• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.3 s.309
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• pp.31-40
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done. Informations from various sensors can find obstacles and make path. In spite of many solutions of finding optimal path, each can be applied to only a constrained condition. This means that it is difficult to find a universal algorithm. A optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose the algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers. It has an advantage of fast planning and simple operation. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in any direction. When a robot meets moving obstacles, it avoids obstacles in a random direction. RAS method using obstacle information from variable sensors is useful to get minimum path length to goal.

• Journal of Advanced Navigation Technology
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• v.12 no.1
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• pp.1-7
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• 2008

International Civil Aviation Organization(ICAO) adopted VOR(Very high frequency Omni-Range) as an international standard air navigation system in 1949 and recommended every country to make use of it in formulating air route and guiding take-off and landing of an aircraft. VOR is quite a useful navigation system so that more than 2,000 VORs have been installed all over the world including 39 in Korea: however, VOR signal could be easily affected by its circumstance like a mountainous area because it provides navigation information through AM and FM of VHF carrier. Therefore this study intends to investigate how much VOR performance is affected by its circumstances. For this purpose, the performance of the 10 VORs influenced by 24 obstacles are measured and analyzed by using an aircraft equipped with measuring instruments. This study may give us a feasible solution of problems related to the VOR siting in the future.

• Journal of KIISE:Software and Applications
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• v.36 no.4
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• pp.291-297
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• 2009

This paper introduces an electronic travel aid, named SmartWand, which detects obstacles using a ultrasonic sensor. In addition to obstacle detection, the SmartWand senses color information of objects and the environmental brightness. It is designed to be attached to a ordinary white cane in order to detect the obstacles at head-hight which cannot be covered by the cane. We have improved the first version of the SmartWand based on a user evaluation. The second version is much lighter and smaller than the previous one. It has been enhanced by two new functions. The SmartWand eliminates impact errors due to tapping the ground using a moving average filtering algorithm and restricts the detection range to the path in the moving direction using an acceleration sensor. We have tested these functions in various environments to determine the parameters for these functions.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.6 s.312
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• pp.1-8
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done recently. Informations from various sensors can be used to find obstacles and plan feasible path. In spite of many solutions of finding optimal path, each can be applied in only a constrained condition. This means that it is difficult to find university good algorithm. An optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose an algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers and cumulative numbers. It has an advantage of fast planning time and completeness of path if one exists. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in dynamic environments. Using the information of the start and destination position, the RAS can be performed for collision-free navigation by reforming feasible paths repeatedly in dynamic environments.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.470-477
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• 2009

Modular reconfigurable robots with physical docking capability easily adapt to a new environment and many studies are necessary for the modular robots. In this paper, we propose a vision-based fuzzy autonomous docking controller for the modular docking robots. A modular docking robot platform which performs real-time image processing is designed and color-based object recognition method is implemented on the embedded system. The docking robot can navigate to a subgoal near a target robot while avoiding obstacles. Both a fuzzy obstacle avoidance controller and a fuzzy navigation controller for subgoal tracking are designed. We propose an autonomous docking controller using the fuzzy obstacle avoidance and navigation controllers, absolute distance information and direction informations of robots from PSD sensors and a compass sensor. We verify the proposed docking control method by docking experiments of the developed modular robots in the various environments with different distances and directions between robots.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.6
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• pp.535-542
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• 2011

The Global Navigation Satellite System(GNSS) is being utilized in numerous applications. The research for autonomous guided vehicles(AGVs) using precise positioning of GNSS is in progress. GNSS based AGVs is useful for setting driving path. This AGV system is more efficient than the previous one. Escipecially, the obstacle is positioned the driving path. Previcious AGVs which follow marker or wires laid out on the road have to stop the front of obstacle. But GNSS based AGVS can continuously drive using obstacle avoidance. In this paper, we developed collision avoidance system for GNSS based AGV using laser scanner and collision avoidance path setting algorithm. And we analyzed the developed system.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.11-19
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• 2013

For an autonomous multi-mobile robot system, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the cost function from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.11
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• pp.1442-1447
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• 2018

Since the indoor location recognition system using RFID is a method for predicting the indoor position, an error occurs due to the surrounding environment such as an obstacle. In this paper, we plan to reduce errors using back propagation neural networks. The neural network adjusts and trains the connection values between the layers to reduce the error between the actual position of the object with the reader and the expected position of the object through the experiment. In this paper, we propose a method that uses the median method and the radiation method as input to the neural network. Among the two methods, we want to find out which method is more effective in recognizing the actual position in an environment with obstacles and reduce the error. Consequently, the method using the median has less error, and we confirmed that the more the number of data, the smaller the error.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1653-1659
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• 2022

Virtual reality content provides users with a high sense of immersion by using HMD devices. However, while wearing the HMD device, it is difficult to determine the user's location or distance from obstacles, resulting in injuries due to physical collisions. In this paper, we propose a reminder module to prevent accidents by notifying the risk of collision with obstacles while wearing the HMD device. The proposed module receives the user's state from the acceleration and gyro sensor and determines the motion that is likely to cause a collision. If there is an obstacle in the expected collision range, a buzzer sounds to the wearer. As a result of the experiment, the accuracy of obstacle detection in the state of wearing the HMD was 86.6% in the 1st stage and 83.3% in the 2nd stage, confirming the performance of the accident prevention reminder.

• Journal of Platform Technology
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• v.9 no.2
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• pp.46-54
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• 2021

Recently, interest in the safety of Self-driving has been increasing. Self-driving have been studied and developed by many universities, research centers, car companies, and companies of other industries around the world since the middle 1980s. In this study, we propose the automatic extraction method of the threatening obstacle on the Road for the Self-driving. A threatening obstacle is defined in this study as a comparatively large object at center of the image. First of all, an input image and its decreased resolution images are segmented. Segmented areas are classified as the outer or the inner area. The outer area is adjacent to boundaries of the image and the other is not. Each area is merged with its neighbors when adjacent areas are included by a same area in the decreased resolution image. The Obstacle area and Non Obstacle area are selected from the inner area and outer area respectively. Obstacle areas are the representative areas for the obstacle and are selected by using the information about the area size and location. The Obstacle area and Non Obstacle area consist of the threatening obstacle on the road. Through experiments, we expect that the proposed method will be able to reduce accidents and casualties in Self-driving.