• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1052-1056
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• 1991

페인팅작업에의 로보트응용은 열악환경의 극복, 자동화, 품질의 향상수단으로서 강력한 대안책이며 이에 관한 관심이 국내외에 고조되고 있다. 본 논문에서는 이전에 제시한 바있는 자동동작계획의 개념을 확장하여 통합페인팅시스템을 위한 Extended ATPS(Automatic Trajectory Planning System)를 개발하고, 이의 구현 및 검증을 위한 하드웨어 시스템의 개발현황을 소개한다. 개발될 시스템은 하드웨어 및 소프트웨어가 일식화된 로보틱페인팅 시스템으로서 동작계획의 자동화 뿐만아니라 측정 및 제어기능을 소프트웨어에서 일관처리하는 새로운 방식이다.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2427-2429
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• 2002

본 논문에서는, 지붕위로 뛰어오르기 위하여 벽의 반동을 이용하는 고양이의 운동상태를 흉내내어 수직의 방향으로 운동하는 고양이 로봇 시스템을 연구한다. 또한 이러한 로봇 시스템의 3-link 부분시스템의 운동은 slider-link에서 구속되어지고, 또한 singular자세를 쉽게 피할 수 있는 운동계획방법(motion planning method)을 제안한다. 제안되어진 연구결과는 수직동작에 대한 메카니즘에 유용한 방법이고 이론적 개념, 모델링, 그리고 제어를 논의한다. 마지막으로, 모의실험을 통한 결과로서 제안되어진 방법의 유용성을 설명한다.

• International Journal of Control, Automation, and Systems
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• v.4 no.4
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• pp.405-413
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• 2006

A novel approach based on genetic algorithms (GA) is developed to find a global minimum-jerk trajectory of a space robotic manipulator in joint space. The jerk, the third derivative of position of desired joint trajectory, adversely affects the efficiency of the control algorithms and stabilization of whole space robot system and therefore should be minimized. On the other hand, the importance of minimizing the jerk is to reduce the vibrations of manipulator. In this formulation, a global genetic-approach determines the trajectory by minimizing the maximum jerk in joint space. The planning procedure is performed with respect to all constraints, such as joint angle constraints, joint velocity constraints, joint angular acceleration and torque constraints, and so on. We use an genetic algorithm to search the optimal joint inter-knot parameters in order to realize the minimum jerk. These joint inter-knot parameters mainly include joint angle and joint angular velocities. The simulation result shows that GA-based minimum-jerk trajectory planning method has satisfactory performance and real significance in engineering.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.656-662
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• 2008

A cost-function based on manipulability and compatibility is designed to determine assembly motions of two cooperating manipulators. Assembly motions are planned along the direction maximizing performance indices to improve control performance of the two manipulators. This paper proposes bimanual task compatibility by defining cost functions. The proposed cost functions are applied and compared to the bimanual assembly task. The problem is formulated as a constrained optimization considering assembly constraints, position of the workpieces, and kinematics and redundancy of the bimanual robot. The proposed approach is evaluated with simulation of a peg-in-hole assembly with an L-shaped peg and two 3-dof manipulators.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.144-145
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• 2022

Since the marking robot draws lines by point-to-point operation, the robot's shifting path greatly affects the working time and productivity. Therefore, it is required to analyze the movement method based on the robot's motion and plan to minimize the movement time. Therefore, this study proposes a method that can optimize the robot's shifting path to minimize the working time of the marking robot. Through the results of this study, it is expected that the non-working time of the marking robot will be reduced and the efficient operation will be possible.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.30-41
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• 2006

The goal of this work is to develop and test a robot-assisted surgery system for spinal fusion. The system is composed of a robot, a surgical planning system, and a navigation system. It plays the role of assisting surgeons for inserting a pedicle screw in the spinal fusion procedure. Compared to conventional methods for spinal fusion, the proposed surgical procedure ensures minimum invasion and better accuracy by using robot and image information. The robot plays the role of positioning and guiding needles, drills, and other surgical instruments or conducts automatic boring and screwing. Pre-operative CT images intra-operative fluoroscopic images are integrated to provide the surgeon with information for surgical planning. Some experiments employing the developed robotic surgery system are conducted. The experimental results confirm that the system is not only able to guide the surgical tools by accurately pointing and orienting the specified location, but also successfully compensate the movement of the patient due to respiration.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.144-148
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• 2005

The goal of this work is to develop and test a robot-assisted surgery system for spinal fusion. The system is composed of a robot, a surgical planning system, and a navigation system. It plays the role of assisting surgeons for inserting a pedicle screw in the spinal fusion procedure. Compared to conventional methods fer spinal fusion, the proposed surgical procedure ensures minimum invasion and better accuracy by using robot and image information. The robot plays the role of positioning and guiding needles, drills, and other surgical instruments or conducts automatic boring and screwing. Pre-operative CT images and intra-operative fluoroscopic images are integrated to provide the surgeon with information for surgical planning. Several experiments employing the developed robotic surgery system are conducted. The experimental results confirmed that the system is not only able to guide the surgical tools by accurately pointing and orienting the specified location, but also successfully compensate the movement of the patient due to his/her respiration.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.192-198
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• 2016

Motion planning problem is still one of the important issues in robotic applications. In many real-time motion planning problems, it is advisable to find a feasible solution quickly and improve the found solution toward the optimal one before the previously-arranged motion plan ends. For such reasons, sampling-based approaches are becoming popular for real-time application. Especially the use of a rapidly exploring random $tree^*$ ($RRT^*$) algorithm is attractive in real-time application, because it is possible to approach an optimal solution by iterating itself. This paper presents a modified version of informed $RRT^*$ which is an extended version of $RRT^*$ to increase the rate of convergence to optimal solution by improving the sampling method of $RRT^*$. In online motion planning, the robot plans a path while simultaneously moving along the planned path. Therefore, the part of the path near the robot is less likely to be sampled extensively. For a better solution in online motion planning, we modified the sampling method of informed $RRT^*$ by combining with the sampling method to improve the path nearby robot. With comparison among basic $RRT^*$, informed $RRT^*$ and the proposed $RRT^*$ in online motion planning, the proposed $RRT^*$ showed the best result by representing the closest solution to optimum.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.417-424
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• 2022

In this paper, the developed trunk cargo unloading automation system is introduced, and the RGB-D sensor-based box loading situation recognition method and unloading plan applied to this system are suggested. First of all, it is necessary to recognize the position of the box in a truck. To do this, we first apply CNN-based YOLO, which can recognize objects in RGB images in real-time. Then, the normal vector of the center of the box is obtained using the depth image to reduce misrecognition in parts other than the box, and the inner wall of the truck in an image is removed. And a method of classifying the layers of the boxes according to the distance using the recognized depth information of the boxes is suggested. Given the coordinates of the boxes on the nearest layer, a method of generating the optimal path to take out the boxes the fastest using this information is introduced. In addition, kinematic analysis is performed to move the conveyor to the position of the box to be taken out of the truck, and kinematic analysis is also performed to control the robot arm that takes out the boxes. Finally, the effectiveness of the developed system and algorithm through a test bed is proved.

• Radiation Oncology Journal
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• v.28 no.4
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• pp.238-248
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• 2010

Purpose: To compare the dose distributions between three-dimensional (3D) and four-dimensional (4D) radiation treatment plans calculated by Ray-tracing or the Monte Carlo algorithm, and to highlight the difference of dose calculation between two algorithms for lung heterogeneity correction in lung cancers. Materials and Methods: Prospectively gated 4D CTs in seven patients were obtained with a Brilliance CT64-Channel scanner along with a respiratory bellows gating device. After 4D treatment planning with the Ray Tracing algorithm in Multiplan 3.5.1, a CyberKnife stereotactic radiotherapy planning system, 3D Ray Tracing, 3D and 4D Monte Carlo dose calculations were performed under the same beam conditions (same number, directions, monitor units of beams). The 3D plan was performed in a primary CT image setting corresponding to middle phase expiration (50%). Relative dose coverage, D95 of gross tumor volume and planning target volume, maximum doses of tumor, and the spinal cord were compared for each plan, taking into consideration the tumor location. Results: According to the Monte Carlo calculations, mean tumor volume coverage of the 4D plans was 4.4% higher than the 3D plans when tumors were located in the lower lobes of the lung, but were 4.6% lower when tumors were located in the upper lobes of the lung. Similarly, the D95 of 4D plans was 4.8% higher than 3D plans when tumors were located in the lower lobes of lung, but was 1.7% lower when tumors were located in the upper lobes of lung. This tendency was also observed at the maximum dose of the spinal cord. Lastly, a 30% reduction in the PTV volume coverage was observed for the Monte Carlo calculation compared with the Ray-tracing calculation. Conclusion: 3D and 4D robotic radiotherapy treatment plans for lung cancers were compared according to a dosimetric viewpoint for a tumor and the spinal cord. The difference of tumor dose distributions between 3D and 4D treatment plans was only significant when large tumor movement and deformation was suspected. Therefore, 4D treatment planning is only necessary for large tumor motion and deformation. However, a Monte Carlo calculation is always necessary, independent of tumor motion in the lung.