• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.88-98
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• 1994

A new local path planning algorithm for free-ranging robots is proposed. Considering that a laser range finder has the excellent resolution with respect to angular and distance measurements, a simple local path planning algorithm is achieved by a directional weighting method for obtaining a heading direction of nobile robot. The directional weighting method decides the heading direction of the mobile robot by estimating the attractive resultant force which is obtained by directional weighting function times range data, and testing whether the collision-free path and the copen parthway conditions are satisfied. Also, the effectiveness of the established local path planning algorithm is estimated by computer simulation in complex environment.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.641-646
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• 2010

This paper presents algorithms for real-time navigation of a humanoid robot with a stereo vision but no other sensors. Using the algorithms, a robot can recognize its 3D environment by retrieving SIFT features from images, estimate its position through the Kalman filter, and plan its path to reach a destination avoiding obstacles. Our approach focuses on estimating the robot’s central walking path trajectory rather than its actual walking motion by using an approximate model. This strategy makes it possible to apply mobile robot localization approaches to humanoid robot localization. Simple collision free path planning and motion control enable the autonomous robot navigation. Experimental results demonstrate the feasibility of our approach.

• Journal of IKEEE
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• v.22 no.2
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• pp.440-445
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• 2018

The work presented in this paper deals with a navigation problem for a multiple mobile robots in unknown dynamic environments. The environments are completely unknown to the robots; thus, proximity sensors installed on the robots' bodies must be used to detect information about the surroundings. In order to guide the robots along collision-free paths to reach their goal positions, a navigation method based on a combination of primary strategies has been developed. Most of these strategies are achieved by means of fuzzy logic controllers, and are uniformly applied in every robot. In order to improve the performance of the proposed fuzzy logic, the genetic algorithms were used to evolve the membership functions and rules set of the fuzzy controller. The simulation experiments verified that the proposed method effectively addresses the navigation problem.

• 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 Korea Multimedia Society
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• v.23 no.8
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• pp.1088-1098
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• 2020

This paper proposes an obstacle avoidance method using a depth polar grid. Depth information is a crucial factor for determining the safe path for collision-free navigation of unmanned aerial vehicles (UAVs) as it can perceive the distance to the obstacles effectively. However, the existing depth-camera-based approaches for obstacle avoidance require computational y expensive path planning algorithms. We propose a simple navigation method using the polar-grid of the depth information obtained from the camera with narrow field-of-view(FOV). The effectiveness of the approach was validated by a series of experiments using software-in-the-loop simulation in a realistic outdoor environment. The experimental results show that the proposed approach successfully avoids obstacles using a single depth camera with limited FOV.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.624-630
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• 2007

The dynamic window approach(DWA) is a well known technique for reactive collision avoidance. It shows safe and efficient performance in real-world experiments. However, a robot can get stuck in local minima because no information about the connectivity of the free space is used to determine the motion. The global DWA can solve this problem of local minima by adding a navigation function. Even with the global DWA, it is still difficult for a robot to execute an abrupt change in its direction, for example, entering from the corridor to a doorway. This paper proposes a modified global DWA using the included angles of waypoints extracted from an optimal path. This scheme enables the robot to decelerate in advance before turning into the doorway. Therefore the robot can reach the goal position more safely and efficiently at high speeds.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.2
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• pp.679-687
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• 2019

This paper presents the autonomous swimming technology developed for an Autonomous Underwater Vehicle (AUV) operating in the underwater jacket structure environment. To prevent the position divergence of the inertial navigation system constructed for the primary navigation solution for the vehicle, we've developed kinds of marker-recognition based underwater localization methods using both of optical and acoustic cameras. However, these two methods all require the artificial markers to be located near to the cameras mounted on the vehicle. Therefore, in the case of the vehicle far away from the structure where the markers are usually mounted on, we may need alternative position-aiding solution to guarantee the navigation accuracy. For this purpose, we develop a sonar image processing based underwater localization method using a Forward Looking Sonar (FLS) mounted in front of the vehicle. The primary purpose of this FLS is to detect the obstacles in front of the vehicle. According to the detected obstacle(s), we apply an Occupancy Grid Map (OGM) based path planning algorithm to derive an obstacle collision-free reference path. Experimental studies are carried out in the water tank and also in the Pohang Yeongilman port sea environment to demonstrate the effectiveness of the proposed autonomous swimming technology.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.867-873
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• 2011

A navigation mesh (NavMesh) is a suitable tool for the representation of a three-dimensional game world. A NavMesh consists of convex polygons covering free space, so the path can be found reliably without detecting collision with obstacles. The main disadvantage of a NavMesh is the huge state space. When the $A^*$ algorithm is applied to polygonal meshes for detailed terrain representation, the pathfinding can be inefficient due to the many states to be searched. In this paper, we propose a method to reduce the number of states searched by using visibility tests to achieve fast searching even on a detailed terrain with a large number of polygons. Our algorithm finds the visible vertices of the obstacles from the critical states and uses the heuristic function of $A^*$, defined as the distance to the goal through such visible vertices. The results show that the number of searched states can be substantially reduced compared to the $A^*$ search with a straight-line distance heuristic.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.292-297
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• 2016

This paper presents a navigation problem for an autonomous mobile robot in an unknown environment. The environment contains various types of obstacles and is completely unknown to the robot. Therefore, all of the surrounding information must be detected by the robot's proximity sensors. A navigation method was developed based on a fuzzy inference system to guide the robot to move along a collision-free path and reach the goal position quickly. The obstacles are assumed to be static, and both regular and irregular types of obstacles were investigated. A wall following method is also proposed for a special environment that contains a labyrinth or sharp U-valley obstacles. Simulation results demonstrate that the proposed method has great potential for this navigation problem.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.3
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• pp.198-204
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• 2007

In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.