• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.690-697
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• 2000

The objective of this study is to develop a method that is able to realize autonomous traveling for tractor-like robot on the slope terrain. A neural network (NN) and genetic algorithms (GAs) have been used for resolving nonlinear problems in this system. The NN is applied to create a vehicle simulator that is capable to describe the motion of the tractor robot on the slope, while it is impossible by the common dynamics way. Using this vehicle simulator, a control law optimized by GAs was established and installed in the computer to control the steering wheel of tractor robot. The autonomous traveling carried out on a 14-degree slope had initial successful results.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.2
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• pp.75-80
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• 2016

This study proposes a efficient technology to control the optimal trajectory planning and real-time implementation method which can perform autonomous travelling for unmaned factory automation. Online path planning should plan and execute alternately in a short time, and hence it enables the robot avoid unknown dynamic obstacles which suddenly appear on robot's path. Based on Route planning and control algorithm, we suggested representation of edge cost, heuristic function, and priority queue management, to make a modified Route planning algorithm. Performance of the proposed algorithm is verified by simulation test.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.217-225
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• 2016

In this paper, we propose an improved path planning method and obstacle avoidance algorithm for two-wheel mobile robots, which can be effectively applied in an environment where obstacles can be represented by circles. Firstly, we briefly introduce the rapidly exploring random tree (RRT) and single polar polynomial (SPP) algorithm. Secondly, we present additional two methods for applying our proposed method. Thirdly, we propose a global path planning, smoothing and obstacle avoidance method that combines the RRT and SPP algorithms. Finally, we present a simulation using our proposed method and check the feasibility. This shows that proposed method is better than existing methods in terms of the optimality of the trajectory and the satisfaction of the kinematic constraints.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.429-434
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• 2005

In this paper, the maze navigation system using image recognition for autonomous mobile robot is proposed. The proposed maze navigation system searches the target by image recognition method based on ADALINE neural network. The infrared sensor system must travel all blocks to find target because it can recognize only one block information each time. But the proposed maze navigation system can reduce the number of traveling blocks because of the ability of sensing several blocks at once. Especially, due to the simplicity of the algorithm, the proposed method could be easily implemented to the system which has low capacity processor.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.1
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• pp.43-50
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• 2014

This paper introduces a robot platform which can do weeding while traveling between rice seedlings stably against irregular land surface of a paddy field. Also, an autonomous navigation technique that can track on stable state without any damage of the seedlings in the working area is proposed. Detection of the rice seedlings and avoidance knocking down by the robot platform is achieved by the sensor fusion of a laser range finder (LRF) and an inertial measurement unit (IMU). These sensors are also used to control navigating direction of the robot to keep going along the column of rice seedling consistently. Deviation of the robot direction from the rice column that is sensed by the LRF is fed back to a proportional and derivative controller to obtain stable adjustment of navigating direction and get proper returning speed of the robot to the rice column.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.883-895
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• 2007

In this work, we present the development of a patrol robot which is intended to navigate outdoor rough terrain. Proposed mechanism consists of six legs for overcoming an obstacle, and six wheels for traveling. Also, in order to absorb vibration in rough terrain effectively, the slide-spring system and tubed type tire are adopted to each leg and each wheel. The control system of robot consists of several imbedded boards for management of lots of diverse devices such as sensors designed for rough terrain, motor controllers, camera, micro controller and so on. And the base system of the robot is designed to operate in real time and to surveille in the vicinity of the robot, and the robot system is controlled by wireless LAN connected to GUI-based remote control system, while CAN communication connects the control board and the device controllers for sensors and motor controllers. For operating this robot system efficiently, we propose the control algorithms for autonomous navigation using GPS, stabilization maintenance by posture control, obstacle-avoidance by impedance control, and obstacle-overcoming with interference-avoidance between wheels. The performance of the robot and the proposed algorithms are tested and proved by a set of experiments in outdoor rough terrain.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.4
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• pp.19-25
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• 2008

This paper proposes a hierarchically structured navigation algorithm for autonomous mobile robot under unknown environment based on fuzzy-neal network. The proposed algorithm consists of two basic layers as follows. The lower layer consists of two parts such as fuzzy algorithm for goal approach and fuzzy-neural algorithm for obstacle avoidance. The upper layer which is basically fuzzy algorithm adjusts the magnitude of the weighting factor depending on the environmental situation. The proposed algorithm provides an efficient method to escape local mimimum points as shown in the simulation result. Most simulation results show that this algorithm is very effective for autonomous mobile robots' traveling in unknown field.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.33-43
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• 2018

In this paper, we describe an sound tracking mobile robot suitable for areas where GPS is not available. Sound sensors are attached to four sides of the robot in order to locate the person in a danger, and the robot is supposed to move to the yelling person. The traveling distance of the mobile robot is calculated by the encoder attached to the wheel of the mobile robot. The moving direction of the mobile robot is measured by a gyro sensor on the robot. When the person in danger pushes a button of the mobile robot, the mobile robot transmits the trajectory data to a designated server.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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• pp.225-230
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• 2023

This research addresses sound command based human tracking problems for autonomous cleaning mobile robot in a networked AI space. To solve the problem, the difference among the traveling times of the sound command to each of three microphones has been used to calculate the distance and orientation of the sound from the cleaning mobile robot, which carries the microphone array. The cross-correlation between two signals has been applied for detecting the time difference between two signals, which provides reliable and precise value of the time difference compared to the conventional methods. To generate the tracking direction to the sound command, fuzzy rules are applied and the results are used to control the cleaning mobile robot in a real-time. Finally the experiment results show that the proposed algorithm works well, even though the mobile robot knows little about the environment.

• Journal of Platform Technology
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• v.11 no.2
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• pp.26-38
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• 2023

This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.