• Journal of Drive and Control
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• v.18 no.2
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• pp.20-31
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• 2021

An excavator is a construction machine that can perform various tasks such as trenching, piping, excavating, slope cutting, grading, and rock demolishing. In the 2010s, unmanned construction equipment using ICT technology was continuously developed. In this paper, the path design process was studied to implement the output data of the decision stage, and the path design algorithm was developed. For example, the output data of the decision stage were terrain data around the excavator, excavator mechanism information, excavator hydraulic information, the position and posture of the bucket at key points, the speed of the desired bucket path, and the required excavation volume. The result of the path design was the movement of the hydraulic cylinder, boom arm, bucket, and bucket edge. The core functions of the path design algorithm are the function of avoiding impact during the excavation process, the function to calculate the excavation depth that satisfies the required excavation volume, and the function that allows the bucket to pass through the main points of the excavation process while maintaining the speed of the desired path. In particular, in the process of developing the last function, the node tracking method expressed in the path design table was newly developed. The path design algorithm was verified as this path design satisfied the JCMAS H02 requirement.

• Journal of KSNVE
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• v.8 no.6
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• pp.1037-1042
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• 1998

This paper discusses the dependence of the convergence rate on the acoustic error path in these popular algorithms and introduces new algorithms which increase the convergence region regardless of the time-delay in the acoustic error path. We also Propose a novel control algorithm (AFC/CAFC) for tonal noise cancellation. The proposed algorithm estimates the magnitude and phase of the tonal noise. The algorithm uses the steepest descent method for the phase/magnitude estimation. Performances of tile CAFC algorithm are presented in comparison with those by the AFC algorithm based on computer simulations and experiments.

• Journal of Forest and Environmental Science
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• v.38 no.4
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• pp.239-248
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• 2022

Forestry crane work in a forest harvester or forwarder is regarded as one of most hard work requiring a very high level of operation skill. The operator must handle two or more multi-axes joysticks simultaneously to control the multiple manipulators for maneuvering the crane-tip to its intended location. This study has been carried out to develop a crane-tip controller which can intuitively maneuver the crane-tip, resulting in improving the productivity by decreasing the technical difficulty of control as well as reducing the workload. The crane-tip controller consists of a single 2-axis joystick and a control algorithm run on microcontroller. Lab-scale forestry crane was constructed using electric cylinders. The crane-tip control algorithm has the crane-tip follow the waypoints generated on the given path considering the dead band region using LBO (Lateral Boundary Offset). A speed control gain to change the speed of relevant cylinders relatively is applied as well. By the P (Proportional) control within the control interval of 20 msec, the average error of crane-tip control on the predefined straight path turned out to be 14.5 mm in all directions. When the joystick is used the waypoints are generated in real time by the direction signal from the joystick. In this case, the average error of path control was 12.4 mm for straight up, straight forward and straight down movements successively at a certain constant speed setting. In the slant movement of crane-tip by controlling two axes of joystick simultaneously, the movement of crane-tip was controlled in the average error of 15.9 mm when the crane-tip is moved up and down while moving toward forward direction. It concluded that the crane-tip control was possible using the control algorithm developed in this study.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.156-161
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• 1997

In this thesis, based on Genetic Algorithm, a new route search algorithm is presented to search an optimal route between the origin and the destination in intelligent route guidance systems in order to minimize the route traveling time. The proposed algorithm is effectively employed to complex road networks which have diverse turn constrains, time-delay constraints due to cross signals, and stochastic traffic volume. The algorithm is also shown to significantly promote search efficiency by changing the population size of path individuals that exist in each generation through the concept of age and lifetime to each path individual. A virtual road-traffic network with various turn constraints and traffic volume is simulated, where the suggested algorithm promptly produces not only an optimal route to minimize the route cost but also the estimated travel time for any pair of the origin and the destination, while effectively avoiding turn constraints and traffic jam.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.119.1-119
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• 2002

$\textbullet$ Introduction: Service robot $\textbullet$ Design of the Guide Service Mobile Robot $\textbullet$ Path tracking algorithm $\textbullet$ Path recognition algorithm $\textbullet$ Localization $\textbullet$ Guide lever $\textbullet$ Conclusions: A mobile robot was developed as a service robot

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.799-808
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• 2004

In this paper, a new collision avoidance algorithm based on the dynamic model of a mobile robot is proposed. In order to avoid obstacles on the path of a mobile robot, intelligent force control is used to regulate accurate distance between a robot and an obstacle. Since uncertainties from robot and environment dynamics degrade the performance of a collision avoidance task, neural network is used to compensate for uncertainties so that the collision avoidance can be performed intelligently. Simulation studies are conducted to confirm the proposed collision avoidance tracking control algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.79-84
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• 1992

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the optimal collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy and a traveling salesman problem strategy (TSP). The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Hopfield Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is used to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm.

• Journal of Drive and Control
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• v.16 no.2
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• pp.22-29
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• 2019

This study presented a model predictive tracking control algorithm of autonomous truck based on object state estimation using extended Kalman filter. To design the model, the 1-layer laser scanner was used to estimate position and velocity of the object using extended Kalman filter. Based on these estimations, the desired linear path for object tracking was computed. The lateral and yaw angle errors were computed using the computed linear path and relative positions of the truck. The computed errors were used in the model predictive control algorithm to compute the optimal steering angle for object tracking. The performance evaluation was conducted on Matlab/Simulink environments using planar truck model and actual point data obtained from laser scanner. The evaluation results showed that the tracking control algorithm developed in this study can track the object reasonably based on the model predictive control algorithm based on the estimated states.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.51-66
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• 2023

In this paper, we propose a new type of process discovery framework, which is named as control-path-driven process group discovery framework, to be used for process mining and process reengineering in supporting life-cycle management of business process models. In addition, we develop a process mining system based on the proposed framework and perform experimental verification through it. The process execution event logs applied to the experimental effectiveness and verification are specially defined as Process BIG-Logs, and we use it as the input datasets for the proposed discovery framework. As an eventual goal of this paper, we design and implement a control path-driven process group discovery algorithm and framework that is improved from the ρ-algorithm, and we try to verify the functional correctness of the proposed algorithm and framework by using the implemented system with a BIG-Log dataset. Note that all the process mining algorithm, framework, and system developed in this paper are based on the structural information control net process modeling methodology.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.716-721
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• 2004

Several Solid Freeform Fabrication Systems(SFFS) are commercialized in a few companies for rapid prototyping. However, they have many technical problems including the limitation of applicable materials. A new method of speedy prototyping is required for the recent manufacturing environments of multi-item and small quantity production. The objectives of this paper include the development of a novel method of SFFS, the ${CAFL}^{VM}$(Computer Aided Fabrication of Lamination for Various Material), and the manufacture of the various material samples for the certification of the proposed system and the creation of new application areas. For these objectives, the technologies for a highly accurate robot path control, the optimization of support structure, CAD modeling, adaptive slicing was implemented. In this paper, we design an algorithm that the cutting path of a laser beam which is controlled with constant speed. The laser beam is tangentially controlled in order to solve the inaccuracy of a 3D model surface. The designed algorithm for constant-speed path control and tangent-cutting control is implemented and experimented in the ${CAFL}^{VM}$ system.