• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.72-75
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• 1988

Due to the fact that the set point regulation scheme by the variable structure control method concerns only the initial and final locations of a manipulator, many constraints may exist in the application of path tracking with obstracle avoidance. The variable structure parameter should be selected in the trajectory planning step by satisfying the constraints of the travel time and the path deviations This paper presents the selection algorithm of the variable structure parameters with the constraints of the system dynamics and the travel time and the path deviation. This study makes unify the trajectory planning and tracking control using the variable structure control method.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.250-259
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• 2021

Path planning is one of the important technologies for automated parking. It requires to plan a collision-free path considering the vehicle's kinematic constraints such as minimum turning radius or steering velocity. In a complex parking lot, Rapidly-exploring Random Tree^* (RRT^*) can be used for planning a parking path, and Reeds-Shepp or Hybrid Curvature can be applied as a tree-extension method to consider the vehicle's constraints. In this case, each of these methods may affect the computation time of planning the parking path, path-tracking error, and parking success rate. Therefore, in this study, we conduct comparative analysis of two tree-extension functions: Reeds-Shepp (RS) and Hybrid Curvature (HC), and show that HC is a more appropriate tree-extension function for parking path planning. The differences between the two functions are introduced, and their performances are compared by applying them with RRT^*. They are tested at various parking scenarios in simulation, and their advantages and disadvantages are discussed by computation time, cross-track error while tracking the path, parking success rate, and alignment error at the target parking spot. These results show that HC generates the parking path that an autonomous vehicle can track without collisions and HC allows the vehicle to park with lower alignment error than those of RS.

• Journal of the Korea Institute of Building Construction
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• v.10 no.3
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• pp.65-70
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• 2010

Steel frame construction in high places entails many risk factors. In order to improve the safety and productivity of steel frame construction, a project to develop a robotic tower-crane has been undertaken. As the first step, a real-time lifting-path tracking system is being developed. In a previous study, a laser-based tracking system was proposed. While a laser-based tracking system requires at least three laser sensors to detect the x, y, z coordinates of a lifted steel member, a GPS-based system has an advantage over the laser-based system, in that the x, y, z coordinates of a lifted steel member can be detected by a single GPS sensor. To improve the accuracy, arelative positioning method using two GPS sensors was proposed in a previous study. This paper reports an improved GPS-based lifting-path tracking system of a tower crane based on an integrated RF modem and GPS system. The results showedthat the RF modem could successfully send the identifier information to a server a maximum distance of 1 km away from the lifted steel beam, and the lifting path information of each beam captured by the GPS-based tracking system was successfully saved together. Also, byusing an improved algorithm for the GPS relative positioning method, the deviation was reduced to 0.61 m on average.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.281-291
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• 2008

In this paper, we propose a new double talk detection algorithm which detects near end signals with less degradation, tracking echo path variation of echo canceler simultaneously. Our method makes use of a cross-correlation between channel input signals and estimated error signals and a normalized cross-correlation between microphone input signals and estimated error signals. By combing thresholds for these cross-correlations pertinently, this algorithm discriminates between variation of echo path and occurrence of double talk. These two cross-correlation are used to detect double talk periods, tracking echo path variation. During the detection period, adjustive adaptive filter is ceased to prevent the echo canceler from being disturbed by near end signals. Also, the echo canceler will still be kept on for tracking any variation in echo path. Through computer simulation results, it was confirmed that the proposed algorithm shows better performance, tracking echo path variation and detecting the double talk periods, than the Ye et. al's and the NLMS algorithms from ERLE viewpoint.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.26 no.6
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• pp.55-61
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• 2021

As the demand for distance education increases, it is necessary to present a problem solving path through a learning tracking algorithm in order to support the efficient learning of learners. In this paper, we proposed a problem solving path of various difficulty levels in various subjects by supplementing the existing learning tracking algorithm. Through the data set obtained through the path for solving the learner's problem, the path through the prim's minimum Spanning tree was secured, and the optimal problem solving path through the recursive neural network was suggested through the path data set. As a result of the performance evaluation of the contents proposed in this paper, it was confirmed that more than 52% of the test subjects included the problem solving path suggested in the problem solving process, and the problem solving time was also improved by more than 45%.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.191-196
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• 2003

This paper presents a method to design an adaptive controller for the kinematic model of a two-wheeled welding mobile robot (WMR) with unknown parameters. We propose a nonlinear controller based on the Lyapunov function to enhance the tracking properties of the WMR. The WMR can track any smooth curved welding path at a constant velocity of the welding point. The system has three degrees of freedom including two wheels and one torch slider. Torch slider motion is used for fast tracking. To design the tracking performance, the errors from WMR to steel wall is defined, and the controller is designed to drive the errors to zero as fast as possible. The effectiveness of the proposed controller is shown through simulation results.

• 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 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 Mechanical Science and Technology
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• v.17 no.11
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• pp.1682-1692
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• 2003

This paper proposes an adaptive controller for partially known system and applies to a two-wheeled Welding Mobile Robot (WMR) to track a reference welding path at a constant velocity of the welding point. To design the tracking controller, the errors from WMR to steel wall is defined, and the controller is designed to drive the errors to zero as fast as desired. Additionally, a scheme of error measurement is implemented on the WMR to meet the need of the controller. In this paper, the system moments of inertia are considered to be partially unknown parameters which are estimated using update laws in adaptive control scheme. The simulations and experiments on a welding mobile robot show the effectiveness of the proposed controller.