has been demonstrated by experiments for balance control and arbitrary driving control.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.59-64
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• 2004

In this paper, the error compensation method of the low-cost IMU is proposed. In general, the position and attitude error calculated by accelerometers and gyros grows with time. Therefore the additional information is required to compensate the drift. The attitude angles can be bound accelerometer mixing algorithm and the heading angle can be aided by single antenna GPS velocity. The Kalman filter is used for error compensation. The result is verified by comparing with the attitude calculated by Attitude Heading Reference System with Micro Electro Mechanical System for a basis

• Journal of Power System Engineering
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• v.21 no.4
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• pp.26-33
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• 2017

In this paper, we developed a control algorithm to maximize the cleaning performance and the cleaning efficiency of the underwater cleaning robot platform which has been developed for various cistern environment in the industrial field. Through these research and development, we have presented the operation and application of underwater cleaning robots that have been developed, and contributed to commercialization. Finally, this results were verified the effectiveness through actual field experiments.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.4
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• pp.359-365
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• 2011

A mobile surveillance robot is defined as a surveillance robot system that is mounted on a mobile platform and is used to protect public areas such as airports or harbors from invaders. The mobile surveillance robot that is mounted on a mobile platform consists of a gun module, a camera system module, an embedded control system, and AHRS (Attitude and Heading Reference System). It has two axis control systems for controlling its elevation and azimuth. In order to obtain stable images for targeting invaders, this system requires a stabilizer to compensate any disturbance due to vehicle motion. In this study, a virtual model of a mobile surveillance robot has been created and ADAMS/Matlab simulations have been performed to verify the suitability of the proposed stabilization algorithm. Further, the suitability of the stabilization algorithm has also been verified using a mock-up of the mobile surveillance robot and a 6-DOF (Degree Of Freedom) motion simulator.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1429-1432
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• 2005

This work is towards the development of a low-cost, small-sized inertial navigation system(INS) which consists of 3 accelerometers, 3 semiconductor gyros and a magnetic compass sensor. This paper explains in detail the structure of the developed system and proposes a 3 dimensional attitude estimation algorithm with Indirect Kalman Filter. The experiments are performed with the developed system attached to a 6 DOF robot for showing the effectiveness of the algorithm.

• International Journal of Ocean System Engineering
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• v.1 no.2
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• pp.102-109
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• 2011

This paper describes the implementation of a precise underwater navigation solution using a multiple sensor fusion technique based on USBL, GPS, DVL and AHRS measurements for the operation of a remotely operated mine disposal vehicle (MDV). The estimation of accurate 6DOF positions and attitudes is the key factor in executing dangerous and complicated missions. To implement the precise underwater navigation, two strategies are chosen in this paper. Firstly, the sensor frame alignment to the body frame is conducted to enhance the performance of a standalone dead-reckoning algorithm. Secondly, absolute position data measured by USBL is fused to prevent cumulative integration error. The heading alignment error is identified by comparing the measured absolute positions with the DR algorithm results. The performance of the developed approach is evaluated with the experimental data acquired by MDV in the South-sea trial.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.427-434
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• 2016

This paper focuses on a real-time hardware processing by implementing the ARM Cortex-M4 based embedded system, using a conversion algorithm from a muscular sense to both visual and auditory elements, which recognizes rotations of a human body, directional changes and motion amounts out of human senses. As an input method of muscular sense, AHRS(Attitude Heading Reference System) was used to acquire roll, pitch and yaw values in real time. These three input values were converted into three elements of HSI color model such as intensity, hue and saturation, respectively. Final color signals were acquired by converting HSI into RGB color model. In addition, Three input values of muscular sense were converted into three elements of sound such as octave, scale and velocity, which were synthesized to give an output sound using MIDI(Musical Instrument Digital Interface). The analysis results of both output color and sound signals revealed that input signals of muscular sense were correctly converted into both color and sound in real time by the proposed conversion method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.4
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• pp.342-351
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• 2010

UAV (Unmanned Aerial Vehicle) have an INS(Inertial Navigation System) equipment and also have an electro-optical Equipment for mission. This paper proposes the vision based attitude estimation algorithm using Kalman Filter and Optical flow for UAV. Optical flow is acquired from the movie of camera which is equipped on UAV and UAV's attitude is measured from optical flow. In this paper, Kalman Filter has been used for the settlement of the low reliability and estimation of UAV's attitude. Algorithm verification was performed through experiments. The experiment has been used rate table and real flight video. Then, this paper shows the verification result of UAV's attitude estimation algorithm. When the rate table was tested, the error was in 2 degree and the tendency was similar with AHRS measurement states. However, on the experiment of real flight movie, maximum yaw error was 21 degree and Maximum pitch error was 7.8 degree.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.33-42
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• 2010

This research propose a practical guidance system considering ocean currents in real sea operation. Optimality of generated path is not an issue in this paper. Way-points from start point to possible goal positions are selected by experienced human supervisors considering major ocean current axis. This paper also describes the implementation of a precise underwater navigation solution using multi-sensor fusion technique based on USBL, GPS, DVL and AHRS measurements in detail. To implement the precise, accurate and frequent underwater navigation solution, three strategies are chosen. The first one is the heading alignment angle identification to enhance the performance of standalone dead-reckoning algorithm. The second one is that absolute position is fused timely to prevent accumulation of integration error, where the absolute position can be selected between USBL and GPS considering sensor status. The third one is introduction of effective outlier rejection algorithm. The performance of the developed algorithm is verified with experimental data of mine disposal vehicle and deep-sea ROV.