• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.141-144
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• 1996

This study deals with the problem of the recognition of the preceding vehicles by image processing. The purpose of this study is the development of the equipment to prevent a collision with preceding vehicles during driving the vehicle. In order to decrease the processing time and increase reliability, at first, the traffic lane is extracted. It is determined by detecting road edges and calculating their tangent. After the traffic lane is gotten, the position of the vehicle is searched inside the lane. The features used to detect the vehicles in the algorithm are shadow of the vehicle, vertical edges, horizontal edges, and symmetrical segment. The preceding vehicles are extracted successfully by this method.

• Journal of the Korean Society of Safety
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• v.32 no.1
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• pp.1-8
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• 2017

In industry AGV's(automated guided vehicles) that can detect and follow guidelines drawn on the factory floor using magnetic or optical sensors are widely used. However, such AGV's without preview capability cannot effectively avoid collision with obstacles that may occasionally pass through the guideline. Furthermore, without preview information, they consume much energy at the right angle corners as they have to make sudden directional change. Also, the risk of dropping payloads increases in such situations. In this study, infrared preview sensors were adopted to a mobile robot for detecting not only the current position but also the forward position of the guideline and the preview control technique was applied to optimally control the mobile robot's motion using the information from the infrared preview sensors. Then the effectiveness of this approach was investigated through a series of experiments. The experimental result shows that the proposed approach is effective for safety enhancement as well as for better efficiency.

• 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.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.12-19
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• 2015

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.300-304
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• 1993

Chip formation control is an important problem in the automation of manufacturing process, since the continuous chip can cause catastrophic failures of the tooling and entangle the workpiece causing damage. However, it is impossible to predict chip form correctly due to the complex nature of cutting process. In order to detect the chip form for unmanned manufacturing, a new identification method is proposed. The feasibility of using acoustic emission signals from the sensing plate for identification of chip form is investigated. Experiments were conducted under the various cutting conditions. When the acoustic emission sensor is attached to the sensing plate, it turns out that the moving averaged AE signals correlated well with the collision of segmented chips with the plate. The sensitivity of moving averaged AE signals to chip congestions due to continuous chip formation is illustrated as well.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.4
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• pp.173-180
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• 2014

Random access protocols feature inherent sensing functionality and distributed coordination, making them suitable for cognitive radio communication environments, where secondary users must detect the white space of the primary spectrum and utilize the idle primary spectrum efficiently without centralized control. These characteristics have led to the adoption of carrier-sensing-multiple-access/collision-avoidance (CSMA/CA) in cognitive radio. This paper proposes a new analytical framework for evaluating the performance of a CSMA/CA protocol that considers the characteristics of idle periods based on the primary traffic behavior in cognitive radio systems. In particular, the CSMA/CA-based secondary network was analyzed in the terms of idle period utilization, which is the average effective data transmission time portion in an idle period. The use of the idle period was maximized by taking its statistical features into consideration.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.5
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• pp.178-185
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• 1999

Recently, Collision Warning System is developed to improve vehicle safety. This system chiefly uses radar. But the detected vehicle from radar must be decide whether it is the vehicle in the same lane of my vehicle or not. Therefore, Vision System is needed to detect traffic lane. As a preparative step, this study presents the development of algorithm to recognize traffic lane curve direction. That is, the Neural Network that can recognize traffic lane curve direction is constructed by using the information of short distance, middle distance, and decline of traffic lane. For this procedure, the relation between used information and traffic lane curve direction must be analyzed. As the result of application to sampled 2,000 frames, the rate of success is over 90%.t text here.

• Proceedings of the KSR Conference
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• 1999.05a
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• pp.307-314
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• 1999

The potential use of ranging sensors for reducing the occurrence of accidents in real environment is explored by many companies and laboratories. Most of the sensors under investigation utilize the FMCW(Frequency Modulated Continuous Wave) waveforms. The automotive environment presents to the FMCW radar sensor a multitude of moving and fixed targets and the sensor must detect and track only the targets which may pose a threat of collision or passengers accident. The sensor must function accurately in the presence of background echoes generated by moving and fixed targets, ground reflections, atmospheric noises, including rains, fog, and, snow and noise generated within the receiver. False detection of the desired target in this environment may issue false alarms. That may be dangerous to the passenger and the vehicle. A high false alarm rate is totally unacceptable. The false alarm mechanism consists of noise peaks, crossing the threshold and the undesired response of the system to off lane targets which are not potentially hazardous to the radar equipped vehicle. This paper presents an improve technique safety performance for driver-less operation using FMCW radar sensors.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1368-1370
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• 2000

The automotive environment presents to the FMCW radar sensor a multitude of moving and fixed targets and the sensor must detect and track only the targets which may pose a threat of collision or passengers accident. The sensor must function accurately in the presence of background echoes generated by moving and fixed targets, ground reflections, atmospheric noises, including rains, fog, and, snow and noise generated within the receiver. False detection of the desired target in this environment may issue false alarms. That may be dangerous to the passenger and the vehicle. A high false alarm rate is totally unacceptable. The false alarm mechanism consists of noise peaks, crossing the threshold and the undesired response of the system to off lane targets which are not potentially hazardous to the radar equipped vehicle. This paper presents an improve technique safety performance for driver-less operation using FMCW radar sensors.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.114-120
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• 2017

The work present in this paper deals with a navigation problem for multiple mobile robots in unknown indoor 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. The environments simulated in this work are dynamic ones which contain not only static but also moving obstacles. In order to guide the robot to move along a collision-free path and reach the goal, this paper presented a navigation method based on fuzzy approach. Then genetic algorithms were applied to optimize the membership functions and rules of the fuzzy controller. The simulation results verified that the proposed method effectively addresses the mobile robot navigation problem.