• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.2
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• pp.121-128
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• 2021

In this paper, we propose a path generation and tracking algorithm of an unmanned air vehicle in a two-dimensional plane given the initial and final points. The path generation algorithm using the Dubins curve proposed in this work has the advantage that it can be applied in real time to an unmanned air vehicle. The path tracking algorithm is an algorithm similar to the line-of-sight induction algorithm. In order to efficiently control the direction angle, a gain related to the look ahead distance concept is introduced. Most of UAVs have the limited maximum curvature due to the structural constraints. A numerical simulation is conducted to follow the path generated by the sliding mode controller considering the angular velocity limit. The path generation and tracking performance is verified by comparing the suggested controller with conventional control techniques.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2498-2501
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• 2003

In this paper, we present a wavelet neural network (WNN) approach to the solution of the path tracking problem for mobile robots that possess complexity, nonlinearity and noise. First, we discuss a WNN based control system where the control signals are directly obtained by minimizing the difference between the reference track and the pose of a mobile robot. This compact network structure is helpful to determine the number of hidden nodes and the initial value of weights. Then, the data with various noises provided by odometric and external sensors are here fused together by means of an Extended Kalman Filter (EKF) approach for the pose estimation problem of mobile robots. This control process is a dynamic on-line process that uses the wavelet neural network trained via the gradient-descent method with estimates from EKF. Finally, we verify the effectiveness and feasibility of the proposed control system through simulations.

• 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.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2000.05a
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• pp.11-15
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• 2000

This paper provides a basic study on automatic of a trailer type vehicle which consists of two parts such as a tractor and a trailer Backward moving and parking control is very important to automate this type of vehicle. However it is very difficult to control such their motion since a trailer type vehicle is a non-holonomic system. Therefore in this paper we propose the backward path tracking control algorithm for a trailer type vehicle. And also this paper presents the results of simulation to verify the effectiveness of the proposed control algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2013.05a
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• pp.335-336
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• 2013

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.483-484
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• 2008

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.1
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• pp.124-130
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• 2001

This paper presents a methodology on automation of a trailer type vehicle which consists of two parts: a tractor and a trailer. Backward moving and parking control is very important to automate this type of vehicle. It is difficult to control the motion such a trailer vehicle whose dynamics in non-holonomic. Therefore, in this paper, the modeling and parameter estimation of the system using a RCGA(real-coded genetic algorithm) is proposed and a backward path tracking control algorithm is then obtained. The simulation results verify the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.1
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• pp.1187-1195
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• 2001

This paper presents a sweeping path planning algorithm for an autonomous smearing robot. An automatic planner generates a sweeping path pattern by proposed five basic procedures. This algorithm rocog-nizes obstacle on the architectural CAD draft and generates subgoals as tracking points which executes the area filling task based on heuristic approach. A sweeping path is planned by sequentially connecting the track-ing points in such a way that(1) the connected line segments should not be crossed, (2) the total tracking points should be as short as possible, and (3) the tracking line should not pass through the obstacle, Feasibility of the developed techniques has been demonstrated on a real architectural CAD draft.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.138-142
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• 2014

This research presents an A* based algorithm which can be applied to Unmanned Ground Vehicle self-navigation in order to make the driving path smoother. Based on the grid map, A* algorithm generated the path by using straight lines. However, in this situation, the knee points, which are the connection points when vehicle changed orientation, are created. These points make Unmanned Ground Vehicle continuous navigation unsuitable. Therefore, in this paper, B-spline curve function is applied to transform the path transfer into curve type. And because the location of the control point has influenced the B-spline curve, the optimal control selection algorithm is proposed. Also, the optimal path tracking speed can be calculated through the curvature radius of the B-spline curve. Finally, based on this algorithm, a path created program is applied to the path results of the A* algorithm and this B-spline curve algorithm. After that, the final path results are compared through the simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.132-138
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• 2014

The use of AGVs(Automated Guided Vehicles) are increasing in many factories. The most widely used AGV system is that magnetic tapes are attached on the factory floor to make guided path and an AGV equipped with a magnetic sensor follows the path by sensing magnetic flux. In this AGV system, usually a magnetic sensor is attached on the front end of an AGV to detect the guided path and the sensor generates analog voltages proportional to the magnetic flux. The problem is that the AGV in use has rather big tracking errors because the accurate orientation of the AGV can not be detected by using only one magnetic sensor. In this paper, we propose a method to minimize the path tracking errors. In our method, one additional sensor is attached on the rear end of the AGV to estimate the orientation of the AGV and to control more accurately the AGV according to the estimated orientation of the AGV. We performed several experiments and the results successfully show the feasibility of the proposed method.