• Journal of the Korean Society for Precision Engineering
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• v.29 no.12
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• pp.1321-1330
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• 2012

This paper describes an advanced formation algorithm of clustered multiple robots for their navigation using flexible formation method for collision avoidance under static environment like narrow corridors. A group of clustered multiple robots finds the lowest path cost for navigation by changing its formation. The suggested flexible method of formation transforms the basic group of mobile robots into specific form when it is confronted by particular geographic feature. In addition, the proposed method suggests to choose a leader robot of the group for the obstacle avoidance and path planning. Firstly, the group of robots forms basic shapes such as triangle, square, pentagon and etc. depending on number of robots. Secondly, the closest to the target location robot is chosen as a leader robot. The chosen leader robot uses $A^*$ for reaching the goal location. The proposed approach improves autonomous formation characteristics and performance of all system.

• Journal of the Korea Institute of Military Science and Technology
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• v.18 no.3
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• pp.226-233
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• 2015

Pose estimation is an important operation for many vision tasks. This paper presents a method of estimating the camera pose, using a known landmark for the purpose of autonomous vertical takeoff and landing(VTOL) unmanned aerial vehicle(UAV) landing. The proposed method uses a distinctive methodology to solve the pose estimation problem. We propose to combine extrinsic parameters from known and unknown 3-D(three-dimensional) feature points, and inertial estimation of camera 6-DOF(Degree Of Freedom) into one linear inhomogeneous equation. This allows us to use singular value decomposition(SVD) to neatly solve the given optimization problem. We present experimental results that demonstrate the ability of the proposed method to estimate camera 6DOF with the ease of implementation.

• Journal of the Korean Society of Industry Convergence
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• v.17 no.2
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• pp.42-53
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• 2014

Robust voice recognition (RVR) is essential for a robot to communicate with people. One of the main problems with RVR for robots is that robots inevitably real environment noises. The noise is captured with strong power by the microphones, because the noise sources are closed to the microphones. The signal-to-noise ratio of input voice becomes quite low. However, it is possible to estimate the noise by using information on the robot's own motions and postures, because a type of motion/gesture produces almost the same pattern of noise every time it is performed. In this paper, we propose an RVR system which can robustly recognize voice by adults and children in noisy environments. We evaluate the RVR system in a communication robot placed in a real noisy environment. Voice is captured using a wireless microphone. Navigation Strategy is shown Obstacle detection and local map, Design of Goal-seeking Behavior and Avoidance Behavior, Fuzzy Decision Maker and Lower level controller. The final hypothesis is selected based on posterior probability. We then select the task in the motion task library. In the motion control, we also integrate the obstacle avoidance control using ultrasonic sensors. Those are powerful for detecting obstacle with simple algorithm.

• Journal of Advanced Navigation Technology
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• v.6 no.1
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• pp.27-36
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• 2002

As the number of autonomous vehicles is increased, drivers are trending toward constant interests in detecting distance between vehicles in close-range and maintaining the distance between forward and backward vehicles for drivers' safety. In this paper, we propose a method of detecting the distance between two vehicles by computing the disparity of the close-rang vehicle using stereo vision. The boundary of the vehicle is obtained by using the modified wavelet transform which has multi-resolution characteristics. Then the disparity between left and right images is computed using coarse-to-fine method and histogram matching. Here we transform the left-right stereo images through 3-steps using the modified wavelet for maintaining the original resolution. An experimental result showed that the proposed method had 4.65% in total error rate.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.599-602
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• 2007

Generally, the mobile robot navigation with obstacle avoidance is one of the key issues to be looked into for successful applications of autonomous mobile robots. In this paper, the Univector field based method is proposed for mobile robot to accomplish the obstacle avoidance and the robot orientation at the target position. Univector field method guarantees the desired posture of the robot at the target position. But it is not effective Univector to avoid obstacles. To solve this problem, modified univector field is used. With this proposed method, robot navigation task becomes easier and effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.833-842
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• 2011

The objectives of this research are development of guidance, navigation and control system for RUAV on virtual instrumentation and real flight test. For this research, the system is divided to DAQ (data acquisition) section, actuator section and controller section. And the hardware and software on each sections are realized on LabVIEW base. Waypoint guidance and control of auto flight are realized using PID gain tuning and waypoint vector tracking guidance algorism. For safe flight test, auto/manual switching module isolated from FCS (Flight Control System) is developed. By using the switch module, swift mode change was achieved during emergency flight case. Consequently, a meter level error of flight performance is achieved.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.180-185
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• 2003

This paper proposes an intelligent navigation algorithm for multiple mobile robots under unknown dynamic environment. The proposed algorithm consists of three basic parts as follows. The first part based on the fuzzy rule generates the turning angle and moving distance of the robot for goal approach without obstacles. In the second part, using both fuzzy and neural network, the angle and distance of the robot to avoid collision with dynamic and static obstacles are obtained. The final adjustment of the weighting factor based on fuzzy rule for moving and avoiding distance of the robots is provided in the third stage. The experiments which demonstrate the performance of the proposed intelligent controller is described.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.372-374
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• 2009

In this research, an obstacle avoidance method is proposed. The common usage of a robot is indoor and the obstacles to the indoor robot is studied. The accurate detection of direction after overcoming the obstacles is necessary for performance of autonomous navigation and mission project. The sensors such as Laser, Ultrasound, PSD can be used to measure the obstacles. In this research, a PSD sensor is used to detect obstacles. It detects the height and width of obstacles located on the floor. Before measuring the obstacles, a calibration of the sensor was done and it produced a better accuracy. We have plotted an error graph using data obtained from the repeated experiments. The graph is fitted to a polynomial curve. The polynomial equation is used for the robot navigation. And in this research, a model of the error of the direction of the robot after overcoming obstacles was obtained also. The prototype of the obstacle and the error of the direction after overcoming the obstacles are modelled using a neural networks. The input of the neural network composed with the height of the obstacles, the speed of robot, the direction of wheels and the error of the direction. To implement the suggested algorithm, we set up a robot which is operated by a notebook computer. Experiment showed the suggested algorithm performed well.

• Journal of Advanced Navigation Technology
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• v.16 no.2
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• pp.197-203
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• 2012

In this paper, study the substantial issues which occurs upon free flight environment by performing separation assurance under multiple conflict(over 3 Aircraft), recovery en route under the terms of time constrains and fixed way point after the conflict avoidance, correlations between conflict detection distance and separation assurance by utilizing Autonomous flight algorithm. Result of this experiment demonstrates that the extension of detection distance is advantageous to solution of separation assurance and enhancing of flight efficiency, choose to maneuver by applying time constrain terms and fixed way point according to the situation of conflict prediction in case of recovery maneuver after the conflict avoidance. And separation assurance can be solved by applying 2 degrees or more of bank angle. When choosing the optimal bank angle could be drastically improved flight efficiency.

• Journal of Advanced Navigation Technology
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• v.9 no.2
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• pp.87-92
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• 2005

An altitude control using a fuzzy controller was performed for a series of research for autonomous flight control of industrial unmanned helicopters. The 3m class gasoline engined unmanned helicopter was designed, and using the designed specifications, Takagi-Sugeno-Kang type fuzzy controller was designed. The input membership functions were generated using target altitude, altitude error and velocity of unmanned helicopter. With these membership functions, the control inputs for altitude control were calculated. These control input signal can control the main rotor's pitch and determine the velocity and altitude of the unmanned helicopter. Also, the altitude control performance of the designed fuzzy controller was evaluated by computer simulations