• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1216-1218
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• 1996

Genetic algorithm(GA) is useful to find optimal solution without any special mathematical modeling. This study presents to search optimal path of Autonomous Mobile Robot(AMR) by using GA without encoding and decoding procedure. Therefore, this paper shows that the proposed algorithm using GA can reduce the computation time to search the optimal path.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.1
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• pp.33-39
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• 2007

One of the most important processes is the face milling in processing task. It makes the smooth surface of processed goods. In processing stage, the formation of burr is inevitable. The formed burr decreases a detailed drawing and effects the safety of workers. So, it causes a deburring process for removing and a bottle-neck condition. Therefore, the study which can minimize the generation of burr is needed. In this paper, complex feature, such as line, arc, circle, spline is studied more reality than any other papers. And also, the algorithm which can predict the path of generated burr is established. Moreover, the finality goal is that the system which can produce tool-path minimized has to be developed.

• Journal of Aerospace System Engineering
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• v.14 no.6
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• pp.1-9
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• 2020

Global e-commerce and delivery companies are actively pursuing last-mile delivery service using drones, and various delivery schedule planning studies have been conducted. In this study, separate individual route networks were constructed to reflect drone route constraints such as prohibited airspace and truck route constraints such as rivers, which previous studies did not incorporate. The A* algorithm was used to calculate the shortest path distance matrix between the starting point and destinations. In addition, we proposed an optimal delivery schedule plan using genetic algorithms and applied it to compare the efficiency with that of vehicle-only delivery.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.48-52
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• 2010

In this paper, we introduce a new path planning algorithm which combines the merits of a visibility graph algorithm and an adaptive cell decomposition. We quantize a given map with empty cells, blocked cells, and mixed cells, then find the optimal path on the quantized map using a visibility graph algorithm. For reducing the number of the quantized cells we use the quad-tree technique which is used in an adaptive cell decomposition, and for improving the performance of the visibility checking in making a visibility graph we propose a new visibility checking method which uses the property of the quad-tree instead of the well-known rotational sweep-line algorithm. For the more efficient visibility checking, we propose two additional improvements for our suggested method. Both of them are used for reducing the visited cells in the quad-tree. The experiments for a performance comparison of our algorithm with other well-known algorithms show that our proposed method is superior to others.

• Journal of Korean Society of Transportation
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• v.33 no.2
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• pp.192-203
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• 2015

Pedestrians not only walk along pedestrian pathways, but also choose unusual routes such as passing through buildings or crossing large scale open spaces. This study defines these unusual paths as social path, and includes them into one of the pedestrian road categories. Previous pedestrian accessibility and route choice studies could not evaluate correctly the space connectivity or optimal route because the social path was not considered properly. Therefore, this study analyzes the effectiveness of the social path in view of space connectivity focused on Coex and Seoul stations in Seoul, which are representative transit oriented development(TOD) areas. Global integration, which is widely used in network analysis, is selected (as performance index) to identify the space hierarchy and define new pedestrian links. The study results show that the network connectivity is improved especially in the main streets and social paths. This study demonstrated that the social path should be considered in finding the pedestrian optimal route from the practical perspective.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.7
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• pp.599-604
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• 2013

Path planning of mobile robots has a purpose to design an optimal path from an initial position to a target point. Minimum driving time, minimum driving distance and minimum driving error might be considered in choosing the optimal path and are correlated to each other. In this paper, an efficient driving trajectory is planned in a real situation where a mobile robot follows a moving object. Position and distance of the moving object are obtained using a web camera, and the rotation angular and linear velocities are estimated using Kalman filters to predict the trajectory of the moving object. Finally, the mobile robot follows the moving object using a single curvature trajectory by estimating the trajectory of the moving object. Using the estimation by Kalman filters and the single curvature in the trajectory planning, the total tracking distance and time saved amounts to about 7%. The effectiveness of the proposed algorithm has been verified through real tracking experiments.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.4
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• pp.89-95
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• 2012

Recent planning for bicycle use is relatively low compared to other studies. Although studies for the bicycle roads accessibility are actively underway, those considering topographical elements and characteristics of the user behaviors are very limited. Choosing paths of cyclists is typically influenced by slopes and intersections as well as optimal distance. This study presents a method to find optimal paths considering topographical elements in case of choosing paths for school commuting using bicycles. Conversion formulae suggested here are tested on a Songpa area using round-trip directions and compared with traditional optimal path computation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.406-412
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• 1996

Optimal trajectory for a robot manipulator minimizing actuator torques or energy consumption in a fixed traveling time is obtained in the presence of obstacles. All joint displacements are represented in finite terms of Fourier cosine series and the coefficients of the series are obtained optimally by nonlinear programming. Thus, the geometric path need not be prespecified and the full dynamic model is employed. To avoid the obstacles, the concept of penalty area is newly introduced and this penalty area is included in the performance index with an appropriate weighting coefficient. This optimal trajectory will be useful as a geometric path in the minimum-time trajectory planning problem.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.3
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• pp.147-155
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• 1997

Optimal trajectory for a robot manipulator minimizing actuator torques or energy consumptions ina fixed traveling time is obtained in the presence of obstacles. All joint displacements are represented in finite terms of Fourier cosine series and the coefficients of the series are obtained optimally by nonlinear programming. Thus, the geometric path need not be prespecified and the full dynamic model is employed. To avoid the obstacles, the concept of the penalty area is newly introduced and this penalty area is includ- ed in the performance index with an appropriate weighting coefficient. This optimal trajectory will be useful as a geometric path in the minimum-time trajectory planning problem.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.471-476
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• 2015

This paper presents a maximum velocity trajectory planning algorithm for differential mobile robots with wheel velocity constraint to cope with physical limits in the joint space for two-wheeled mobile robots (TMR). In previous research, the convolution operator was able to generate a central velocity that deals with the physical constraints of a mobile robot while considering the heading angles along a smooth curve in terms of time-dependent parameter. However, the velocity could not track the predefined path. An algorithm is proposed to compensate an error that occurs between the actual and driven distance by the velocity of the center of a TMR within a sampling time. The velocity commands in Cartesian space are also converted to actuator commands to drive two wheels. In the case that the actuator commands exceed the maximum velocity the trajectory is redeveloped with the compensated center velocity. The new center velocity is obtained according to the curvature of the path to provide a maximum allowable velocity meaning a time-optimal trajectory. The effectiveness of the algorithm is shown through numerical examples.