• 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.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.212-218
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• 2008

Collision avoidance is a fundamental and important task of an autonomous mobile robot for safe navigation in real environments with high uncertainty. Obstacles are classified into static and dynamic obstacles. It is difficult to avoid dynamic obstacles because the positions of dynamic obstacles are likely to change at any time. This paper proposes a scheme for vision-based avoidance of dynamic obstacles. This approach extracts object candidates that can be considered moving objects based on the labeling algorithm using depth information. Then it detects moving objects among object candidates using motion vectors. In case the motion vectors are not extracted, it can still detect the moving objects stably through their color information. A robot avoids the dynamic obstacle using the dynamic window approach (DWA) with the object path estimated from the information of the detected obstacles. The DWA is a well known technique for reactive collision avoidance. This paper also proposes an algorithm which autonomously registers the obstacle color. Therefore, a robot can navigate more safely and efficiently with the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.990-994
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• 1999

This paper proposes a new fuzzy-neural algorithm for navigation of a mobile robot with stationary and moving obstacles environment. The proposed algorithm uses fuzzy algorithm for its speed control and neuralnetwork for effective collision avoidance. Some computer simulation results for a mobile robot equipped with ultrasonic range sensors show that the suggested navigation algorithm is very effective to escape in stationary and moving obstacles environment.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.64-70
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• 2002

This paper proposes a new construction method of neural networks. The construction method consists of two fundmental ideas, which are a parallel selection-style evaluation and rules evolution. A new collision avoidance algorithm using genetic and neural network is proposed to avoid moving obstacles such as mobile robots. The input parameters of this algorithm is position of moving obstacles and target. Output is a regenerated direction of mobile robot. This algorithm is very simple and so, it is available to application of real time process. The pattern of collision avoidance is learned through test execution.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.57-69
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• 2000

A moving window technique for detecting a lane and obstacles using the Images captured by a CCD camera attached in an automobile, is proposed in this paper To process the dynamic images in real time, there could be many constraints on the hardware To overcome these hardware constraints and to detect the lane and obstacles in real time, the optimal size of window IS determined based upon road conditions and automobile states. By utilizing the sub-Images inside the windows, detection of the lane and obstacles become possible m real time. For each Image frame, the moving windows are re-determined following the predicted directions based on Kalman filtering theory to Improve detection accuracy, as well as efficiency The feasibility of proposed algorithm IS demonstrated through the simulated experiments of highway driving.

• 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.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.889-893
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• 2000

In this paper, a method to detect lanes and obstacles from the images captured by a CCD camera fitted in an automobile is proposed, and a new terminology “Moving Window” is defined. Processing the input dynamic images in real time can cause quite a few constraints in terms of hardware. In order to overcome these problems and detect lanes and obstacles in real time using the images, the optimal size of “Moving Window” is determined, based upon road conditions and automobile states. The real time detection is made possible through the technique. For each image frame, the moving window is moved in a predicted direction, the accuracy of which is improved by the Kalman filter estimation. The feasibility of the proposed algorithm is demonstrated through the simulated experiments of freeway driving.

• Journal of Korea Game Society
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• v.6 no.3
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• pp.3-12
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• 2006

Path-finding, one of the traditional Game A.I. problems, becomes an important issue to make games more realistic. Due to the limited resources in the computer system, path-finding systems sometimes produce a simplified and unrealistic path. The most relent researches have been focused on the path-finding avoiding only static obstacles. Various moving obstacles are however deployed in real games, a method avoiding those obstacles and producing a smooth path is necessary. In this paper, navigation mesh is used to represent 3D space and its topological characteristics are used for path-finding. Intellectual repulser and attractor are also used to avoid moving obstacles and to find an optimal path. We have evaluated the path produced by the method proposed in this paper and verified its usability in real game.

• 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.