• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.11-16
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• 2023

The technology of 3D reconstruction, primarily relying on point cloud data, is essential for digitizing objects or spaces. This paper aims to utilize reinforcement learning to achieve the acquisition of point clouds in a given environment. To accomplish this, a simulation environment is constructed using Unity, and reinforcement learning is implemented using the Unity package known as ML-Agents. The process of point cloud acquisition involves initially setting a goal and calculating a traversable path around the goal. The traversal path is segmented at regular intervals, with rewards assigned at each step. To prevent the agent from deviating from the path, rewards are increased. Additionally, rewards are granted each time the agent fixates on the goal during traversal, facilitating the learning of optimal points for point cloud acquisition at each traversal step. Experimental results demonstrate that despite the variability in traversal paths, the approach enables the acquisition of relatively accurate point clouds.

• Journal of Drive and Control
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• v.20 no.4
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• pp.27-34
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• 2023

Weeding in orchards is closely associated with productivity and quality. The customary weeding process is both labor-intensive and time-consuming. To solve the problems, there is need for automation of agricultural robots and machines in the agricultural field. On the other hand, orchards have complicated working areas due to narrow spaces between trees and amorphous terrain. Therefore, it is necessary to develop customized robot technology for unmanned weeding work within the department. This study developed a path generation and path control method for unmanned weeding according to the orchard environment. For this, the width of the weeding span, the number of operations, and the width of the weeding robot were used as input parameters for the orchard environment parameters. To generate a weeding path, a weeding robot was operated remotely to obtain GNSS-based location data along the superheated center line, and a driving performance test was performed based on the generated path. From the results of orchard field tests, the RMSE in weeding period sections was measured at 0.029 m, with a maximum error of 0.15 m. In the steering period within row and steering to the next row sections, the RMSE was 0.124 m, and 0.047 m, respectively.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.6
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• pp.711-717
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• 2014

Global path planning for autonomous driving of unmanned ground vehicle is essential. When setting global path planning, its accuracy and effectiveness is increased if useful information such as terrain type of driving route has been reflected on global path planning. As a method to reflect the terrain type, there is a method to perform global path planning by applying the weight to each terrain type. At this time, how to assign appropriate weights corresponding to the terrain type is more important than anything. In this paper, we proposed a method to determine the weight for terrain type that may affect the results of global path planning. Moreover, we presented effective operation method and design results(GUI) to check the possibility of the use of the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.10
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• pp.194-199
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• 2001

In this paper, we propose a new locomotive mechanism using impulsive force for microcapsule-type endoscope. It has the compact size for movement in the colon and actuating mechanisms for hi-directional movement. The actuating mechanism resembles a pneumatic cylinder and consists of body, inertia mass(piston). spring. pneumatic source and calve. When valve is ON, the pneumatic impulsive force between piston and body drives them in two opposite direction. As the air in the body is passed away, the contrary movements are occurred by spring reaction. Therefore, the direction of body's motion is determined by the relative magnitude of two opposite impulsive forces, i.e., pneumatic and spring force. The effect of two impulsive forces can simply be controlled by On-Off time of solenoid valve.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.1
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• pp.33-40
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• 2000

In this paper, an integrated method for the path planning and motion control of wheeled mobile robots using a hybrid system model and control is presented. The hybrid model including the continuous dynamics and discrete dynamics with the continuous and discrete state vector is derived for a two wheel driven mobile robot. The architecture of the hybrid control system for real time path planning and following is designed which has the 3-layered hierarchical structure : the discrete event system using the digital automata as the higher process, the continuous state system for the wheel velocity controls as the lower process, and the interface system as the interaction process between the continuous system as the low level and the discrete event system as the high level. The reference motion commands for autonomous navigation are generated by the abstracted motion in the discrete event system. The motion control tasks including the feasible path planning and autonomous motion control with various initial conditions are investigated as the applications by the simulation studies.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.1
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• pp.31-40
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• 2021

The important goal of the unmanned vehicle technology is on controlling the direction and speed of the vehicle with information acquired from various sensors, without the intervention of the driver, until the vehicle reaches to its destination. In this paper, our focus is on developing an unmanned conveyance system by exploiting low-cost sensing technology for indoor factories or warehouses, where the moving range of the vehicle is limited. To this end, we propose an architecture of a scalable automated conveyance system. Our proposed system includes a number of unmanned conveyance vehicles, and the efficient control mechanism of the vehicles without neither conflicts nor deadlock between the vehicles being simultaneously moved. By implementing the real prototype of the system, we successfully verify the efficiency and functionality of the proposed system.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.23-30
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• 2024

This paper studies a GPS error filtering method that takes into account the continuity of the ongoing path to enhance the safety of autonomous agricultural mobile robots. Real-Time Kinematic Global Positioning System (RTK-GPS) is increasingly utilized for robot position evaluation in outdoor environments due to its significantly higher reliability compared to conventional GPS systems. However, in orchard environments, the robot's current position obtained from RTK-GPS information can become unstable due to unknown disturbances like orchard canopies. This problem can potentially lead to navigation errors and path deviations during the robot's movement. These issues can be resolved by filtering out GPS information that deviates from the continuity of the waypoints traversed, based on the robot's assessment of its current path. The contributions of this paper is as follows. 1) The method based on the previous waypoints of the traveled path to determine the current position and trajectory. 2) GPS filtering method based on deviations from the determined path. 3) Finally, verification of the navigation errors between the method applying the error filter and the method not applying the error filter.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.1C
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• pp.26-35
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• 2006

In this paper, an automatic mobile robot system for a intelligent path planning using the detection scheme of the spatial coordinates based on stereo camera is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity map obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation. From some experiments on robot driving with 240 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the mobile robot and the objects, and relative distance between the other objects is found to be very low value of $2.19\%$ and $1.52\%$ on average, respectably.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.201-210
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• 2019

This paper proposes the AMCS(Agricultural Machine Control System that distinguishes farms using satellite photos or drone photos of farms and controls the self-driving and operation of farm drones and tractors. The AMCS consists of the LSM(Local Server Module) which separates farm boundaries from sensor data and video image of drones and tractors, reads remote control commands from the main server, and then delivers remote control commands within the management area through the link with drones and tractor sprinklers and the PSM that sets a path for drones and tractors to move from the farm to the farm and to handle work at low cost and high efficiency inside the farm. As a result of AMCS performance analysis proposed in this paper, the PSM showed a performance improvement of about 100% over Dijkstra algorithm when setting the path from external starting point to the farm and a higher working efficiency about 13% than the existing path when setting the path inside the farm. Therefore, the PSM can control tractors and drones more efficiently than conventional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.723-730
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• 2015

In this paper, a location tracking compensation algorithm based on the Least-Squares Method ($LCA_{LSM}$) was proposed to improve the autonomous tracking efficiency for the docent robot in exhibition hall, and the performance of the $LCA_{LSM}$ is analyzed by several practical experiments. The proposed $LCA_{LSM}$ compensates the collected location coordinates for the robot using the Least-Squares Method (LSM) in order to reduce the cumulated errors that occur in the Encoder/Giro sensor (E/G) and to enhance the measured tracking accuracy rates in the autonomous tracking of the robot in exhibition hall. By experiments, it was confirmed that the average error reduction rates of the $LCA_{LSM}$ are higher as 4.85% than that of the $LCA_{KF}$ in Scenario 1 (S1) and Scenario 2 (S2), respectively on the location tracking. In addition, it was also confirmed that the standard deviation in the measured errors of the $LCA_{LSM}$ are much more low and constant compared to that of the E/G sensor and the $LCA_{KF}$ in S1 and S2 respectively. Finally, we see that the suggested $LCA_{LSM}$ can execute more the stabilized location tracking than the E/G sensors and the $LCA_{KF}$ on the straight lines of S1 and S2 for the docent robot.