• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.327-330
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• 1995

If a mobile robot is used in a real situation, robot must face a moving obstacles. In that case, the collision avoidance algorithm for moving obstacle is a indispensible element in mobile robot control. We csrried out a research to find and evaluate the advanced algorithm for mobile robot. At first we generate the continous path for mobi;e robot. Then by creating a curved path for avoidance, the mobile robot can change its path smoothly. Smoothed path made the robot adapt more effectively to the changing of path. Under time-varying condition, computer simulation was performed to show the validation of proposed algorithm.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.345-348
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• 1997

In this paper, a motion control algorithm is developed using a fuzzy control and the optimization of performance function, which makes a robot arm avoid an unexpected obstacle when the end-effector of the robot arm is moving to the goal position. During the motion, if there exists no obstacle, the end-effecter of the robot arm moves along the pre-defined path. But if there exists an obstacle and close to the robot arm, the fuzzy motion controller is activated to adjust the path of the end-effector of the robot arm. Then, the robot arm takes the optimal posture for collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sizes of obstacles. It was concluded that the proposed algorithm gives a good performance for obstacle avoidance.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.131-139
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• 2024

Crew Transfer Vessels (CTVs) are primarily used for the maintenance of offshore wind farms. Despite being manually operated by professional captains and crew, collisions with other ships and marine structures still occur. To prevent this, the introduction of autonomous navigation systems to CTVs is necessary. In this study, research on the obstacle avoidance system of the autonomous navigation system for CTVs was conducted. In particular, research on obstacle avoidance simulation for CTVs using deep reinforcement learning was carried out, taking into account the currents and wind loads in offshore wind farms. For this purpose, 3 degrees of freedom ship maneuvering modeling for CTVs considering the currents and wind loads in offshore wind farms was performed, and a simulation environment for offshore wind farms was implemented to train and test the deep reinforcement learning agent. Specifically, this study conducted research on obstacle avoidance maneuvers using MATD3 within deep reinforcement learning, and as a result, it was confirmed that the model, which underwent training over 10,000 episodes, could successfully avoid both static and moving obstacles. This confirms the conclusion that the application of the methods proposed in this study can successfully facilitate obstacle avoidance for autonomous navigation CTVs within offshore wind farms.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1227-1233
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• 2011

An effective method of obstacle avoidance for omni-directional mobile robots is proposed to avoid moving obstacles in dynamic environments. Our method uses the concept of circle lists which represent the trajectories of robot and obstacles. This method predicts not only collision position but also collision time, and hence it enables the robot avoiding the most urgent collision first. In order to avoid obstacles, our method uses artificial repulsive force and contraction force. Simulation results show that the robot could avoid obstacles effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.2
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• pp.155-163
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• 2000

This paper presents a path planning method of the sensor based intelligent vehicle using fuzzy logic controller for avoidance of moving obstacles in unknown environments. Generally it is too difficult and complicated to control intelligent vehicle properly by recognizing unknown terrain with sensors because the great amount of imprecise and ambiguous information has to be considered. In this respect a fuzzy logic can manage such the enormous information in a quite efficient manner. Furthermore it is necessary to use the relative velocity to consider the mobility of obstacles, In order to avoid moving obstacles we must deliberate not only vehicle's relative speed toward obstacles but also self-determined acceleration and steering for the satisfaction of avoidance efficiency. In this study all the primary factors mentioned before are used as the input elements of fuzzy controllers and output signals to control velocity and steering angle of the vehicle. The main purpose of this study is to develop fuzzy controllers for avoiding collision with moving obstacles when they approach the vehicle travelling with straight line and for returning to original trajectory. The ability are and effectiveness of the proposed algorithm are demonstrated by simulations and experiments.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.187-194
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• 2002

In this paper, a motion control algorithm is developed using a fuzzy control and the optimization of performance function, which makes a robot arm avoid an unexpected obstacle when the end-effector of the robot arm is moving to the goal position. During talc motion, if there exists no obstacle, the end-effector of the robot arm moves along the predefined path. But if these exists an obstacle and close to talc robot arm, the fuzzy motion controller is activated to adjust the path of the end-effector of the robot arm. Then, the robot arm takes the optimal posture far collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sites of obstacles. It was concluded that the proposed algorithm gives a good performance for obstacle avoidance.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2387-2392
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• 2003

In this paper, We designed the local path planning direction algorithmusing fuzzy controller applied fuzzy logic. Algorithm decieded a direction angle by theposition of obstacle, the distance with obstacle, the progress direction of robot, the speed of vehicles and the perception area of sensor. The robot designed with proposed algorithm carried out soft moving without any particular operation, and we could observe that it had very soft curved moving as if an expert drove.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.47-53
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• 2018

In this paper, we investigate a collision avoidance algorithm for unmanned aerial vehicles using potential field based on the relative velocity of obstacles. The potential field consists of the attraction force and the repulsive force that are generated for the target and the obstacles. And the field can be classified into the attractive potential field generated by the target and the repulsive potential field generated by the obstacle, respectively. In this study, we construct an attractive potential field as a function of the distance between the UAV and the target position. On the other hand, a repulsive potential field is created by a function of distance and the relative velocity of the obstacle with respect to the UAV. The proposed potential field based collision avoidance algorithm is evaluate through simulations.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.570-575
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• 2000

This paper presents a delayed time path planning method of the Autonomous Mobile Robot using fuzzy logic controller for avoidance of obstacles in unknown environment. It is the objective of this paper to develop fuzzy control algorithms using delayed time techniques to deal with moving obstacles randomly. This control method gives the benefit of the collision free movement in real time and optimal path to the pre-settled goal. The computer simulations are demonstrated the effective of the suggested control method in obstacle avoidance.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.266-268
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• 2005

Recently, the ability of sensing obstacles by oneself and creating suitable moving path in mobile robots are required to provide various kinds automation services. Therefore, in this paper, we studied the avoidance behavior of mobile robots from dynamic obstacles using potential function that minimizes distance and time. We examined the performance of the proposed algorithm by comparing the method of based on the geometrical experience in simulations.