• Journal of the Korean Society of Safety
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• v.35 no.1
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• pp.12-17
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• 2020

This paper analyzes functions of component parts of D-Urban Railway's door system along with operation obstacle risks on frequency(the number of occurrences/year) and severity(delay time/the number of occurrences). Based on this, the paper presents improvements and current system's problems after obstacle risks of EMU and door system are appled. The obstacle of door system causes corrosion of main parts such as DCU due to heat problem of operation environment, problems of maintenance methods and deterioration. DCUs on PCBs with more than 50% pattern corrosion cause problems. Even though the number of door system's obstacle occurrences for the last 5 years is 42, along with 104 minutes of operation obstacle, EMU operation obstacle risk is low(Level 1), which indicates there is limit in matrix of railway risks presented by the standard of railway safety management system. Therefore, it is necessary to have railway risk matrix suitable for the field. Finally, the paper deducts the obstacle risks through frequency and severity. Since 2017 when the risks of EMU and door system's obstacle, that of EMU has been 24(47% reduced) and that of door system has been average 9.5 per year(23% reduced).

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1290-1303
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• 2005

In this research, a remote control system has been developed and implemented, which combines autonomous obstacle avoidance in real-time with force-reflective tele-operation. A tele-operated mobile robot is controlled by a local two-degrees-of-freedom force-reflective joystick that a human operator holds while he is monitoring the screen. In the system, the force-reflective joystick transforms the relation between a mobile robot and the environment to the operator as a virtual force which is generated in the form of a new collision vector and reflected to the operator. This reflected force makes the tele-operation of a mobile robot safe from collision in an uncertain and obstacle-cluttered remote environment. A mobile robot controlled by a local operator usually takes pictures of remote environments and sends the images back to the operator over the Internet. Because of limitations of communication bandwidth and the narrow view-angles of the camera, the operator cannot observe shadow regions and curved spaces frequently. To overcome this problem, a new form of virtual force is generated along the collision vector according to both distance and approaching velocity between an obstacle and the mobile robot, which is obtained from ultrasonic sensors. This virtual force is transferred back to the two-degrees-of-freedom master joystick over the Internet to enable a human operator to feel the geometrical relation between the mobile robot and the obstacle. It is demonstrated by experiments that this haptic reflection improves the performance of a tele-operated mobile robot significantly.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.408-412
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• 2003

Obstacle avoidance algorithm is very important on an unmanned vehicle. Therefore, in this research, we propose a algorithm of obstacle avoidance and we can prove through vehicle test and sensor experiments. Obstacle avoidance must be divided into two parts: the first part includes the longitudinal control for acceleration and deceleration and the second part is the lateral control for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are confirmed through vehicle tests.

• International Journal of Automotive Technology
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• v.4 no.4
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• pp.173-180
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• 2003

Obstacle avoidance is considered as one of the key technologies in an unmanned vehicle system. In this paper, we propose a method of obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. Obstacle avoidance consists of two parts: one longitudinal control system for acceleration; and deceleration and a lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. The method proposed for vehicle control, modeling, and obstacle avoidance has been confirmed through vehicle tests.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.183-192
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• 2003

Obstacle detection and avoidance are considered as one of the key technologies on an unmanned vehicle system. In this paper, we propose a method of obstacle detection and avoidance and it is composed of vehicle control, modeling, and sensor experiments. Obstacle detection and avoidance consist of two parts: one is longitudinal control system for acceleration and deceleration and the other is lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control system of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are evaluated through road tests.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2387-2392
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• 2003

In this paper, We designed the local path planning direction algorithmusing fuzzy controller applied fuzzy logic. Algorithm decieded a direction angle by theposition of obstacle, the distance with obstacle, the progress direction of robot, the speed of vehicles and the perception area of sensor. The robot designed with proposed algorithm carried out soft moving without any particular operation, and we could observe that it had very soft curved moving as if an expert drove.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.219-228
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• 2022

The purpose of this study is to explore what obstacles adult undergraduate experience in adapting to college life. To this end, in-depth interviews were conducted with 32 adult undergraduate attending colleges in Daegu and Gyeongbuk. For the study, Colaizzi's phenomenological research method was used and analyzed. As a result of the analysis, eight factors such as relation obstacle, bachelor's and curriculum operation obstacle, social recognition obstacle, study ability obstacle, college environment obstacle, economic obstacle, personal disposition obstacle, and temporal obstacle were found. Through the above research results, it was found that the college environment, which is operated mainly by general college students, is expressed as various types of obstacle for adult undergraduate who work and study at various ages and experiences. Based on the derived obstacle factors, it is expected that a follow-up study will be conducted to develop a measurement tool that can empirically explore the obstacle of adult undergraduate to adapt to college life.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.65-73
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• 2024

This paper presents a path planning optimization model for the engineering units to install obstacles in the shortest time during wartime. In a rapidly changing battlefield environment, engineering units operate various engineering obstacles to fix, bypass, and delay enemy maneuvers, and the success of the operation lies in efficiently planning the obstacle installation path in the shortest time. Existing studies have not reflected the existence of obstacle material storage that should be visited precedence before installing obstacles, and there is a problem that does not fit the reality of the operation in which the installation is continuously carried out on a regional basis. By presenting a Mixed Integrer Programming optimization model reflecting various constraints suitable for the battlefield environment, this study attempted to promote the efficient mission performance of the engineering unit during wartime.

• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.105-111
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• 2009

In this paper, we provide experimental results and verification for obstacle avoidance algorithm 'ELA(Emergency Level Around)', which is applicable to rescue robots. ELA is a low level intelligence-based obstacle avoidance algorithm, so can be used in fast mobile robots requiringhigh speed in operation with little computational load. Constructed system for experiments consist of laptop, sensors, peripheral devices and mobile robot platform VSTR(Variable Single-tracked Robot) to realize predetermined scenarios. Finally, experiment was conducted in indoor surroundings including miscellaneous things as well as dark environment to show fitness and robustness of ELA for rescue, and it is shown that VSTR navigates endowed area well with real-time obstacle avoidance based on ELA. Therefore, it is concluded that ELA can be a candidate algorithm to increase mobility of rescue robots in real situation.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.7
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• pp.737-742
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• 2013

Recently, unmanned aircrafts for safe measurement in hazardous locations have been developed. In a method of operation of unmanned aircraft vehicles (UAV), there are two methods of manual control and automatic control. Small UAVs are used for low altitude surveillance flights where unknown obstacles can be encountered. Obstacle avoidance is one of the most challenging tasks which the UAV has to perform with high level of accuracy. In this study, we used a laser range finder as an obstacle detector in automatic navigation of unmanned aircraft to patrol the destination automatically. We proposed a system to avoid obstacles automatically by measuring the angle and distance of the obstacle using the laser range finder.