• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.377-388
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• 2020

In this paper, the autonomous mobile robot whit only LRF sensors proposes an algorithm for avoiding moving obstacles in an environment where a global map containing fixed obstacles. First of all, in oder to avoid moving obstacles, moving obstacles are extracted using LRF distance sensor data and a global map. An ellipse-shaped safety radius is created using the sum of relative vector components between the extracted moving obstacles and of the autonomuos mobile robot. Considering the created safety radius, the autonomous mobile robot can avoid moving obstacles and reach the destination. To verify the proposed algorithm, use quantitative analysis methods to compare and analyze with existing algorithms. The analysis method compares the length and run time of the proposed algorithm with the length of the path of the existing algorithm based on the absence of a moving obstacle. The proposed algorithm can be avoided by taking into account the relative speed and direction of the moving obstacle, so both the route and the driving time show higher performance than the existing algorithm.

• 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.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.663-673
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• 2007

This paper presents a new moving obstacle detection method using an optical flow in mobile robot with an omnidirectional camera. Because an omnidirectional camera consists of a nonlinear mirror and CCD camera, the optical flow pattern in omnidirectional image is different from the pattern in perspective camera. The geometry characteristic of an omnidirectional camera has influence on the optical flow in omnidirectional image. When a mobile robot with an omnidirectional camera moves, the optical flow is not only theoretically calculated in omnidirectional image, but also investigated in omnidirectional and panoramic images. In this paper, the panoramic image is generalized from an omnidirectional image using the geometry of an omnidirectional camera. In particular, Focus of expansion (FOE) and focus of contraction (FOC) vectors are defined from the estimated optical flow in omnidirectional and panoramic images. FOE and FOC vectors are used as reference vectors for the relative evaluation of optical flow. The moving obstacle is turned out through the relative evaluation of optical flows. The proposed algorithm is tested in four motions of a mobile robot including straight forward, left turn, right turn and rotation. The effectiveness of the proposed method is shown by the experimental results.

• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.183-190
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• 2007

The most important thing for navigation of a mobile robot is to find the most suitable path and avoid the obstacles in the static and dynamic environment. This paper presents a method to search the optimal path in start space extended to time domain with considering a velocity and a direction of moving obstacles. A modified version of $A^*$ algorithm has been applied for path planning in this work and proposed a method of path search to avoid a collision with moving obstacle in space-tim domain with a velocity and an orientation of obstacles. The velocity and the direction for moving obstacle are assumed as linear form. The simulation result shows that a mobile robot navigates safely among moving obstacles of constant linear velocity. This work can be applied for not only a moving robot but also a legged humanoid robot and all fields where the path planning is required.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.3
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• pp.143-150
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• 2008

In this paper, we investigate a real-time environment recognition system based on stereo vision for moving object. This system consists of stereo matching, obstacle detection and distance estimation. In stereo matching part, depth maps can be obtained real road images captured adjustable baseline stereo vision system using belief propagation(BP) algorithm. In detection part, various obstacles are detected using only depth map in case of both v-disparity and column detection method under the real road environment. Finally in estimation part, asymmetric parabola fitting with NCC method improves estimation of obstacle detection. This stereo vision system can be applied to many applications such as unmanned vehicle and robot.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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• pp.19-26
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• 1995

In this paper, a fuzzy-neural hybrid control approach is proposed for controlling a mobile robot that can avoid an unexpected obstacle in a navigational space. First, to describe the global structure of a known environment, a heuristic collision-free space band is introduced. Based on the band, the moving information in the known environment is trained to a neural controller. Then, during the execution of a mobile robot navigation moving information at each position is given the neural controller. If the mobile robot encounters an unexpected obstacle, a fuzzy controller activates to avoid the unexpected obstacle. Finally, some numerical examples are presented to demonstrate the control algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.10
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• pp.936-940
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• 2013

As the ageing population grows around the world, the demand for electric wheelchairs, an important mobility assistance device for the disabled and elderly, is gradually increasing. Therefore, a number of studies related to intelligent wheelchairs are actively underway to improve safety and comfort for wheelchair users. However, previous collision avoidance studies for intelligent wheelchairs have concentrated on collision avoidance methods with the shortest distance and by only changing either velocity or heading angle, rather than considering the forces exerted on the user. If a collision avoidance algorithm that does not consider these forces is applied to an intelligent wheelchair, there is a possibility of an accident due to falling as wheelchair users are generally disabled and elderly people. In this paper, we propose a collision avoidance algorithm which minimizes the forces exerted on a wheelchair user by minimizing the variation of the wheelchair's velocity and heading angle when the sizes, positions, velocities, and heading angles of a wheelchair and a moving obstacle are known.