• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.139-143
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• 2004

Lee et al have proposed a framework for the linguistic map-based navigational planning of a mobile robot on dynamic environment and provided simulation results applied it to the static environment[1], In this paper, we extends the navigational planning of a mobile robot into dynamic environment. There are two kinds of dynamic obstacles： (1) Time-obstacles that change condition of obstacles with time. (2) Space-obstacles that move their position with time. We propose an algorithm which a mobile robot identifies and avoids the two kinds of dynamic obstacles. The proposed algorithm consists of two stages： (1) The fuzzy logic-based perception stage which identifies the dynamic obstacles around a mobile robot by using sensory data and fuzzy rules, (2) The planning stage which plans the path to goal by avoiding the dynamic obstacles[2-6]. We provide computer simulation results for a mobile robot in order to show the validity of the proposed algorithm.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.583-586
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• 2003

There are electric four-wheeled vehicles to assist elder people. Because of the vehicles'dynamic characteristic such as impossible to move abeam, it is difficult for these people who has little experience and has little knowledge to drive. Also to judge the future state of dynamic obstacles and to decide how to elude them safely are more difficult. We installed the predictive fuzzy controller(evaluates the future states which several kinds of operation candidates were done and chooses the best one) that modeled humans'algorithms in the system. Human predicts the future states of dynamic obstacles and chooses an operation(wait, steer, go back, etc) to elude safely. To elude dynamic obstacles flexibly, we added expert's knowledge for safe driving to this controller. In this paper, we propose the intelligent soft driving system by the controller that can elude dynamic obstacles safely, and we confirm the effectiveness by a simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.11
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• pp.1193-1199
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• 2014

To achieve safe and high-speed navigation of a mobile service robot, velocity of dynamic obstacles should be considered while planning the trajectory of a mobile robot. Trajectory planning schemes without considering the velocity of the dynamic obstacles may collide due to the relative velocities or dynamic constraints. However, the general planning schemes that considers the dynamic obstacle velocities requires long computational times. This paper proposes a velocity control scheme by scaling the time step of trajectory to deal with dynamic obstacle avoidance problem using the RNLVO (Robot Nonlinear Velocity Obstacles). The RNLVO computes the collision conditions on the basis of the NLVO (Nonlinear Velocity Obstacles). The simulation results show that the proposed scheme can deal with collision state in a short period time. Furthermore, the RNLVO computes the collisions using the trajectory of the robot. As a result, accurate prediction of the moving obstacles trajectory does not required.

• 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 Electrical Engineering and Technology
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• v.12 no.2
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• pp.918-925
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• 2017

This paper presents a path planning problem for multi-robot system in the environment with dynamic obstacles. In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly, a navigation method based on fuzzy logic controllers has been developed by using proximity sensors. There are two kinds of fuzzy controllers developed in this work, one is used for obstacle avoidance and the other is used for orientation to the target. Both static and dynamic obstacles are included in the environment and the dynamic obstacles are defined with no type of restriction of direction and velocity. Here, the environment is unknown for all the robots and the robots should detect the surrounding information only by the sensors installed on their bodies. The simulation results show that the proposed method has a positive effectiveness for the path planning problem.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.396-401
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• 2004

Recently a framework for the cognition-based navigational planning of a mobile robot on dynamic environment has been proposed, and simulation results applied it to the static environment been presented [1]. In this paper, we propose a linguistic map-based framework for the navigational planning of mobile robots, which is applicable to the dynamic environment including not only static obstacles but also dynamic obstacles such as temporal-spatio obstacles, by extending Lee et al. 's framework, and provide computer simulation results obtained by applying to a mobile robot on the dynamic environment in order to show the validity of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.141-147
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• 2008

In this paper, we present one approach to achieve safe navigation in indoor dynamic environment. So far, there have been various useful collision avoidance algorithms and path planning schemes. However, those algorithms have a fundamental limitation that the robot can avoid only "visible" obstacles. In real environment, it is not possible to detect all the dynamic obstacles around the robot. There exist a lot of "occluded" regions due to the limitation of field of view. In order to avoid possible collisions, it is desirable to consider visibility information. Then, a robot can reduce the speed or modify a path. This paper proposes a safe navigation scheme to reduce the risk of collision due to unexpected dynamic obstacles. The robot's motion is controlled according to a hybrid control scheme. The possibility of collision is dually reflected to a path planning and a speed control. The proposed scheme clearly indicates the structural procedure on how to model and to exploit the risk of navigation. The proposed scheme is experimentally tested in a real office building. The presented result shows that the robot moves along the safe path to obtain sufficient field of view, while appropriate speed control is carried out.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.418-422
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• 2005

In this paper, a novel algorithm capable of detecting generic obstacles on a flat surface is proposed. The algorithm fundamentally exploits a distortion phenomena taken place in remapping process of original stereo images to a virtual top-view. Based on the distortion phenomena, we construct stereo polar histograms of edge maps, detect peaks on them, and search for matched peaks on both histograms using a Dynamic Programming (DP). Eventually, the searched corresponding peaks lead to estimate obstacles' positions. The advantages of the proposed algorithm are that it is not largely affected by an intensity difference between a pair of stereo images and does not depend on the typical stereo matching methodologies. Furthermore, the algorithm identifies the obstacles' positions quite robustly.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.233-238
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• 2010

This paper describes a multi-mobile robot system with fuzzy rule based structure in collision avoidance. Collision avoidance is an important function to perform a given task collaboratively and cooperatively in multi-mobile robot environments. So the important but challenging problem is handled in this paper. Considered obstacles for collision avoidance between multi mobile robots are static, dynamic, or both of them at the same time. Using the fuzzy rule based structure, distance and angle from a robot to obstacles are described as fuzzy linguistic values and steering angle for the robot are updated from the collision environments. As a result, the multi-mobile robot can modify a global path from a robot itself to its own target. In addition, avoiding collision with static or dynamic obstacles for the robot system can be achieved. Simulation based experimental results are given to show usefulness of this method.