• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.771-779
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• 2010

This paper presents a method that integrates the geometric path tracking and the obstacle avoidance for nonholonomic mobile robot. The mobile robot follows the path by moving through the turning radius given from the pure pursuit method which is the one of the geometric path tracking methods. And the obstacle generates the obstacle potential, from this potential, the virtual force is obtained. Therefore, the turning radius for avoiding the obstacle is calculated by proportional to the virtual force. By integrating the turning radius for avoiding the obstacle and the turning radius for following the path, the mobile robot follows the path and avoids the obstacle simultaneously. The effectiveness of the proposed method is verified through the real experiments for path tracking only, static obstacle avoidance, dynamic obstacle avoidance.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.932-937
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• 2003

In this paper, we will explain about the unmanned vehicle control and modeling for combined obstacle avoidance and lane tracking. First, obstacle avoidance is considered as one of the important technologies in the unmanned vehicle. It is consisted by two parts: the first part includes the longitudinal control system for the acceleration and deceleration and the second part is the lateral control system for the steering control. Each system uses to the obstacle avoidance during the vehicle moving. Therefore, we propose the method of vehicle control, modeling and obstacle avoidance. Second, we describe a method of lane tracking by means of vision system. It is important in the unmanned vehicle and mobile robot system. In this paper, we deal with lane tracking and image processing method and it is including lane detection method, image processing algorithm and filtering method.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.928-933
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• 2012

In this paper, the IR and compass sensors for the underwater system were used. The walls of the water tank have been recognized and avoided treating the walls as obstacles by the bio-mimetic underwater robot. This paper is consists of two parts: 1.The hardware part for the IR and compass sensors and 2.The software part for obstacle avoidance algorithm while the bio-mimetic robot is swimming with the obstacle recognition. Firstly, the hardware part controls through the RS-485 communications between a microcontroller and the bio-mimetic underwater robot. The software part is simulated for obstacle recognition and collision avoidance based upon the data from IR and compass sensors. Actually, the bio-mimetic underwater robot recognizes where is the obstacle as well as where is the bio-mimetic robot itself while it is moving in the water. While the underwater robot is moving at a constant speed recognizing the wall of water tank as an obstacle, an obstacle avoidance algorithm is applied for the wall following swimming based upon the IR and compass sensor data. As the results of this research, it is concluded that the bio-mimetic underwater robot can follow the wall of the water tank efficiently, while it is avoiding collision to the wall.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.691-694
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• 2000

In this paper, a motion control algorithm is proposed by using neural network system, which makes a robot arm successfully avoid unexpected obstacle when the robot is moving from the start to the goal position. During the motion, if there is an obstacle the vision system recognizes it. And in every time the optimization-algorithm quickly chooses a motion among the possible motions of robot. The proposed algorithm has a good avoidance characteristic in simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1657-1661
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• 2005

The velocity dipole field method is presented for real-time collision avoidance of mobile robots. The direction of motion of the obstacle is used as the axis of the dipole field, and the speed of the obstacle is used to proportionally strengthen the dipole field. The elliptical field lines of the dipole field are useful to skillfully guide the robot around obstacles, quite similar to the way humans avoid moving obstacles. Field modulation coefficient is also introduced to weaken the field effect as the obstacle recedes. The real-time algorithm of the velocity dipole field has been devised and experimentally tested on the robot soccer test-bed. The results show the capability of the new real-time collision avoidance strategy and how it can overcome the weaknesses in the conventional potential field method. The new method makes an explicit and proactive action of collision avoidance, unlike the conventional method, which forces the robot merely away from the obstacle aimlessly. The proposed method delivers greater capability with no considerable computational overhead

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.490-492
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• 2004

This paper presents an obstacle avoidance of a mobile robot by the subgoal generation using infrared sensors. When an obstacle appears on the path which the robot is moving forward the robot has to get information, such as distance between the robot and the obstacle and the shape of the obstacle for avoidance behavior. Our collision avoidance algorithm needs the only distance between the robot and the obstacles. The distances are used for subgoal generation. Simulation results show that a robot can go to the goal, carrying out subgoal generation and avoiding obstacles.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.192-197
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• 2009

In this paper, we proposed the obstacle avoidance system using a single camera image and LM(Levenberg-Marquart) neural network fuzzy controller. According to a robot technology adapt to various fields of industry and public, the robot has to move using self-navigation and obstacle avoidance algorithms. When the robot moves to target point, obstacle avoidance is must-have technology. So in this paper, we present the algorithm that avoidance method based on fuzzy controller by sensing data and image information from a camera and using the LM neural network to minimize the moving error. And then to verify the system performance of the simulation test.

• Journal of Ocean Engineering and Technology
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• v.30 no.5
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• pp.426-430
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• 2016

Recently, many unmanned surface vehicles (USVs) have been developed and researched for various fields such as the military, environment, and robotics. In order to perform purpose specific tasks, common autonomous navigation technologies are needed. Obstacle avoidance is important for safe autonomous navigation. This paper describes a vector field histogram+ (VFH+) based obstacle avoidance method that uses the monocular vision of an unmanned surface vehicle. After creating a polar histogram using VFH+, an open space without the histogram is selected in the moving direction. Instead of distance sensor data, monocular vision data are used for make the polar histogram, which includes obstacle information. An object on the water is recognized as an obstacle because this method is for USV. The results of a simulation with sea images showed that we can verify a change in the moving direction according to the position of objects.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.67-75
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• 1998

This paper presents a new robot motion planning method for moving obstacle avoidance. To consider the mobility of a moving obstacle, we define virtual distance function(VDF) between the robot and the obstacle. At each sampling time, we use the VDF to construct an artificial potential, considering the motion of obstacles. The robot moves according to the repulsive and attractive force vector induced by the artificial potential function. The proposed algorithm can be driven the robot to avoid moving obstacles in real time. Some simulation studies show the effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2381-2383
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• 2003

This paper presents an effective approach to dynamic obstacle avoidance for mobile robot. The main concept of this approach includes modified polar mapping for recognition of the moving obstacle in vision-based robot systems. To simplify the segmentation of the moving obstacle from the background and to obtain its relative position data the modified polar mapping is proposed. Dynamic moving obstacles are avoided with a vision sensor and stationary obstacles are avoided with a sonar sensor.